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The industrial development of emerging markets has been a powerful driver for mergers and acquisitions. The contributions collected in this book assess major M&A deals in the largest emerging capital markets (Brazil, Russia, India, China) and their role in shareholder value creation in the markets’ specific business environments. In addition, the book explores various dimensions of M&A deals in order to summarize the main trends in corporate control markets in the largest emerging countries, and how they differ from those in developed countries; to identify deal-performance relationships and the determinants of success or failure; to reveal the drivers for the premium in M&A deals; and to capture market responses to different M&A strategies. By doing so, the book makes a significant contribution to the literature, which has to date largely focused on developed markets.
In our research, we examine what macroeconomic factors determine and influence the credit cycle. In addition, our study contains four sections with theoretical and empirical parts, in which we describe how to measure credit cycles for developed and developing countries, and then introduce an important measure of the credit gap. Our results show a comparative analysis of credit cycles between different countries with different economic growth, and we have created an econometric model, which shows us the impact of macroeconomic factors according to the credit cycles for developing and developed economies.
The Pocket Guide contains the main indicators of the digital economy for the Russian Federation. Provides information on the use of ICT by individuals and enterprises, the development of e-government, personnel for the digital economy, telecommunications and the development of the ICT sector. International comparisons are shown on a number of indicators. The handbook includes information from the Federal State Statistics Service (Rosstat), the Ministry of Digital Development, Communications and Mass Communications of the Russian Federation, the Ministry of Education and Science of the Russian Federation, the Bank of Russia, OECD, Eurostat, ITU, the World Intellectual Property Organisation, and the results of its own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.
Urban population is growing worldwide. Our societies are facing grand challenges like climate change and growing inequalities between people. There is an increasing need to develop cities that are environmentally and socially sustainable, functional and supporting well-being of their inhabitants. When striving towards these goals, transportation and mobility play a crucial role. Easy and environmentally sustainable mobility options are called for in most cities. For these to attract users, they need to be safe and pleasant, providing positive experiences and well-being in addition to efficiency in time or cost.
NECTAR conference is organized with a title “Towards Human Scale Cities – Open and Happy” to reflect the new requirements of urban transportation. This 15th NECTAR conference, organized in Helsinki 5th - 7th June 2019, provides presentations by world-class keynotes Mikael Colville-Andersen and Professor Tim Schwanen, who approach human scale mobility from the viewpoints of a designer and a researcher. More than 140 scientific presentations explore advancements in the field of transport, communication and mobility, with a particular focus on good quality mobility options for people. The focus of the conference is urban transportation and the new possibilities that open data and digital technologies provide for mobility solutions and their research. Presentations provide food for thought concerning mobility choices and quality, new mobility solutions like MaaS, and policies that are implemented to support them.
Helsinki offers an interesting environment for the 2019 NECTAR conference. It is the home of the busiest passenger harbor in Europe with a twin-city development with Tallinn across the bay, and a major air transportation hub between Europe and Asia. It is one of the fastest growing capital regions in Europe, with large densification developments taking place in old logistic centers: harbor areas of Jätkäsaari and Kalasatama and a train depot in Pasila. Public transportation is valued high by citizens, as well as politicians and planners making investment decisions for the future. First robotized buses are in operation and MaaS solutions are emerging. New bike sharing system is one of the most used in the world and has expanded to cover most of the city region. As everywhere in Europe, new forms of micromobility from electronic scooters to electric longboards are appearing on the streets making planners and police puzzled. The city has profiled itself as an open city: large amounts of open data about the region have been made available and the region of Helsinki is committed to open and transparent decision
and policy making. This supports also research in the major universities: University of Helsinki and Aalto University, the local organizers of the conference.
We anticipate that the conference days will forward our thinking on how to make cities more sustainable, functional and pleasant for people, and how to study them scientifically in a meaningful and transparent manner.
See the world’s #1 investor like never before―and learn how you can replicate his success
Many books have been written about Warren Buffett’s value-investing strategy, and volumes more have been written about becoming a top-tier value investor. Even so, no one can touch the success Warren Buffett has achieved. Why? In this revealing examination of Buffett’s success, practitioner, professor, and bestselling author Еlena Chirkova proposes the key to replicating his achievements is found in his acquisition practices as well as his investment strategy.
In The Warren Buffett Philosophy of Investment, she looks at the man in full to piece together the framework leading to his unmatched wealth-generating prowess. The cornerstone of her study goes beyond investment theory to show Buffett’s core wealth drivers are his philosophies behind Berkshire Hathaway. From his decision to create a joint stock company (instead of a mutual fund) to his hands-off policy with acquired companies to making himself a brand-name of mergers and acquisitions―she illustrates an intimate portrayal of Buffett operating behind the scenes by piecing together his career with scholarly diligence and scrutiny. Even well-read Buffett followers gain fresh insight into the man by discovering:
Additionally, readers are treated to extraordinary coverage of how Buffett strategically set up Berkshire Hathaway to suit his personal long-term investment strategy and provide almost cost-free leverage. See how Buffett’s singular acquisition tactics and portfolio investments earned Berkshire Hathaway the distinction as “the right home for the right people,” which gives him access to deals unobtainable by other companies and investors.
You’re only investing with half a strategy until you take your value investing to the next level with The Warren Buffett Philosophy of Investment.
We construct and compare the results of individual investment strategies: take into account trade, dynamics and costs, and assess the benefits of policy diversification. Our analysis is based on a set of 10 major currencies and an extended sample of 16 additional emerging market currencies. We implement foreign exchange strategies in FX markets against the ruble instead of the US dollar, as is customary in the foreign exchange literature. We find that the effectiveness of strategies depends on changing the ruble mode. We also provide evidence that combining strategies based on volatility offers a significant risk-adjusted yield improvement over either of the two strategies independently or with benchmarks.
We consider the issue of short term immunization of a bond-like obligation with respect to changes in interest rates using a portfolio of bonds. In the case that the zero-coupon yield curve belongs to a fixed low-dimensional manifold, the problem is widely known as parametric immunization. Parametric immunization aims to make the price sensitivity of the hedged portfolio for all parameters of the model zero. However, within a popular approach to estimating non-parametric (smoothing splines) structural terms, parametric hedging is not applied immediately. We present a non-parametric approach to hedging a bond-like obligation, allowing for a common form of assessment of the timing structure with possible smoothing. We show that our approach gives standard immunization on the basis of the maximum duration, when the degree of smoothing goes to infinity. We also reinstating the industry's best hedging approach, based on the length of the key rate, as another specific case. The hedging portfolio is easy to calculate using only the basic operations of linear algebra.
The article shows how the Bayesian approach to income adjustment can be implemented in a non-parametric structure with automatic smoothing obtained from data. It also briefly illustrates the benefits of this approach using real data.
The article uses an infinite-dimensional (functional space) approach to reverse problems. Numerical calculations are performed using the Markov-Monte Carlo chain algorithm with several settings to ensure good performance. The model clearly uses spreads between queries and sentences to account for observation errors and provides automatic smoothing based on them.
The non-parametric structure captures the complex forms of the zero-coupon curves of emerging markets. The Bayesian approach assesses the accuracy of estimates, which is crucial for some applications. Examples of valuation results are given for three different bond markets: liquid (German), medium liquid (Chinese) and illiquid (Russian).
The result shows that an infinite-dimensional Bayesian approach to evaluating the structure of the term is possible. Market practices can use this approach to better understand the timing of interest rates. For example, they could now supplement their non-parametric estimates of the timing structure with Bayesian confidence intervals to enable them to assess the statistical significance of their results.
The model does not require parameters to be set during the evaluation. It has its own parameters, but they must be selected during the model configuration.
This article is devoted to the creation of intelligent modelling tools for decision support in the evaluation of intellectual projects submitted for financing, as based on qualitatively defined characteristics. The economic and mathematical models that form the basis of the toolkit are constructed using the mathematical apparatus of fuzzy logic, which allows for the description of poorly structured knowledge of specialists, as well as their application in solving questions about the extent of the impact of the proposed projects on the environment. The authors classify investment projects according to the degree of impact on the environment, the environmental criteria required by the investor for the evaluation of investment projects, and the formal formulation of the problem of evaluation of investment projects when taking into account the environmental factor. The toolkit was created based on the concept of intellectualization, where economic and mathematical models for the evaluation of investment projects are programmatically implemented via the tools and functions available in the MATLAB package.
We study alternative arbitrage strategies for stocks of Russian companies and the corresponding depositary receipts issued in European exchanges (‘mirror trades’). We provide evidence for significant arbitrage opportunities in Russia, and the potential returns are higher when the depository receipts are underpriced relative to stocks on the domestic market. Such asymmetry in arbitrage returns may be a consequence of money expatriation from Russia using these ‘mirror trades’ even when they are unprofitable, creating further mispricing. We also show that the long-short ‘buy-and-hold’ strategies, although being risky, generate returns which are about twice as high as the returns to the conversion strategies. Although the arbitrage returns have declined over time, they are still positive and generally higher than the market returns. Low liquidity of Russian depositary receipts on European exchanges is a significant barrier to arbitrage.
The paper examines how the type of ownership affects the efficiency of Russian banks. Using bank-quarter data for selected banks in the period 2004–2015, we combine stochastic frontier analysis (SFA) methodology with an intermediary approach to assess both profit and cost efficiency scores. Our key findings show that foreign-owned banks are the most profit efficient, and state-owned banks efficiently manage costs compared to other banks. These results are robust when we consider these banks in terms of risk preferences and specialization.
The article examines the problem of the ICO (Initial Coin Offering, from English — “initial offer of coins, initial placement of coins”). The information source is the ICO rating data of the return on investment in blockchain startups. The methodological base of the research is a situational comparative analysis of the ICO, DAOICO, IEO and STO and systematization of information. The author analyzes three new ICO models. The first one includes elements of Decentralized Autonomous Organizations (DAO). Its aim is to minimize the difficulties and risks associated with the ICO. The second model (Initial Exchange Offering (IEO), from English — “primary exchange offer”) is designed to minimize risks, liquidity problems and a delay in listing tokens at the end of the token sale. The third model — the Security Token Offering (STO, from English — “offer of security token”) — was designed to support real assets and comply with the SEC requirements. These models are a new direction for small and medium enterprises and investors. The absence of any scientific work emphasizes the relevance and scientific novelty of the study. The article is a follow-up of the empirical work related to the success of the ICO, as well as the basis for its revision using the case study results.
In developing economies, which rely considerably on the dollar and euro, changes in the currency structure of bank deposits may be strategic and may work as an additional market discipline mechanism. This study sheds light on this currency shifts mechanism in the Russian market for personal deposits. Using data on 900 banks for 2005–2015, we show that less risky banks demonstrate higher growth in the share of deposits denominated in foreign currency (FX), even when the exchange rate volatility component is extracted. The shifts are supported by the quantity-based mechanism as more reliable banks enjoy higher FX deposit growth.
We analyze whether bank familiarity affects depositor behavior during financial crisis. Familiarity is measured by regional or local cues in the bank's name. Depositor behavior is measured by the depositor's sensitivity to observable bank risk (depositor discipline). Using 2001-2010 bank-level and region-level data for Russia, we find that depositors of familiar banks become less sensitive to bank risk during a financial crisis relative to depositors of unfamiliar banks. To validate that our results stem from a flight to familiarity during crisis and not from implicit guarantees from regional governments, we split our sample along the lines of regional affinity and trust in local governments. The flight to familiarity effect is strongly confirmed in the subsample of regions with strong regional affinity, while the effect is absent in the subsample of regions with more trust in regional and local governments, lending support to the thesis that our results are driven by a flight to familiarity rather than by implicit guarantees.
The knowledge economy has come a long way before becoming one of the fundamental concepts in scientific and political discourse. The World Bank and the OECD analyze the level of development of the knowledge economy at the global level. However, the transformation of the economy at the regional level is also very important, largely because of the general tendency towards regionalization. This issue is particularly acute for emerging and post-communist countries (including Russia), which are in the process of transition to a market economy. Grounding on the World Bank’s Knowledge Economy Index indicators, the authors developed the Russian Regional Knowledge Economy Index (Russian RKEI). The authors allocated the leading and lagging groups of regions regarding the knowledge economy development as well as the fastest-growing regions. The authors identified critical success factors in the modernization of regional economic systems. Besides, the authors marked the negative trend in the development of the knowledge economy in more than half of Russian regions. On the one hand, this is due to the economic crisis and a reduction in investment; on the other hand, institutional problems continue to restrain economic development. The results can be used in further theoretical and applied studies for both Russia and other transition economies.
In this article, we evaluate CEO behavior in terms of his or her preferences to risk, and how the actions of boards of directors interplay with these behaviors. Specifically, we set out to test whether the actions of boards of directors can overcome the negative impacts of CEO behavior on various aspects of payout policy. We set out to examine these tendencies in terms of the levels of payout, the propensity to pay, and the choice of payout channel utilized. We use several compensation-based proxies to measure CEO risk preferences on a sample of non-financial and non-utility companies from the US for 2007 to 2016 from the S&P 1500 Index. Our contribution is threefold. First, the findings fill the gaps in the research on the impact of CEO risk preferences on the decision to start paying dividends and on the decisions to switch between cash dividend and share repurchase. The results indicate that CEOs who are encouraged by the boards to take more risks paid out more through repurchases, while less risky CEOs are more likely to initiate paying dividends. Second, by means of quantile regression we demonstrate that the level of repurchases is more sensitive to the CEO’s risk preferences in the companies from top quartiles. Third, by introducing our index of corporate governance quality, we may document that corporate governance tools reduce or even eliminate the negative effects of CEO risk preferences. In companies with high corporate governance index, the risk preferences of the CEO do not affect payout decisions.
This paper examines the nature of the relationship between corporate R&D investment and the probability of default. Existing evidence on the topic is varied and often conflicting due to its complexity. In this paper, we investigated the non-linear relationship between R&D investment and the probability of default, and also detected several factors influencing the nature of the relationship. The research relies on the sample of Asian Tiger's countries (Hong Kong, Singapore, South Korea and Taiwan) for the period from 2012 to 2017. Results of the research reveal a Ushaped relationship between corporate R&D investment and default probability. Considering the relationship more precisely, we divide the sample into two parts based on the availability of financial resources, and test the significance of this factor. R&D investment is found to significantly decrease default probability for financially constrained firms. We also examine the investment efficiency factor by comparing R&D investment and default probability between underinvesting and overinvesting firms. The rise of R&D investment decreases default probability for
underinvesting firms, and increases e for overinvesting ones. Studying separately high-tech firms, we reveal that R&D investment leads to decrease of default probability.
Innovative companies have become one of the major drivers of the economy worldwide. According to various surveys, nearly 70% of the world's most innovative companies in 2019 are US firms. However, academic studies have tended to focus on the influence of the top management team and the board of director’s on the firm performance or the relationship between innovative activity and the CEO`s preferences. However, this overlooks the idea that the CEOs themselves can exert a significant influence on the performance of innovative companies. As such, we aim in this research paper to show which CEO characteristics could lead to higher firm value.
This research uses the generalized least squares model on a sample of 12,565 firm-year observations during the period 2004-2015. We used data for three innovative industries: (i) pharmaceuticals, biotechnology & life sciences, (ii) software and services, and (iii) technology hardware and equipment industries. Additionally, we hand-collected data from the CVs stored in the CIQ database. Finally, we provide examples to prove the validity of our tests.
Our results indicate that educational background, tenure, and duality play crucial roles in explaining firm value. Our findings indicate that CEO characteristics play crucial roles in explaining technology firm value and performance. We demonstrated that the founding CEO, as well as a CEO with better education, contributes more to firm performance. We found that the characteristics of a CEO can mitigate conflicts between different types of investors and their influence on firm performance. More specifically, the CEO-founder was found to add greatly to the performance of Software and Pharmaceutical companies. Furthermore, CEO influence seems to mitigate the conflict of interest with independent active institutional investors in the Hardware industry.
The novelty of this paper resides in its specific answers to questions that are overlooked or taken for granted in broader studies on the same subject area. We emphasize the differences in ownership structure in high-tech and non-tech industries, and not only provide answers as to whether the vaunted ‘power’ of a chief executive is significant in increasing company value, but whether a highly educated CEO contributes more to innovations in the hi-tech sphere. The specificity of the empirical investigations concluded herein lends itself well to reference, and as such, this paper provides opportunities for academics, students, professionals, and journalists in the business field to cite its conclusions in any number of media.
This paper aims to discover evidence on the possible impact of CEO overconfidence on payout policy, and the role of corporate boards in offsetting the possible negative effects of this overconfidence. Our investigation demonstrates the effect of overconfidence on the choice of payout method, specifically regarding the repurchases-dividends mix. We also evaluate the ability of corporate governance mechanisms to reduce or even eliminate the negative effects of CEO behavior on payout decisions.
This study is conducted using a sample of 671 non-financial companies from the US for the period of 2007–2016. We apply probit regressions to study different aspects of payout decisions, and use a panel GMM estimator to check for possible endogenous effects. Using a corporate governance quality index, we test the ability of boards of directors to reduce negative effects of CEO’s overconfidence on the payout decisions.
Our findings confirm the hypothesis that overconfident CEOs tend to increase the levels of payout in the form of repurchases, while the levels of cash dividends are unaffected by this type of CEO behavior. Moreover, an overconfident CEO is more likely to initiate repurchases if this has not been done already. The results further illustrate that overconfident CEOs not only pursue higher levels of repurchases, but also switch more often from cash dividends to repurchases. However, it is also shown, in contract to previous research in the field, that efficient boards of directors have very limited power in eliminating the negative effects of CEO overconfidence.
This paper contributes to the existing literature by analyzing the specific area of CEO overconfidence using data from
the United States, and follows specific lines of inquiry which have not been deeply studied. Further possibilities to explore the implications of this research exists particularly in the consideration of its apparent contradiction of previous research. There is yet scope to determine applicable tools of reducing the negative effects of specific CEO behaviors. It is possible to identify and investigate other relevant behavioral characteristics that may influence payout decisions. Further, these characteristics may be evaluated to see if the operation of these interrelations reproduce alternative results in terms of the effect of corporate governance, both in the US and in other markets.
The question as to whether political influence can benefit the commercial activity of companies, and the related
questions surrounding political corruption that arise, are of perennial fascination for persons at every level of society
and in every country. With this in mind, this article seeks to explore the relationship between political connections in
commercial firms and investment efficiency. This relationship will be studied on an empirical basis, and will shed some light on the actual parameters, mechanisms, and effects of political influence in the business sphere in the Russian Federation.
In this research, we consider only direct relations between business operators and the members of Russian ministries, councils, political parties, heads of the regions and cities. These relationships are categorised as being politically influential depending on the status of the politician, and whether they are active at a federal, regional or municipal level. Connections with such politicians are examined where there is evidence of direct links with company CEOs and chairmen of the boards of directors of companies.
This research is carried out on the sample of 106 Russian non-financial companies for the period 2010–2015. 44
companies from the final sample were considered as politically connected on at least one level. Some firms have connections more than at one level (11 companies). Companies have politically connected chairman of the board (36
companies) more often than connected CEO (26 companies). Using regression analysis, we determined whether the
political ties in Russia have a positive or a negative impact on the investment expenditures of companies.
Interestingly, and perhaps contrary to popular belief, we identified a negative relationship between political ties and the efficiency of investment decisions for individual companies. The presence of politically-connected CEOs at federal and regional levels is seen to have a significant negative impact on investment efficiency. However, our results also indicate that the presence of politically-connected chairmen of the board which are active at the municipal level is correlated with efficient investment activity. This indicates that political influence at this level may be responsible for more prudent recommendations regarding commercial and investment decisions. Overall, it can be seen that in this sample of companies from the Russian Federation, the presence of state-tied representatives may be aligned with a tendency for companies to follow targets that are favourable for its government connections and not for the firm itself.
Although political connections have a mixed impact on the company’s value, the relation with investment efficiency is
primarily negative. Thus, we may reason that the government has a strong power over politically-related companies.
Such influences are linked with a tendency for companies to deviate from their primary goal of value maximisation.
These results may indicate the influence of undue pressure from a government which strives to reach its own goals
through the mechanism of commercial activity, or perhaps the opportunistic behaviour of individuals in management
positions who are motivated towards personal political gain at the expense of the company. Political connections have a mixed effect on the company’s performance and investment efficiency, and we postulate that firms establish relationships with government officials pursuing the goal to obtain more advantageous position. The links between political operators and business activity demonstrated in this research undoubtedly highlight some uncomfortable areas of discourse in the commercial sphere. On a granular level, further research into specific transactions and motivations may seem more a research area for journalists or law enforcement investigators, but this may be simply a popular prejudice. There is certainly ample opportunity for expanding the scope of this study’s results. Beyond the interests of political, sociological and legal researchers, the data presented herein will be of immediate interest to persons operating in the commercial, business, and economic spheres of the Russian Federation and internationally.
Sustainable development is a worldwide recognized social and political goal, discussed in both academic and political discourse and with much research on the topic related to sustainable development in higher education. Since mental models are formed more effectively at school age, we propose a new way of thinking that will help achieve this goal. The authors undertook this study in the context of Russia, where the topic of sustainable development in education has been yet poorly developed. The authors used the classical methodology of the case analysis. The analysis and interpretation of the results employed the framework of the institutional theory. Presented is the case of Ural Federal University, which has been working for several years on the creation of a device for the purification of industrial sewer water in the framework of an initiative student group. Schoolchildren recently joined the program, and such projects have been called university-to-school projects. Successful solutions for inventive tasks contribute to the formation of mental models. This case has been analyzed in terms of institutionalism, and the authors argue for the primacy of mental institutions over normative ones during sustainable society construction. This case study is the first to analyze a partnership between a Federal University and local schools regarding sustainable education and proposes a new way of thinking.
Since 2013, Initial Coin Offerings (ICO) have allowed companies to attract financing with the help of cryptocurrencies. Statistics of ICO shows that the ICO market is increasing and demand for funds continues to grow with claims of over $ 15 billion raised in the first half of 2018. The increasing volumes of investment in ICO projects as an alternative method to venture capital or IPO are caused by, for example, the possibility of reselling the received tokens at a higher price after the launch of the project or obtaining the company’s services at lower prices. While the importance of the topic is growing, there is the absence of fundamental works emphasizing the determinants of an ICO’s success. The scientific novelty of the forthcoming research consists in the formation of the model evaluation of ICO success. Using econometric analysis based on data for 1392 projects, we show that the volatility of the main cryptocurrencies has a significant impact on the success of ICO. The constraints of the platform for Smart Contacts (ERC‑20) and dependence on the Ethereum volatility overcome all other factors. Our data contributes to existing literature and shows the insignificance of the sector of the project, almost all location region and fluctuation of influence of quality of the team. This result may be explained by the uncertainty of the investor about the project (weak signals), absence of the regulation and legal framework. This result is beneficial for owners of companies since it is an argument for decreasing costs for marketing.
The paper proposes an economic and mathematics models of sustainable tourism development strategic management based on application of fuzzy algebra mathematical apparatus. The conducted research is built, starting from the formulation of strategic management of sustainable tourism development concept and ending with the creation of economic and mathematics models of decision support. A mathematical model that supports decision making in the evaluation of sustainable development of tourist and recreational areas was developed based on the use of mathematical apparatus of fuzzy inference. The model is built in Fuzzy Logic Toolbox environment of MATLAB and allows selecting strategic reference points for sustainable tourism development with the combination of the results of economic benefits with environmental and social indicators.
The paper contributes to the literature on the management and corporate governance in microfinance institutions. Microfinance market is one of the rare markets with the great representation of women in management and governance. The objective of our paper is to reveal the effects of women’s presence on financial and social performance of microfinance institutions controlling for risks. We develop a model that allows for capturing the gender diversity influence on financial and social performance controlling for risks in Eastern Europe and Central Asia. We focus on the role of women among loan officers, in the boards of directors or the management in the creation of microfinance institutions social or financial performance. The model of two sets of panel data regressions for social and financial performance is tested on the data of 193 microfinance institutions of Eastern Europe and Central Asia for 2010 to 2014 financial years. We find out that female management, CEO and members of boards of directors could increase performance for riskier microfinance institutions with greater stake of portfolio with more than 90 days in arrears. We also state that women on boards try to promote the strategy of large quantity of small loans with greater interest. The social performance of microfinance institutions is crucially determined by the microfinance institutions’ size. For largest microfinance institutions the questions of social performance lie in the field of boards of directors while for smaller microfinance institutions’ social performance is mostly driven by CEO and staff with the evident positive female role.
Consideration of investment activity of companies in relation to macroeconomic factors suggests that they have an optimal investment policy. In the majority of works devoted to the analysis of investment activity of companies, attention has been mainly focused on the influence of internal factors as they are manageable, and less has been paid to external factors. In the Russian reality, since it may result in a companies’ bankruptcy, over-investment occurs less frequently than under-investment. Therefore, the priority question is — what has a bigger impact on over-investment, is it macroeconomic factors, or internal factors? The goal of our study is to establish the macro-drivers having the strongest impact on the likelihood of over-investment in Russian companies. For measuring the influence of macro-drivers, a binary choice regression model is estimated on the basis of panel data. The results reveal that the biggest impact on the probability of over-investment, has the oil price volatility decreasing it by 38%, the volatility of the exchange rate takes second place (–29%) and the growth rate of the Gross Domestic Product and the inflation rate have an inconsequential influence (7% and less than –1% respectively). At the end of the paper, the analysis of the speed of adjustment to target levels of investment, shows that in the macroeconomic environment Russia experienced in 2012–2017, companies would have target levels of investment, adjustment to which would occur gradually, over a period of around 2 to 5 years depending on the industry.
In recent years there has been a rapid increase in the use of digital technologies, the role of which is steadily increasing compared to other types of technologies. The growing role of information is changing economic structures in such a way that we can talk about the formation of a new economy – the digital economy. The digital economy, according to the policy documents of the European Union "is the result of the widespread use of new information technologies, which affected all sectors of the economy." However, if we apply the methodology of economic theory, the digital economy can be understood as a set of social relations arising from the use of electronic technologies, electronic infrastructure and services, technologies for analyzing large amounts of data and forecasting in order to optimize production, distribution, exchange, consumption and increase the level of socio-economic development of states.
Most of the papers on the sixth technological order formation and the development of Industry 4.0 focus on the study of the impact of the digital economy on the business transformation. The article shows that each technological structure of the economy corresponds to its own management conceptual model of the production and economic system. And, consequently, the formation of the digital economy foundations immanently leads to the evolutionary development of management models in socio-economic systems, which are insufficiently studied in the available works.
The article substantiates the conclusion that in the conditions of the digital economy there will be a transformation of the cost management model to the technology efficiency management model. This means that the main source of economic growth will be not just innovative development, but the search for more effective innovative technologies. In the digital economy, technology will become almost universally available, so the key to success will be new models of digital technology management, allowing for both operational regulation and modeling of future opportunities and threats of the state, business, and every member of society.
The article discusses a model for the evaluation of universities and science in general from the point of view of university engagement in the socio-economic environment. The authors conducted a scientometric analysis of the topical area. The primary goal was the identification of various interrelations between some classical scientometric indicators and alternative ones, most clearly reflecting the interaction of science, society, and industry. Three countries were chosen as the object of the study and the five most appropriate research areas. Based on a comparative analysis, we can conclude that traditional scientometric indicators correlate quite well with indicators of social and commercial relevance of scientific research. However, we did not observe this relationship in the case of Brazil; thus, we can infer the influence of the national and disciplinary context. Quantitative indicators are not enough for the evaluation of university engagement, and we do need peer review here.
Increasing the accuracy of short-term electricity price forecasting allows day-ahead power market participants to obtain a positive economic effect by bidding close to the equilibrium price. However the electricity price time-series is generally infested with extreme values due to high price volatility. This paper discusses the impact of outlier filtering on forecasting accuracy based on a recently introduced seasonal component autoregressive model. We consider such methods of outlier detection (with a priori defined cut-off parameter) as threshold, standard deviation, percentage, recursive, and moving filter on prices. It is shown that such data pre-processing often leads to the forecasting accuracy gain while the error decrease (relative to the approach without filtering) in a number of cases may reach 1.8–1.9% of the average weekly price (in absolute values). For an a priori defined cut-off parameter, the simple threshold and standard deviation filter on prices outperform other considered methods, and yield to the accuracy gain in 63% and 67% of cases, correspondingly. At the same time, in case of the out-of-sample filter parameter grid-optimization all of the methods demonstrate comparable prediction power (equal to the marginal performance). But, practically speaking, such optimization is time-consuming and cannot be carried out on unavailable future data. As an competitive alternative, we propose a combined filter on prices based on a committee machine which uses the results of individual non-optimized algorithms and is not time-consuming, but gives accuracy comparable to the best one obtained for each of the studied electricity markets and leads to forecast gain in 63% of the considered cases.
Three approaches are developed for assessment of different types of organizational ambidexterity proposed in the relevant literature. The new model for measurement of organizational ambidexterity using data envelopment analysis (DEA) is introduced. The DEA score based on innovation activity inputs and two different performance outputs acts as a proxy for organizational ambidexterity. Sustainability goals and product ambidexterity are also analyzed as the key characteristics of ambidextrous behavior. The introduced three approaches are tested for their aptness to complement
each other as well as to support a strategic decision-making. Empirical examples from energy and pharma sectors associate organizational ambidexterity with firms’ performance. We measured the organizational ambidexterity of energy and pharma companies by (1) pursuing long-term versus short-term organizational performance measured
as a DEA two-output efficiency score; (2) the share of disruptive products in a company’s activities assessed through the proportion of R&D expenditure or sales; and (3) sustainability versus financial performance of the company, where the Green ranking and participation in innovative financing programs were used as proxies for sustainable development. Positive relation between performance and organizational ambidexterity for energy sector are discovered. At the same time, orientation towards sustainability disrupts performance of pharmaceutical companies. Results of the OA impact on performance are highly industry-sensitive and depend on the methods used in empirical assessment. Our findings suggest that the scarcity of data sources make all three approaches complementary and mainly functional for strategic decision-making.
In this paper, the authors focus on two primary governance mechanisms which can be considered as sources of support for startup companies: the company’s ownership contingent and the company’s management personnel. Based on descriptive statistics from a sample of 416 Skolkovo start-ups from the ‘Nuclear’ and ‘Space’ clusters, and a Start-up-Barometer survey of 300 IT-entrepreneurs, this work provides new insights into ownership and management characteristics of Russian startups and the interplay between these dynamics.
The Russian venture market presents an interesting case of an emerging market with a number of successful startups in a challenging economic environment. The supply of venture capital for Russian startups is restricted by the presence of sanctions and legal restrictions on the investments of financial institutions such as pension funds and banks. Therefore, similar to other developed and developing markets, the most significant source of investments for Russian startups is bootstrapping.
In this paper we show that startups with different characteristics attract different kinds of investors, which is reflected in the companies ownership structures. In particular, government development institutes are more interested in investing in nuclear-focused startups, while corporate investors tend to keep a higher level of control over startups compared to other investors. We also confirmed the presence of correlations between different types of owners: government development institutions, corporate investors, venture funds, and family members. Additionally, the size of equity share for all types of owners (except family members) was found to be negatively correlated with the CEO’s share in the ownership structure.
Although the purpose of the article is descriptive, it motivates further research on the sources of support of startup growth, including relative importance of such sources and their effects on startup performance.
The term “smart city” has recently become greatly widespread in academic and political discourse. Nevertheless, this is rather a marketing term that unites a number of technological (and other) areas: Internet of Things (IoT), augmented and virtual reality (AR/VR), communication networks. The latest generation of networks is essential for the development of digital ecosystems of smart cities. It has been assumed that the smart city and 5G networks form an emerging technological area. The goal of the work is to study the structure of the development and implementation of new technologies for the urban environment on the sample of 5G-based technologies. For the analysis of new technologies in the selected subject area, a study of patent landscapes and scientometric analysis of the topic field has been conducted. The object of the scientometric analysis is the study of citation patterns. The use of the patent landscape is based on the information systems and databases of patent information developed by patent offices and commercial companies and consists of visualizing the logical connections between various indicators of patent activity, on the one hand, and technological and market trends, on the other. Together, the scientometric and patent landscape show the most promising areas of technological research. The results of the study can be used in further theoretical and applied research, in the formation of government policy in research and development, as well as in decision-making in the field of urban management.
The question as to whether tax rate influences capital structure remains unresolved,
though the amount of research conducted on the issue grows every year. This question
is particularly important for innovative companies for two reasons. First, R&D spending
and the level of innovativeness among firms are crucial indicators of a country’s overall
economic performance. The second reason is that tax incentive programs today are applied
by governments with increasing frequency. There is a strong lack of tax rate influence on the
capital structure of innovative companies and tax incentive programs impact on the debtto-
equity ratio particularly. This research is intended to help fill this gap. The question as to
the influence of tax rate as well as influence of R&D taxation programs on capital structure
will be studied via the econometrics approach – that is, through panel regressions. The time
frame to be considered is from 2012 until 2015. Four hypotheses connected with taxation
influence on capital structure in BRIC countries were investigated. These hypotheses differ
according to which indicator of the structure of capital is taken as the basis of the analysis.
This investigation may be useful for governments or other analysts to estimate ETR influence
on capital structure choice and assist in making a decision between increasing the tax rate
(and thereby collect more taxes) versus stimulating companies to take on less debt and less
risks. The results highlighted in this paper show an absence of significant impact vis-à-vis
the tax rate on the capital structure and also indicate an absence of a significant impact
of tax incentive programs on capital structure.
We compared the ability of various empirical methods to reproduce public credit ratings (PCRs) of industrial companies (ICs) from BRICS countries using publicly available information. This task is of primary importance for researchers and practitioners as a lot of BRICS’ ICs lack public credit ratings (CRs) from reputable rating agencies such as Moody’s, Standard and Poor’s or Fitch. The paper is aimed at filling the gap in the existing research as only very few efforts were focused on prediction of PCRs of ICs from entire BRICS IC community. The modelled variables are CRs of 208 BRICS’ industrial companies assigned by Moody’s at the year-end from 2006 till 2016. The sample included 1217 observations. Financial dependent variables included companies’ revenue, operating profitability, interest coverage ratio, debt/book capitalization and cash flow debt coverage. Non-financial dependent variables included dummies for home region, industry, affiliation with the state and a set of macroeconomic data of IC’s home countries. The set of statistical methods included linear discriminant analysis (LDA), ordered logit regression (OLR), support vector machine (SVM), artificial neural network (ANN) and random forest (RF). The resulting models were checked for in-sample and out-of-sample predictive fit. Our findings revealed that among considered methods artificial intelligence models (AI) – SVM, ANN and RF outperformed LDA and OLR by predictive power. On testing sample, AI gave on average 55% of precise results and up to 99% with an error within one rating grade; RF demonstrated the best outcome (58% and 100%). Conversely, LDA and OLR on average gave only 37% of precise results and up to 70% with an error within one grade. LDA and OLR also gave higher share of Type I errors (overestimation of ratings) than that of AI. Therefore, AI should have higher practical application than DA and OLR for predicting the ratings of BRICS ICs.
We compared the ability of various empirical methods to reproduce public credit ratings (PCRs) of industrial companies (ICs) from BRICS countries using publicly available information. This task is important for researchers and practitioners because many of BRICS’ ICs lack PCRs from reputable rating agencies such as Moody’s, Standard and Poor’s, and Fitch. This paper aimed at filling the gap in the existing research as insufficient efforts were focused on prediction of PCRs of ICs from the entire BRICS IC community. The modeled variables are credit ratings (CRs) of 208 BRICS’ ICs assigned by Moody’s at the year-end from 2006 to 2016. The sample included 1217 observations. Financial explanatory variables included companies’ revenue, operating profitability, interest coverage ratio, debt/book capitalization, and cash flow debt coverage. Non-financial explanatory variables included dummies for home region, industry, affiliation with the state, and a set of macroeconomic data of IC’s home countries. The set of statistical methods included linear discriminant analysis (LDA), ordered logit regression (OLR), support vector machine (SVM), artificial neural network (ANN), and random forest (RF). The resulting models were checked for in-sample and out-of-sample predictive fit. Our findings revealed that among considered methods of artificial intelligence models (AI), SVM, ANN, and RF outperformed LDA and OLR by predictive power. On testing sample, AI gave on average 55% of precise results and up to 99% with an error within one rating grade; RF demonstrated the best outcome (58% and 100%). Conversely, LDA and OLR on average gave only 37% of precise results and up to 70% with an error within one grade. LDA and OLR also gave higher share of Type I errors (overestimation of ratings) than that of AI. Therefore, AI should have higher practical application than DA and OLR for predicting the ratings of BRICS ICs
A substantial body of academic literature continues to investigate whether M&A deals create or destroy shareholder
value and what are the main determinants of M&A performance, but the results are still inconclusive. In this paper, we
investigate the impact of corporate life cycle on M&A performance from the perspective of acquiring firms.
We shed additional light on the performance of M&A deals from the perspective of bidders’ life cycle stages and the
deal size . We single out mega deals, where activity remains upbeat, and compare their effects on M&A performance
with the effect of non-mega transactions. In contrast to previous studies in the area, we identify four life cycle stages
(introduction, growth, maturity and decline), whereas the existing literature mostly focuses on three life cycle stages.
Our sample includes 2413 US domestic M&A deals from 2003 to 2017, and consists of 386 mega deals and 2027 non-mega transactions. The data for analysis were obtained from Capital IQ, Bloomberg and Thomson Reuters Eikon databases.
Based on the event study method and regression analysis, we find that stock market reaction is positive for M&A deals in the US and this reaction is more favourable for non-mega acquisitions than for mega M&A deals. We show that non-mega deals outperform mega transactions for acquirers at the introduction and growth stages of the business life cycle.
Our results also indicate that benefits for shareholders from acquiring firms decrease on average with the lifecycle of an organisation, but the returns for shareholders are positive in both cases. By contrast, in mega deals, shareholders receive negative returns when the acquiring firm is at introductory life cycle stage.
The scientific novelty of this paper is reflected in our contribution and expansion of the scope of research in this field.
There is a relative scarcity of analysis examining M&A deals from the perspective of life cycle stage, and our addition of a fourth category of analysis in this area, along with a focus on the value of the deal, expands the range of methodology for future research. This research is open to further expansion in different markets and our methodology is readily adaptable for the addition of further analytical variables. Importantly, with the validation of our research hypotheses and the confirmation of significant results, we provide a useful new tool for managers and professionals engaged in M&A deals to actively gauge and forecast practical implications of their deals.
This study is dedicated to estimating the impact of currency risk on the cost of equity in Brazil, Russia, India and South Africa. Our contribution to the literature is that we have obtained evidence on the pricing of exchange rate risk in developing countries, which at the time of writing is quite scarce. This scarcity is one motivation for our research, which is dedicated to BRICS capital markets, though with the Chinese stock market excluded since it is heavily regulated. The aim of this research is to determine whether in emerging countries stock markets currency risk is a significant factor that influences the cost of equity capital in a company. Changes in the value of exchange rates can impact the cash flows of a firm and its exposure to risk, and hence, the value of the company. In our research we will discuss the influence of exchange rate movements on the value of firms through their impact on the cost of equity. Specifically, we investigate whether companies that report substantial currency gains or losses have to pay a higher required rate of return on equity. Furthermore, in this study we make an attempt to estimate currency risk premia for exposure to appreciation and depreciation of currency separately, and try to identify possible differences. For each country, three analytical models that extend the Fama-French Three Factor Model (by incorporating currency risk) are estimated. We use an equal-weighted portfolio approach to identify currency risk factors. These factors are estimated either by using information about the ratio of currency gains to sales, or the magnitude of covariation between equity returns and exchange rate changes. In the second case appreciation and depreciation of domestic currency against the US dollar is considered separately. The results indicate that in Russia, firms which report substantial currency losses pay a positive risk premium, while in Brazil, India and South Africa companies with significantly positive or negative currency gains pay a lower required return on equity than firms with almost zero currency gains. Finally, we attempt to explain the estimation results using a sectoral breakdown of product exports for each country of the data sample.
Technological development and digitalization plays a crucial role in financial sector by allowing firms to create value in a rapidly changing environment. The acquisitions of firms related to financial technologies are one of the ways to obtain vital knowledge. In order to identify the fintech companies we are looking at firms that are involved in business activities in both the IT and financial sectors. By examining the growing role of fintech firms in the recent mergers and acquisitions from an investor point of view, this paper contributes to the existing literature by investigating the post-acquisition performance of the acquirer firms measured by abnormal returns. We discovered significant positive average abnormal return after acquisition of fintech companies in the short-term and negative average abnormal return in the long-term using event studymethodology. The specifics of cross-border acquisitions, the level of the domestic market development of the acquirer, and other characteristics of M&A deals are considered in order to explain the reaction of investors to announcements of fintech firms’ acquisitions. The determinants of corresponding M&A deals in emerging and developed markets were revealed.
This study aims to explore the influence of corporate taxation on the performance of innovative companies under various research and development (R&D) tax incentive programs.
The empirical model is based on the data of 520 companies for period 2007-2016. This model includes return on assets as the main proxy for performance and effective tax rate as a main explanatory variable. Controlling for other known determinants, the authors divide the sample into the subsamples to control for the various R&D tax incentive programs. The fact that the model includes the lagged explanatory variable of performance the Blundell –Bond model was applied.
The authors found evidence that corporate taxation has a significant impact on performance, but the direction could be ambiguous. Impact of the corporate tax rate on performance in general sample is significantly negative, which is consistent with results obtained by authors for the non-innovative companies. However, for further examination, the authors use subsamples of companies with different R&D tax incentive programs. The effect of corporate tax becomes positive under the patent box program only. Moreover, under various R&D tax incentive program, the impact of main control variables has changed. Therefore, the authors conclude that not only corporate taxation but also R&D tax incentive programs significantly influence the performance of innovative companies.
The data are limited due to fragmented information disclosure about the R&D tax incentive program used. Thus, a different data set might reveal new information and correlation between variable on the same topic. Moreover, the authors do not cover all R&D tax incentive programs, which are specified for companies and countries. However, the study fills the gap between corporate taxation, performance and innovative companies. As the significant result was found the further research is important. The study contributes not only in the field of research but also a practical one. The choice of R&D tax incentive program influences main indicators of companies’ performance so it may change the behavior of the investors and decision-making managers of the companies.
Given the increasing interest in the topic of innovative companies, this study fills the gap between corporate taxation in innovative companies and performance. In addition, the importance of R&D tax incentive programs as a feature of innovative companies was found.
I model the choice between a negotiated block trade and a public tender offer as means of acquiring control in a firm with a large minority blockholder. Potential acquirers differ in their (privately known) value‐creation ability. In equilibrium, block trades are made by lower ability acquirers compared to tender offers. The equal opportunity rule (EOR) and the “freezeout” rule are complements in promoting efficiency of control transfers. Stronger investor protection may hamper value‐increasing takeovers when the EOR is present. The model also delivers predictions about announcement returns and the incidence of block trades and tender offers under different legal regimes.
This article is devoted to a comprehensive study of toxic assets, which are on the balance sheets of professional securities market participants, in order to calculate the real value of capital. The authors have developed a method similar to a formalized algorithm for identifying toxic assets of liquidating or liquidated companies and assets in credit institutions with a revoked license, for subsequently adjusting the value of equity (net assets), and analyzing for compliance with the Bank of Russia supervisory requirements. The method is described by the authors in accordance with BPMN notation. The authors determined the information base of the method, which includes only mandatory reporting and open information resources, which makes it simple and transparent for users. Prospective users of the method may be the Bank of Russia, current and future counterparties of professional participants in the securities market, DBMS developers and scientific employees of economic specialties. The method was tested by the authors on the basis of a real-life brokerage company.
In this paper we are going to review both theoretical studies in the field of intellectual capital measurement and empirical research, devoted to analyses of intellectual capital influence on companies’ value and financial performance. As a result, potential areas for further investigations in this field were revealed.
Considering groups of intellectual capital measurement methods, we identified that direct intellectual capital methods and scorecard methods are the most appropriate for the purpose of IC components measurement. To obtain objective results of measurement it seems reasonable to develop system of proxy indicators for all intellectual capital components (human, structural and relational capitals) and subcomponents (process and innovation, client and network capitals). Basing on existing literature, we make an attempt to identify and systemize indicators, associated with intellectual capital and reveal that network capital metrics remain under-researched and deserve closer examination. It was also found that investigators should develop the system of intellectual capital indicators, taking into account industry specificity.
As for empirical studies, in order to investigate the influence of intellectual capital on corporate value and financial performance, it seems reasonable to elaborate models, which include factors, associated with all intellectual capital components and subcomponents and, what is just as important, their interrelations. Furthermore, it is vital to investigate the relationships between the values of IC components for companies. The models should be adopted for both developed and developing countries. It is also important to analyze the influence of intellectual capital in various industries separately, taking into consideration phase of economic cycle.
This article evaluates the benefits to merchants resulting from participation in the retail payments market. Using surveys to obtain a representative sample of 800 traditional (offline) Russian merchants, the article finds significant, robust evidence in favor of positive merchant's benefits. This study further separates the benefits into direct and opportunity: finding that the non-welfare improving regulatory initiatives might result from the failure to account for the opportunity benefits to merchants. This article also examines the factors affecting the level of merchants' benefits. Results show that factors affecting the value of benefits and the probability of accepting payment cards differ. Findings imply that unbalanced intervention may be detrimental to the agents' welfare, leading to a suggested mechanism for ex-ante evaluation of the effect of shocks and interventions.
The use of Big Data technology has been a modern trend in the travel industry over the last 10 years. At present, almost all travel companies that desire to stay profitable and be customeroriented use the Big Data technology. Therefore, we have several questions to answer: should we use Big Data in tourism or should we not? How to use it? What kind of risks we should consider in order to achieve effective results? These research problems were examined through a thorough analysis of Russian and world travel markets using statistical data on several sites, programs, and organizations that are associated with the tourism industry (e.g., Booking.com, Trivago). The main result of this study is to substantiate the importance of Big Data technology for the travel industry. Big Data technology helps to personally connect companies and clients of the sector so that their interaction would lead to their mutual benefits. The net result of this interaction is an increase in the economical aspect of the sector and thus the country’s growth.
Technologies may have significant effects on productivity in the agricultural sector as documented in the related literature. However, those impacts vary from country to country. These differences could partially reflect the distinct scientific landscapes, science technology and innovation (STI) policies and approaches to R&D. In order to explain the cross-country volatility of agricultural productivity, we aim to study issues of STI development in the agricultural sector in each country. Among other characteristics of STI in general and the scientific landscape, in particular, we looked at the diversification of research publication between subfields of agricultural science. We estimated the research diversification parameter and studied its relation to economic performance of an agricultural sector. Our main finding shows that R&D funding, if carefully balanced with the diversification of agricultural science, could improve research performance and eventually productivity in an agricultural sector.
Each company operates within the framework of interrelated structures: ownership, corporate governance and capital structure. The particular combination of these dimensions determines the corporate financial architecture of the company. Despite the growing body of literature on the challenges of the knowledge economy to the structural dimensions of companies, still little is known about the financial architecture of innovative firms. At the same time it is widely recognized that such companies substantially differ from traditional types of businesses in their business models and dynamics. Meanwhile, the financial architecture of a company generates the distribution of the incentives to enhance innovations affecting interests and risk-sharing among stakeholders. To address the lack of research into the interaction of corporate structures and their distinct features in innovative companies, this paper aims at identifying the robust financial architecture patterns of innovative companies. Using a sample of more than 1,300 publicly traded US-based manufacturing companies, we use an agglomerative hierarchical clustering method to identify relevant patterns and compare them to the firms which are not considered to be ‘knowledge intensive’. The empirical results allow the identification of seven robust financial architecture patterns within innovative companies. Our findings show that the first major difference between the financial architecture of innovative and non-innovative firms is in the higher role of activist institutional investors in the ownership. The second notable difference is related to CEO-duality, which plays a significant role in corporate governance only in innovative firms. Moreover, innovative companies are less leveraged than non-innovative firms. In addition, mature innovative companies demonstrate better financial performance.
We study the relationship between economic policy uncertainty and systemic risk for nine European countries in January 2010–September 2016 by applying conventional Granger causality tests and advanced techniques (wavelet analysis and Bayesian VARs). The country-level analyses show that the lead-lag patterns vary considerably in the short and longer run as well as at diﬀerent frequencies. Nonetheless, the pivotal role of uncertainty tends to strengthen over longer time horizons (at lower frequencies) and in the BVAR framework. This is true for ﬁnancially fragile economies such as Ireland, Italy, Russia, Spain. A panel BVAR model conﬁrms this ﬁnding for the whole sample.
One of the most important factors determining a firm’s profitable growth is scientific and technological progress. In the age of high technology innovations are vitally necessary for companies to compete with one another. Global statistics show that a huge amount of investments are focused on research and development projects in different sectors of the economy such as software and programming, biotechnological products, capital goods, beverages, accessories, restaurants, retail, hotels and motels, and so on.
However, R&D expenses are characterized by high uncertainty and returns in the long run, so not every company can afford such risky investments, for example, most of small and medium enterprises (SMEs). Besides external uncontrollable factors such as crises, disasters, political instability, and armed conflicts, each firm has its own internal problems. Together this can lead to the financial distress or even failure of a firm, and each additional risky asset can increase the probability of insolvency.
Thus, the relevance of the present paper is that each company has to find the optimal tradeoff between investments in innovations and financial distress. The solution to this problem can improve a company’s efficiency and lead to its growth. And vice versa, an unsuccessful selection can result even in the default of a firm.
The purpose of the present paper is to evaluate financial distress costs at innovative companies. In order to achieve stated this aim, the following tasks will be completed in this paper:
The subject of the investigation is financial distress costs. Our study focuses on companies that spent at least $200 million on research and development in 2015. For the further development of the topic, data was collected from Bloomberg and the financial reports of companies. The novelty of the present paper is that the model for direct and indirect cost evaluation at innovative companies was developed.
For the regular Sturm–Liouville boundary value problem with general nonseparated selfadjoint
boundary conditions, conditions for the existence of zero and negative eigenvalues and expressions
for their number are obtained. The conditions are expresses in a closed form, and the coefficient
functions of the original equation appear in these conditions indirectly through a single numerical
This study is focused on gaps in the theory of capital structure research regarding the
phenomenon of zero-debt behavior. On the sample of firms from 21 countries with emerging
capital markets over the period of 2010–2015, we show that the zero-debt policy choice
is firstly driven by financial flexibility motive, while financial constraints could be regarded
as the second motive. We show that major determinants of the zero-leverage choice are
growth opportunities, profitability, business risk and cash holdings. We find that all these
firms are smaller, less profitable, riskier and possess high cash holdings. Moreover, we find
that macroeconomic conditions have lower influence on the debt policy decision in comparison
with corporate determinants.
This study explores the impact of a company’s financial flexibility on the effectiveness of its investments.The number of companies that have financial flexibility was calculated with the application of thespare debt capacity method. The research identifies the impact of financial flexibility on investment activity and on the level of suboptimal investments. The data from 1,736 companies in theAsian region, during the 2005-2015time period, are presented. The Asian region has unique institutional, economic and commercial environments that present a great basis for this paper. The results of the research reveal that financially flexible companies spend more on their investment expenditure and conduct more effective investment policiesby reducing the level of over- and underinvestment. Financial flexibility helps companies to make effective investments during a crisis period, but the difference in the flexibility between developed and developing countries and between large and small companies was not observed.
This paper is dedicated to the investigation of the strategies related to the high-dividend portfolio investment. The aim of this research is to increase the high-dividend portfolio efficiency by adding some filters and optimization weights of the assets in the portfolio. In order to achieve this goal, the authors complement the classical version of the «Dogs of the Dow» strategy with financial indicators ROA and P/E with equal and optimized weights of the assets in each portfolio. Two additional parameters are also used in the process of testing: the number of stocks and the month of the annual portfolio rebalancing. Thus, the obtained models have high-quality advantages in comparison with the traditional concept of high-dividend investing, eliminating its inherent disadvantages and providing higher rates of return.
We use the linear programming approach to quantify quote inconsistencies in risk-free bond markets. We present an algorithm to identify whether an inconsistency is probably due to the insufficient framework flexibility, the insufficient data quality, or the non-homogeneity of the dataset. In the latter case we study the problem of filtering out some instruments so that the remaining dataset be homogeneous. We show that the traditional filtering approach performs unacceptably poor and propose new algorithms. We find that the bonds, which get mispriced the most by a fitting algorithm, surprisingly are not the bonds, which cause the inconsistencies.
The paper is aimed at comparing the divergence of existing credit risk models and creating a synergic model with superior forecasting power based on a rating model and probability of default model of Russian banks. The paper demonstrates that rating models, if applied alone, tend to overestimate an instability of a bank, whereas probability of default models give underestimated results. As a result of the assigning of optimal weights and monotonic transformations to these models, the new synergic model of banks’ credit risks with higher forecasting power (predicted 44% of precise estimates) was obtained.
Our paper offers analysis of tendencies and determinants of development of local currency corporate bond markets in the period from 2006 to 2015. We consider a wide range of macroeconomic and institutional factors for 15 bond markets. The sample consists of 600 country-quarter observations. Multifactor linear regression models and the generalized method of moments are applied for the balanced panel data. Our analyses reveals that inflation and its stability, exchange rate, and market capitalization have a significant influence on the share of local currency bonds. Financial and macroeconomic instability stimulates the growth of local currency bond markets.
Transparent and effective corporate governance positively influences the financial stability of the company: it increases the investment attractiveness and reduces the costs of lending. For Russia, this problem is relatively new. And at the moment, corporate management in the manufacturing industry continues to be characterized by a high concentration of ownership and a combination of ownership and management functions. In this paper, using logistic regression we investigate the impact of corporate governance factors and industry expectations on a negative net worth of the companies in the period 2011–2015. The results showed, in particular, the probability of a negative company’s net worth is higher, the lower the index of business confidence in the industry; the presence of agency problem; the smaller the number of members in the board of directors; the higher ownership concentration; and, if company is not privately owned or joint-stock company in the manufacturing industry. Robustness of the coefficients of the final specification was confirmed.
When an asset-pricing model is claimed to explain a cross-section of portfolio returns, it should do so both within one asset class and across different asset classes. This paper illustrates that this is not always the case using the CAPM and Asness, Moskowitz and Pedersen (AMP, 2013) models applied to momentum and value portfolio returns as examples. Apparently, on one hand, the CAPM is almost as good as the AMP model in explaining the portfolio returns across asset classes, but on the other hand, the AMP model is almost as bad as the CAPM in explaining these returns within one asset class.
The paper studies salient features of systemic risk in a sample of 22 European (EU and non-EU) countries during January 2010–March 2016. Building on a novel dataset and conducting an empirical horse race, we determine pivotal systemic risk measures for the sample countries. SRISK and volatility indicator tend to lead other metrics, followed by leverage. In contrast to the conventional wisdom, composite systemic risk measures aggregated with the aid of principal and independent component analysis perform worse. The leading systemic risk measures exhibit a high degree of connectedness. The VIX index, TED spread, the Composite Index of Systemic Stress (CISS) and long-term interest rates underlie their dynamics. Two clusters within the sample are identified, with CISS and long-term interest rates being crucial to distinguish between them. There is only scarce evidence for causal linkages between systemic risk and industrial production in the sample countries, based on the concurring results of standard and nonparametric Granger causality tests.
This paper investigates how institutional and macroeconomic factors influence the profit efficiency frontier of Russian banks. We demonstrate that the macroeconomic environment is crucial for constructing the profit frontier. The cargo transportation index, exchange rate, and intermediation ratio have a positive relationship with this efficiency frontier while the share of loan loss provision in the loan portfolio is negatively associated with it. In addition, we find that such institutional determinants as a bank’s location, branch network diversity, and ownership type matter for constructing this frontier.
Subject The article discusses the existing methods to model the term structure of default probability and their drawbacks affecting the practical use.
Objectives The research is aimed to make effective suggestions to creditors on setting the technique to evaluate the probability of the corporate borrower's default, considering a changeable term before the loan deal ends, without contradicting IFRS 9 – Financial Instruments.
Methods The research represents the economic and statistical analysis, optimizes aspects of special distributions based on statistical data of rating agencies.
Results I refer to consolidated empirical data of rating agencies on the corporate sector to substantiate the two-parameter formula of term structure of default probability, which does not contradict IFRS 9 with respect to corporate borrowers. In this case, internal bank data are insufficient to build the separate internal model PD Lifetime or this process is too arduous.
Conclusions and Relevance I substantiate the default probability term structure formula, which is best in the pool of fitting distributions, being calibrated with empirically and statistically representative external data of rating agencies, covering a 44-year period. The formula is explicit, without implying complex calculations. The formula may prove useful in calculating the rate of reserves for loan assets, with their terms being coordinated with the principle lending mechanism (SPPI test) with respect to the second impairment phase under the classification given in IFRS 9.
Dynamic changes in the world bring challenges for making long-term future-oriented policy and strategy. A number of recent developments like drops in oil prices, increasing global conflicts, mass immigration, and economic stagnation have had disruptive effects on long-term policies and strategies. This new fast-changing landscape requires approaches and tools, which may help to practice adaptive Foresight for a dynamically changing context.Design/methodology/approach
The scenario approach presented in the paper aims to develop and multiple time horizons by bringing together short-term forecasts and long-term exploratory and visionary scenarios. Each time horizon allows for re-considering and dynamically changing drivers and assumptions of scenarios and thus builds not a single linear, but multiple and dynamic pathways into the future. Following the presentation on the background and description of the methodology, the paper illustrates the proposed approach with a case study on Science and Technology (S&T) development in Russia.
The flexible scenario approach allows developing and strategies with similar adaptability and flexibility. Practical implications: The scenario approach presented in the paper may be applicable for foresight exercises at all levels of governance including national and international, regional, and corporate.
The scenario approach presented in the paper may be applicable for foresight exercises at all levels of governance including national and international, regional, and corporate.
A novel scenario approach is presented for the formulation of Science and Technology policy with an illustrative case study.
Purpose: Dynamic changes in the world bring challenges for making long-term future-oriented policy and strategy. A number of recent developments like drops in oil prices, increasing global conflicts, mass immigration, and economic stagnation have had disruptive effects on long-term policies and strategies. This new fast-changing landscape requires approaches and tools, which may help to practice adaptive Foresight for a dynamically changing context.
Design/methodology/approach: The scenario approach presented in the paper aims to develop and multiple time horizons by bringing together short-term forecasts and long-term exploratory and visionary scenarios. Each time horizon allows for re-considering and dynamically changing drivers and assumptions of scenarios and thus builds not a single linear, but multiple and dynamic pathways into the future. Following the presentation on the background and description of the methodology, the paper illustrates the proposed approach with a case study on Science and Technology (S&T) development in Russia.
Findings: The flexible scenario approach allows developing and strategies with similar adaptability and flexibility.
Practical implications: The scenario approach presented in the paper may be applicable for foresight exercises at all levels of governance including national and international, regional, and corporate.
Practical implications: The scenario approach presented in the paper may be applicable for foresight exercises at all levels of governance including national and international, regional, and corporate. Originality/value: A novel scenario approach is presented for the formulation of Science and Technology policy with an illustrative case study.
We propose a model in which an entrepreneur, seeking outside fi nancing, sells a large equity share to an outside blockholder in order to signal his low propensity to extract private benefi ts. A conventional theoretical rationale for the presence of an outside block holder is mitigation of the agency problem via some type of monitoring or intervention. Our model provides a novel insight: outside blockholders may be attracted by fi rms with low, rather than high, agency problems. Our result yields a new implication for the interpretation of an often documented positive relationship between outside ownership concentration in a fi rm and its market valuation: such relationship may be driven by “sorting” rather than by a direct effect of blockholder monitoring. In fact, we show that the positive correlation may arise even if the blockholder derives private benefi ts and has no positive impact on the value of small shares. Finally, we argue that our analysis may help explain why the market reacts more favorably to private placements of equity as opposed to public issues.
Importance The article considers the features of terrorist attacks, which have an impact on stock indices.It analyzes 117 terrorist attacks committed in different countries within 1988–2016.
Objectives The research assesses how terrorist attacks influence stock index trends. It will enable market agents make better decisions and avoid excessive losses, reduce negative reaction of the market in general, and helpthe national financial system minimize the adverse consequences of terrorist attacks.
Methods We employ historical-logical, graphical, statistical methods and a comparative analysis to describean impact of different aspects of terrorist attacks on the dynamics of stock indices. We also systematize analytical information in this area.
Results The findings show that the impact of terrorist attacks on stock index dynamics depends on various factors, i.e. the number of victims, level of country’s economic development, day of terrorist attack, etc. We found out that the market trend before a terrorist attack had a significant influence on stock index movement after the attack.Terrorist attacks influence industries in a different way.
Conclusions and Relevance Terrorist attacks mostly have a dramatic impact on the dynamics of stock indices. However, the influence is often insignificant and impermanent. Therefore, investors should refrain from ill-judged financial decisions to avoid losses. The findings may be useful for investors, market makers and other market participants.
The Basel Committee on Banking Supervision (BCBS) standards are generally accepted by 46 countries in the world (28 jurisdictions). However, these countries differ in terms of details of standards’ implementation, i.e. national discretions take place. In 2012 the Basel Committee launched Regulatory Compliance Assessment Program (RCAP) to assure that all member states operate according to rules at least not softer than the original ones. Standards’ unification across countries results in need for less developed countries to adopt standards faster and in a more stringent form. One may foresee financial instability exacerbation as an outcome of such policy.
That is why paper objective is to demonstrate that standards’ implementation (RCAP) score is an implicit product of country’s macroeconomic and financial system development. For example, higher share of foreign banks and higher unemployment are strongly associated with countries that have regulation significantly different from the Basel original ones (having low compliance scores finally). This is exactly why standards should be differentiated by countries. Key message of the paper is that to promote financial stability regulator should target natural heterogeneity of risk management and risk regulation instead of that appealing artificial homogeneity (of which RCAP is one the examples).
We propose a market-consistent approach to the definition and construction of the implied term structure of the risk-free interest rates which are model-independent with respect to the choice of the fitting method. The main idea consists of the simultaneous fitting of the credit default swap (CDS) and the defaultable bond quotes where the theoretical prices are calculated in the framework of the reduced-form modelling of credit risk under standard assumptions. We obtain not only the implied risk-free zero-coupon yield curve but also the implied issuer-specific hazard rate curves. Prior to fitting, we perform a selection of bond issues and issuers. Next, we check for data consistency via arbitrage-like reasoning. Typically, the initial data needs a consistency adjustment, namely `artificial' widening of the observed bid-ask spreads for the selected financial instruments. We construct feasibility bands representing achievable precision of the fitting procedure depending on maturity. Then we apply this methodology to determine the term structure of the risk-free rates for the euro zone. This generic approach for the calculation of the risk-free reference rates in the euro zone can be helpful for the purposes of insurers and pension funds. In particular, the relevant term structure can be used in the assessment of technical provisions as requested in Article 77 of the Solvency II Level 1 text.
Russian stakeholders of joint stock companies, which shares are not traded on a stock exchange, and limited liability companies need the effective instruments which enable them to detect the facts of financial statement fraud quickly because the financial statement remains the main source of information about the companies’ performance for them. Although Institute of Auditors is one of the most reliable tools which identify financial statement manipulations, the costs, connected with audit, are too high and, and as a result, stakeholders have to look for other instruments to distinguish fraudsters, which make an attempt to overestimate or underestimate net assets and financial results, from non-fraudsters. Mathematical model of the American researcher Messod Beneish can be considered as an example of such tools. The general purpose of this paper is to identify whether it is possible, basing on the Beneish model, to create a new one, which enables to distinguish fraudulent from non-fraudulent financial statements reporting in Russia, and determine the accuracy level of fraud status forecasts made by using this model. In our research we are going to concentrate on identification of companies, which overestimate net assets and financial results. Tо obtain the information on the financial ratios included in the model we use financial reports of Russian both non-traded joint stock companies and limited liability firms. The conclusion can also be drawn that it is possible to develop the fraud detection probit model and linear model (integrated M-score index), which enabled stakeholders to identify fraud status correctly in 83% and 60 % respectively. Developing the model we include extra parameters, connected with growth rate of other income to sales ratio and an accounting policy of the company. It was found that fraud risk increases if the company chooses accounting policy according to which administrative costs are charged to core product expenses.
In this study, we use a sample of 192 listed shipping companies and employ a logit model in order to investigate the determinants of the probability of default. We enhance our analysis by isolating not only the cases of company liquidations but also those cases where companies had to change their legal status due to warning liquidity signals. Our key findings are in line with prior research and moreover we depict a changing trend in the marginal effects of relevant variables, on the probability of default. We further show, through an empirical application, how the obtained results can be used in a managerial decision-making process and in a bank credit underwriting process in order to assess the creditworthiness of a shipping company.
There are many studies revealing factors which influence the demand for financial services. However genetic features, determining the individual's overall postnatal behaviour, have not been studied within this context. This paper extends the previous literature by studying to what extent individual biological endowment, proxied by prenatal testosterone (PT, measured by the 2D:4D ratio), can determine personal demand for bank services and insurance. We use the data from the Russian Longitudinal Monitoring Survey (RLMS) of 2011–2012. Our findings confirm the existence of the link between inherent biological variation and financial inclusion: PT affects the use of bank cards, intention to borrow from a bank, having a bank deposit and the consumption of insurance products.
This study explores the firm-level relationship between earnings quality and investment efficiency. Higher quality of reported results has the capacity to positively impact the efficiency of company’s investment levels by over- and underinvestment reduction. The research is carried out on the sample of 7546 companies from Eastern Europe for the period 2010-2015. Eastern European countries have a unique institutional and business environment that is relevant to the purpose of this paper. We divide the sample into 2 fundamentally different economic sectors – industrial and retail – and test the significance of each factor in the main relationship. We also examine the factor of the firm’s ownership form by comparing earnings quality with investment efficiency values between public and private companies. Our main results show that a higher earnings quality mitigates both overinvestment and underinvestment issues. The relationship between earnings quality and underinvestment turns out to be stronger in the industrial sector. As for the comparison of public and private firms, public companies on average demonstrate a higher earnings quality and lower overinvestment issues.
In this article, we consider the relation between capital structure, corporate governance, ownership structure and performance of a company depending on its life cycle stages. The central aim of this study is to define the most sustainable and effective types of financial architecture by using the cluster and regression analysis. This study describes the three stages of the life cycle of a company: the first stage is growth, followed by maturity and finally the stage of decline, but for our research we only examine companies in the maturity stage. The research includes 11 countries from emerging markets and the primary sample includes 4,675 non-financial companies from 2011 to 2015. As the measure of a company’s performance, we used Tobin’s Q coefficient and total shareholder return. The primary sample was divided into the 3 life cycle stages by using the approach of comparing the growth rates of revenues at the average rate of revenue growth in the industry (Cao, 2010); however, we did not consider the earlier stages of the life cycle due to the specificity of the sample. A cluster analysis was performed on the sample for the growth and maturity stages in order to show the difference between the clusters that depends on the life cycle stages. We analyzed the clusters’ sustainability by regression analysis in each cluster. We described the influence of the financial architecture component on market performance. The results indicate more than one sustainable cluster and demonstrate the influence of the ownership structure, capital structure and the board characteristics on the company’s efficiency depending on the stage of the life cycle, which proves there is a need to take into account the issues of the life cycle. The managers and directors of a company can use results of this study when developing a company’s strategy, especially during the transition period from one life cycle to another.
The following research is dedicated to the analysis of political events’ impact on price dynamics of Russian stock market financial assets. In recent times, in line with the sharpening of internal and external political clashes, such events significantly affect the country’s financial system. However, this issue is insufficiently considered on Russian market. Constructed econometric GARCH models allowed unambiguously characterizing the impact of political events on return and volatility of financial assets. Moreover, the effects of leverage and clusterization were also assessed. The provided research discloses the impact of political events on the market as a whole as well as on separate industries. It was demonstrated that the obtained results are similar to the ones from other developing markets, however, the particularity of Russian stock market was also revealed. As the obtained results disclose the peculiarities of price formation on Russian market, they will be useful for domestic and foreign investors, operating on Russian stock market, other market participants and specialists in financial science. Analysis of a wider range of political events is a considerable advantage of the present research in comparison with the other papers that cover the Russian market. As a result, the market reaction to such events’ manifestation was studied more thoroughly.
The capital adequacy ratio is one of the important regulatory requirement for banks, which indicates its willingness to cover losses in the event of borrowers’ defaults. The Probability of Default (PD) and Loss Given Default (LGD) are two core parameters of the internal risk rating models used to calculate regulatory capital under the assumption that PD and LGD are independent. Papers based on developed countries data provide evidence with the dependence to be positive. It causes that banks underestimate the level of a risk of its loan portfolio, while they do not take into account the existence of such relationship. This is the first paper which aims to estimate the relationship between PD and LGD for Russian public companies. A major conclusion of the research is that using Russian data one cannot argue for the presence of risk parameter dependence whereas research using developed countries’ data suggests there is a positive one. This implies there is no need to overcharge capital for Russian banks compared to their counterparts from developed countries.
mportance Having been adopted in 2015, personal insolvency regulations significantly influenced the supply structure in the lending market, and dramatically changed banks' approaches to dealing with difficult customers, especially in consumer lending. Objectives The research analyzes strengths and weaknesses credit institutions face as a result of the enforcement of personal insolvency regulations, nature of changes in banks and debtors' interaction models, and transforms principles of lending policies in line with existing economic realities. Methods I apply methods of logic, economic analysis to study banking risks associated with insolvency of individual borrowers. Results I fundamentally evaluate principles of personal bankruptcy laws so as to determine possible banking risks at each stage of bankruptcy proceedings. Having analyzed cause-and-effect perspectives, I identified procedural and economic difference of debt restructuring processes and sale of debtors' property that took place as part of bankruptcy proceedings. Conclusions and Relevance The adoption of bankruptcy regulations will make banks be more tolerable to troubled borrowers seeking for debt restructuring. Banks seldom exercise their entitlement for suing bankrupt debtors, since this reduces interest, other income and the amount to be repaid. The analysis unravels the personal insolvency procedure in terms of vulnerable aspects and allows to understand advantages banks may enjoy if they deal with borrowers without initiating bankruptcy litigations.
This study investigates the impacts of CEO power on firm financing policies (i.e. debt financing and operating leasing) using the Caner and Hansen (2004) instrumental variable threshold regressions approach. The sample consists of a panel of 297 Chinese listed small and medium sized enterprises (SMEs) over the period 2009–2012. The empirical results indicate that there are threshold effects in the CEO power-debt relationship and CEO power-operating lease relationship. In particular, we find that firms tend to use more debt financing (and operating leasing) when CEO power index below a certain threshold level;
beyond the threshold level, CEO tends to manipulate firm capital structure to pursue their own interests, thus using less debt financing and operating leasing. In addition, our estimation results suggest a positive relationship between debt and operating leases when CEO power is smaller than certain threshold, while it becomes negative if the power index exceeds the threshold level.
Purpose. The purpose of this research is to look at effects of research and development expenditures (R&D) on value and risks of publicly traded companies by studying returns on stock exchanges of R&D-intensive economies (Republic of Korea, Finland, and Israel). Design/Methodology/Approach. Empirical tests of multifactor asset pricing models were applied in order to demonstrate that R&D intensity could be considered a pricing factor and affect investors’ risk premiums on those markets. In order to discover the reasons behind the asset pricing R&D anomaly, we investigated the nature of R&D risk further by looking into the interactions of R&D and currency risks. Findings. We discover that investors in stock markets of R&D-intensive countries should require a positive equity risk premium. However, the reduction of R&D intensity may increase firm’s risks and firms with higher R&D-intensity are less exposed to currency risks in R&Dintensive economies. Originality/value. Many researchers have investigated the relationship between a firm’s R&D and stock returns. But nearly all of them focus on the U.S. stock market and attempt to determine the reasons for R&D’s impact on firms’ risks and market value. Meanwhile, the role of R&D and related risks for investors could be even more prominent for stock markets in R&D intensive countries. In order to bridge this gap, we study stock returns on exchanges of three developed countries where the ratio of Gross domestic expenditure on R&D (GERD) to GDP is among the highest worldwide. We adopted the methodology of asset pricing empirical studies and developed it further to analyze the causes of R&D risks. The new methodology was applied to discover relationship between R&D intensity and currency risk exposure. Our interesting findings could be used for development of firm’s corporate strategies in those countries and for elaboration of policy decisions.
This paper estimates the capacity utilization rate for Russian manufacturing. We also propose a way to build continuous production capacity time series and indicators to describe the basic characteristics of production capacity. The data come from form 1-natura‑BM of the Russian Federal State Statistics Service. Our findings on the trends and structural characteristics of production capacity are shown to be significant for economic policy since we found that in recent years capacities utilization rate in Russian manufacturing industry has been not extremely high and that there is a strong correlation not only between capacities utilization rate and inflation rate but between capacities utilization rate and capacities commissioning intensity as well.
This paper proposes a new approach to decision making processes for investors to focus on factor investing and stock selection strategies on the national stock market by capturing the momentum effect (when two portfolios of past relative winners and past losers continue to beat a given benchmark for a certain period of time in the future). Our approach is based on ranking all the combinations of strategy design (5184 strategies) and the disclosure of the momentum effect with two criteria (mean return and risk) controlling for momentum return probability distribution.
It is new perspective on the momentum effect permitting its analysis from a comprehensive view taking into account the strategy’s different design elements and observing how the disposition of investor preferences has changed depending on the criterion. We distinguish two criteria: (1) maximizing the mean return of the investment with control t-statistics and the author’s innovation with the Bootstrap p-value, (2) minimizing the risk approximated by the number of drawdowns. This paper conducts the first comprehensive examination of the momentum effect on the Russian stock market.
Since 2013, we have observed an increasing number of failed Russian banks with negative capital and falsified financial reporting. We use previously unavailable data for the period 2010 – 1H2015 to develop a logit model predicting the probability of bank failure with negative capital. In order to do so, we suggest solutions for the class imbalance and variable selection problems. The models chosen are confirmed to be robust and have longer forecasting horizons compared to previous research. Also, we implement a novel probability-based approach to the out-of-sample forecasting evaluation which confirms a good fit of the selected models to data. The model predicts bank failures in three quarters and finds 33% of actual failures among 5% of banks with the highest predicted probability to fail (out-of-sample). In addition, we make available previously unpublished banking data for Russia
By present, many models of bankruptcy forecasting have been developed, but this area remains a field of research activity; little is known about the practical application of existing models. In our opinion, this is because the use of existing models is limited by the conditions in which they are developed. Another question concerns the factors that can be significant for forecasting. Many authors suggest that indicators of the external environment, corporate governance as well as firm size contain important information; on the other hand, the large number of factors does not necessary increase predictive ability of a model. In this paper, we suggest the genetic algorithm based two-step classification method (TSCM) that allows both selecting the relevant factors and adapting the model itself to application. Classifiers of various models are trained at the first step and combined into the voting ensemble at the second step. The combination of random sampling and feature selection techniques were used to ensure the necessary diversity level of classifiers at the first step. The genetic algorithms are applied at the step of features selection and then at the step of weights determination in ensemble. The characteristics of the proposed method have been tested on the balanced set of data. It included 912 observations of Russian companies (456 bankrupts and 456 successful) and 55 features (financial ratios and macro/micro business environment factors). The proposed method has shown the best accuracy (0.934) value among tested models. It has also shown the most balanced precision-recall ratio. It found bankrupts (recall = 0.953) and not bankrupts (precision = 0.910) rather accurately than other tested models. The ability of method to select the task-relevant features has been also tested. Excluding the features that are significant for less than 50% of the classifiers in the ensemble improved the all performance metrics (accuracy = 0.951, precision = 0.932, recall = 0.965). So, the proposed method allows to improve the advantages and alleviate the weaknesses inherent in ordinary classifiers, enabling the business decisions support with a higher reliability.
We study share price performance at ex-dividend date, and its relation to trading volume and a set of factors corresponding to different explanatory theories. Among the investigated factors that may have impact on ex-dividend date share price, are dividend yield, capital gains tax rate and dividends tax rate, transaction costs, market microstructure characteristics, market stock risk, and disposition effect. The research was conducted with the panel data of companies from BRIC zone for the period 2005-2015. According to obtained results, dividend capturing and disposition effect theories are likely to have explanatory power for ex-day phenomenon for our sample. Tax theory and dividend clientele theory have not found empirical support.
The topic of payout policy significance in terms of value creation has been developing for 50 years already. This development has led to the establishment classic theories that explain different patterns in the companies’ payout policy choices: signaling, agency costs theory, clientele theory and catering theory. However, tests results are not always consistent among different authors, which means that these theories cannot be used universally. Classic theories assume that all agents on the market are fully rational, which is rather unrealistic. These two facts led to the development of behavioral explanation of the payout policy choice. This approach focuses on the behavioral characteristics of managers that are responsible for the decision-making process in the company. Thus, the payout policy according to this approach is considered as the function of behavioral characteristics of managers (overconfidence, optimism, risk preferences, etc.) rather than the function of the financial variables.
This particular article is the review of researches that cover classic and modern theories of payout policy. The article covers the logic of the development of different views on the payout policy. The author covers articles that test different theories, analyzes main results and conclusions, investigates the reasons for the development of these theories. The main focus has been made on the behavioral approach which is considered as the most fruitful direction for the future research. The authors also cover the methodology of existing papers, variables that measure behavioral characteristics and results.
We present a nonparametric method for fitting the term structure of interest rates from bond prices. Our method is a variant of the smoothing spline approach, but within our framework we are able to determine the smoothing coefficient automatically from data using the generalized cross-validation or maximum likelihood estimates. We present an effective numerical algorithm to simultaneously find the term structure and the optimal smoothing coefficient. Finally, we compare the proposed nonparametric fitting method with other parametric and nonparametric methods to find its superior performance. We find that existing term structure fitting methods perform well in liquid markets while illiquid markets present new challenges, which we address in this article.
The purpose of of this study is to develop the instrument to measure the effectiveness of public investment in R & D and make timely adjustments to the scientific and technical policy. This will contribute to the growth of fundamental results, patents as well as their commercialization and innovative development of the the overall economy. The article assesses the effectiveness of public investment in research and technological development (RTD), including attracted extrabudgetary funds, on the basis of the authors' methodology for assessing the efficiency of public spending on RTD projects. The main distributors of state budget funds in Russia are the Federal Executive Bodies (FEB). The proposed tool allows first to evaluate the effectiveness of public expenditure on RTD in general, though it does not involve matching FEB among themselves, but only evaluates their work in promoting the development of their assigned research areas in dynamics. This method sets the general rules for evaluation of the effectiveness of state financial support of RTD, defines the key indicators reflecting the performance of such support and the use of science as a tool for ensuring the achievement of indicators and socio-economic development of the state.
Analyzing the accounting reports of 8573 Russian companies, the article determined the threshold values of the indicators for known foreign and domestic bankruptcy probability models for ten sectors of the economy. The developed a ten-factor bankruptcy model is based on sector-specific threshold values and has a relatively high predictive power for the majority of sectors.
This article evaluates cardholders' benefits resulting from the participation in the retail payments market. Using surveys and data simulations to obtain a representative sample of 1500 Russian individuals, the article finds significant, robust evidence in favor of positive cardholders' benefits. This study also examines the effect of the level of variable cardholders' benefits on the frequency of card payments. Results show that such effect is non-linear and forms a u-shape. Findings imply that unbalanced intervention may be detrimental to the agents' welfare and propose a mechanism for ex-ante evaluation of the effect of shocks and interventions.
There seems to be a consensus among regulators and scholars that in order to improve the functioning of a banking system it is necessary to raise the level of bank information disclosure. However, its influence on bank competition – which is an important factor affecting the efficiency and stability of the banking system – is left out of consideration. To test whether greater bank information disclosure is associated with both lower market power and lower concentration in the banking markets, we use country-level data covering the years 1998, 2001, 2005 and 2010. Our findings show that countries with higher levels of bank transparency have lower levels of bank concentration, while the link between transparency and market power is less pronounced. We also show that the reduction of competition due to stricter disclosure requirements depends on bank credit risks and the relationship is U-shaped.
The last couple of decades have witnessed significant institutional and structural changes in financial sector within a worldwide trend toward consolidation. In the segment of organized trading stock exchanges merge and develop into large and diversified publicly traded companies. These processes are rather complicated in case of a transition economy like Russia. In December 2011 MICEX, the first largest and state-controlled stock exchange acquired RTS, the second largest and privately owned stock exchange primarily designed for foreign investors. We empirically investigate whether the acquisition resulted in improved liquidity of the Russian stock market which was one of the declared acquisition objectives. We use the Kolmogorov–Smirnov and the Wilcoxon tests to compare market-wide liquidity in several discrete periods pre and post acquisition. A deep and thorough insight into liquidity performance is ensured by assessing liquidity from limit order book data of tick frequency along three dimensions (tightness, immediacy, and elasticity).
This paper aims to investigate the effect that internal corporate governance mechanisms have on the performance of commercial banks, how it differs for developed and emerging European markets, and whether it has changed as a result of the financial crisis. The key statistical tool used in the paper is the panel data analysis of the sample of 150 banks from 27 countries, over the period 2004-2011. We document the evidence partially supporting the effectiveness of smaller boards of directors, while the board independence seems to be negatively associated with the strategic performance of banks, especially in emerging markets and in times of a crisis. In emerging markets, state-owned banks appear to be more market-efficient, while high ownership concentration is considered by market players to be a negative signal. Studying the 2008 financial crisis period provides the evidence for structural movements in nonfinancial performance drivers.
Previous and new results are used to compare two mathematical insurance models with identical insurance company strategies in a financial market, namely, when the entire current surplus or its constant fraction is invested in risky assets (stocks), while the rest of the surplus is invested in a risk-free asset (bank account). Model I is the classical Cramér–Lundberg risk model with an exponential claim size distribution. Model II is a modification of the classical risk model (risk process with stochastic premiums) with exponential distributions of claim and premium sizes. For the survival probability of an insurance company over infinite time (as a function of its initial surplus), there arise singular problems for second-order linear integrodifferential equations (IDEs) defined on a semiinfinite interval and having nonintegrable singularities at zero: model I leads to a singular constrained initial value problem for an IDE with a Volterra integral operator, while II model leads to a more complicated nonlocal constrained problem for an IDE with a non-Volterra integral operator. A brief overview of previous results for these two problems depending on several positive parameters is given, and new results are presented. Additional results are concerned with the formulation, analysis, and numerical study of “degenerate” problems for both models, i.e., problems in which some of the IDE parameters vanish; moreover, passages to the limit with respect to the parameters through which we proceed from the original problems to the degenerate ones are singular for small and/or large argument values. Such problems are of mathematical and practical interest in themselves. Along with insurance models without investment, they describe the case of surplus completely invested in risk-free assets, as well as some noninsurance models of surplus dynamics, for example, charity-type models.
After the 2008 crisis, the Russian consumer loan market shows high growth rates, accompanied by the quality deteriorating even faster. At the same time, a great proportion of households are not attracted by the banks and borrow informally. In this paper, we aim to learn why households refuse to become bank clients, using the data from a 2009–2010 national survey of Russian households. Our results suggest that household's choice of the informal credit market is based not only on credit rationing, but also on a lack of financial literacy, credit discipline and trust in the banking sector as a whole.
Financing and payout decisions generally affect company’s economic performance: they have impact (both directly and indirectly) on the free cash flow and, thus, on company’s and shareholders’ value. Search for optimal capital structure and optimal payout policy strategy that are likely to maximize shareholders’ utility resulted in the papers, dedicated to determinants of capital structure and payout policy. In such papers, one of the policies is usually treated as a determinant for another one. This bound does not let researchers to make some conclusions about existence or absence of interrelation between payout and financing choices. To capture this interrelation, simultaneous regression analysis should be performed. Researchers, though, cannot come up with unified conclusion about the existence and direction of such interrelation. The absence of certain results as well as low level of research done on emerging markets make this topic rather relevant. The results of recent research on the interrelation between payout and financing decisions are discussed in this paper. We also develop an econometric model that allows us to check the existence of interrelation in emerging markets and to compare the results to those obtained from developed markets. The article contributes to the existed literature in the following directions: first, two debt variables are taken into account (total and long-term debt) as well as two payout policy variables (total payout and dividend payout). Second, macroeconomic variables are controlled. Third, the results obtained from the companies from emerging countries are compared to those obtained from developed markets.
The aim of this paper is to construct a reliable banks’ rating model for the main international agencies based on public information for the potential practical use. The Bankscope database for the period from 1996 to 2011 was used in the research. The ordered probit models show that inclusion of macroeconomic variables as well as the regional dummies improve their explanatory power. Moreover, the significance of the time dummies allowed us to conclude that rating agencies do change their grade when an economy operates on the different business cycle stages. Furthermore, the conclusions of a conservative nature of Standard & Poor’s ratings and overvalued Moody’s grades compared to the rating agency Fitch were performed. The models were checked for the in-sample and out-of-sample fit including distributional comparisons across agencies. The obtained model was classified as practically useful, as it gave 31 % of precise results and up to 70 % forecasts with an error within one rating grade. Moreover, 62 % of rating classes of banks were predicted without an error and more than 95 % of rating classes’ forecasts had an error within one rating class.
We considered the problem of choosing optimal hedging ratio taking into account interday and intraday return decomposition. It was shown that the standard hedging approach which uses only close prices (i.e. daily returns) is inefficient in comparison with hedging strategy based on open and close prices, i.e. when differentiating hedging ratio for interday and intraday periods. Results are confirmed both by applying Moving Window Regression and Error Correction Model for major world indexes for 1992–2012.
We investigate two insurance mathematical models of the following behavior of an insurance
company in the insurance market: the company invests a constant part of the capital in a risk
asset (shares) and invests the remaining part in a risk-free asset (a bank account). Changing parameters
(characteristics of shares), this strategy is reduced to the case where all the capital is invested in a
risk asset. The first model is based on the classical Cram´er–Lundberg risk process for the exponential
distribution of values of insurance demands (claims). The second one is based on a modification of the
classical risk process (the so-called stochastic premium risk process) where both demand values and
insurance premium values are assumed to be exponentially distributed. For the infinite-time nonruin
probability of an insurance company as a function of its initial capital, singular problems for linear
second-order integrodifferential equations arise. These equations are defined on a semiinfinite interval
and they have nonintegrable singularities at the origin and at infinity. The first model yields a
singular initial-value problem for integrodifferential equations with a Volterra integral operator with
constraints. The second one yields more complicated problem for integrodifferential equations with
a non-Volterra integral operator with constraints and a nonlocal condition at the origin. We reduce
the problems for integrodifferential equations to equivalent singular problems for ordinary differential
equations, provide existence and uniqueness theorems for the solutions, describe their properties and
long-time behavior, and provide asymptotic representation of solutions in neighborhoods of singular
points. We propose efficient algorithms to find numerical solutions and provide the computational
results and their economics interpretation.
This paper focuses on the efficiency of target-company investment decisions before and after Merger & Acquisition deals. We study whether M&A deals help to solve the problem of suboptimal investment after the acquisition. Using a sample of 145 target companies from BRICS countries that were acquired during the period 2004-2014, we outline those that had over- or underinvested before the deal and show that more than half the companies managed to optimize the investment level after the deal. We determine the key factors that improve the inefficiency of investment decisions and demonstrate that the industry and country have an impact on the degree of suboptimal investment.
R&D projects in pharmaceutical industry are extremely risky and bring benefits in long-run period. Self-interested managers try to avoid risk and underinvest in R&D. In this paper we study the effect of independent directors, insider ownership and scientific connections on R&D investments. Independent directors and insider ownership can mitigate agency problem by additional monitoring and convergence of interests. Scientific collaborations promote technological development and increase R&D. The research reveals the difference of the effects in emerging and developed market.
This study investigates the puzzle of zero-debt in emerging markets using a sample of firms from Eastern Europe during 2000-2013. The results of this paper are in line with the previous research of firms from developed markets. Firms that are financially constrained do not use debt as a result of credit rationing while financially unconstrained firms intentionally eschew debt to maintain financial flexibility and avoid underinvestment incentives. Furthermore, this study provides new insights into unconstrained firms’ performance during different economic situations. Firms that strategically avoid debt show better financial results than levered firms.
This article is devoted to the exploration of the mechanism of making decision about the company’s financing structure. It is shown that the interaction between various financial characteristics of company plays statistically significant role in the capital structure determination. Namely their possible values space may be split into several areas in which different, but might intersected, sets of financial indicators impact statistically significant on the capital structure. Moreover, the same indicator in different areas may have a differential impact on the capital structure. Also there were formulated several hypothesis about the potential direction of influence of various financial indicators on the capital structure assuming the truth of pecking order or trade off hypotheses. And one of the accompanying results of research was the getting facts in favor of the packing order theory for the companies in the chosen branch. Regression trees in combination with linear regression models were used to build the corresponding model of statistical relationship between the measure of capital structure and the set of company’s financial indicators. Model training and testing of the set of hypothesis were done using data about annual Russian companies reporting in the branch of automobile retail.
This article explores the expansion of the Russian state into financial markets after the 2008 global financial crisis. The main argument is that the Russian state has been unable to pursue its own developmental agenda in the sector despite increased regulation and state takeovers. While independent private market participants were pushed aside by state-controlled financial intermediaries, the state failed to follow its own policy strategy towards establishing an international financial centre in Moscow. Instead, the Russian financial market institutions were rendered into a vehicle for inter-bank lending under control of the Central Bank of Russia. Data from Russian stock market and corporate bond market trading highlights the trend. The study discusses the role played by informal power networks in redistribution of state-controlled resources and financial flows, and how this factor influenced the state regulation of financial markets in Russia.
This paper examines the dynamic beta of Russian companies within the framework of the market model. The closing weekly prices of 29 Russian stocks, six Russian sector indices and the MICEX Index as a market index during the period from January 2009 to June 2015 are used to estimate time-varying beta using various econometric techniques. According to the results for the analyzed period, semiparametric regressions are confirmed to be the most effective model. As regards the forecast period, multivariate GARCH models surprisingly outperform all the other methods. An analysis of beta dynamics shows that most of time-varying betas are non-stationary.
We present a new approach to technology road mapping (TR) which allows one to assess interactions of technologies and markets. Unlike the traditional methodology of TR that mostly relies on qualitative techniques, the proposed approach combines qualitative and quantitative methods. This bottom-up economic model allows the aggregation of estimates on different levels from the product group to industry used to quantify the market development. The KLEMS (capital, labor, energy, materials and services) production factors and multifactor productivity embedded in the model play the role of parameters measuring interactions between market outputs and technology innovation according to market-pull and technology-push effects. The qualitative methods include: STEEPV trend identification, 2 × 2 scenario analysis, and expert procedures. This allows for decreasing the number of parameters, inputs and calculations in the economic model. At the same time, balance between qualitative and quantitative techniques provide more realistic estimates for technological and market parameters. The assessment of interactions between technologies and markets is illustrated using the case of civil aircraft manufacturing in Russia. Technology impact is measured in terms of output growth of the industry.
The rapidly growing Russian national currency bond market is demonstrating attractive yield levels after global crisis 2008-2009. A significant share of ruble bond issues has relatively low trading volume, so liquidity risk is of particular importance for potential investors. This article provides an analysis of theoretical approaches to the construction of bond liquidity integral indices andreviews existing practice in the Russian market. First, it compares methodologies of Russian investment banks (Trust, Gazprombank, Zenith and others) and a new cyclic algorithm introduced by Thomson Reuters Agency (TRLI 2015). In empirical part of our research Thomson Reuters’ integral indices of bond liquidity (weighted and non-weighted) are tested in the context of explaining the difference in yields of 1118 Russian national currency bonds outstanding (including government,municipal and corporate bonds). The multi-factor cross-sectional regression analysis results show that the influence of both Thomson Reuters liquidity indices on Russian bond yields is fairly stable. Duration and S&P rating also exert stable influence on bond yields. The non-weighted liquidity index has better explanatory power than the weighted one.
We look for typological similarity or dissimilarity between the banking systems of China and Russia. In both countries we have identified a multitier and hierarchically organized system of commercial banks headed by several institutions under direct control of the government. These core state-controlled banks combine commercial banking with development banking. The difference between the Chinese and the Russian system in terms of bank relevance and directed lending was highlighted by T. Speranskaya in 2009, but now the growing state “dirigisme” gradually erodes that difference. We also suggest that the lending by the core statecontrolled banks complements budgetary funds as a source of investment into fixed assets of nonfinancial enterprises in both countries.
In this research we investigate the problems of dynamic relationship between electricity price and demand over different time scales for two largest price zones of the Russian wholesale electricity market. We use multi-scale correlation analysis based on a modified method of time-dependent intrinsic correlation and the complete ensemble empirical mode decomposition with adaptive noise for this purpose. Three hypotheses on the type and strength of correlations in the short-, medium- and long-runs were tested. It is shown that price zones significantly differ in internal price-demand correlation structure over the comparable time scales, and not each of the theoretically formulated hypotheses is true for each of them. We can conclude that the answer to the question whether it is necessary to take into account the influence of demand-side on electricity spot prices over different time scales, is significantly dependent on the structure of electricity generation and consumption on the corresponding market. © 2015 Elsevier B.V.
The matter of the Maternity capital program effectiveness is still arguable. Among demographers, it is widely believed that monetary stimulation of birth rate simply shifts the birth calendar and does not increase the net fertility rate. However, this prediction is only a hypothesis, which still needs to be subjected to rigorous empirical testing].
In my research, I test the prediction, that that program affects the inter-birth interval. My analysis confirmed this hypothesis, and showed that women without higher education indeed shorten the interval between births. The birth interval in this group is shortened, on average, by 4.6 months. At the same time, women with a higher education are not affected.
The efficiency of the interbank market depends largely on its inherent disciplining mechanisms. This paper investigates the discipline mechanisms of Russia’s interbank market, testing the hypothesis that market discipline in Russia was strong enough to constrain excessive risk-taking by participating banks before, during, and after the 2008–2009 financial crisis. The existence and efficiency of quantity-based market discipline are investigated using the Arellano-Bover and Blundell-Bond linear dynamic panel-data estimations. Our approach detects market discipline only during the financial crisis, not before or after. Even during the crisis, the efficiency of market discipline in curbing bank risk-taking was rather low.
Mobile banking is one of the most dynamic developing types of distance banking services. For the recent years in Russia, the amount of individual bank accounts with the ability of the distance access through mobile devices increased more than by 20 times. Every year more and more banks start to offer mobile banking services. Despite this, the popularity of mobile banking applications is lower than the popularity of other banking services. Thus the problem of mobile banking adoption by customers is still an extremely important problem.
The authors analyzed foreign surveys devoted to the exploration of the incentives to mobile banking usage. The model developed by the authors is based on the well-known theoretical and empirical approaches and taken into account Russian peculiarity. As a theoretical basis, the most widespread theories describing technology acceptance and innovation diffusion were used. Using structural equation modeling (SEM) approach, the authors verified key incentives to use mobile banking by mobile Internet users i.a. perceived usefulness and perceived efforts.
These results are in accordance with most foreign surveys in this subject area. The findings also will be helpful for banks as they allow these financial institutions to highlight the cutting edge of mobile banking in Russia.
We investigate the cross section momentum effect in the Japanese stock market over the period January 1997 to December 2013, sub-periods before August 2008 and during the crisis September2008–2009. From previous studies, it follows that the Japanese market is the exception to the findings on developed capital markets (momentum effect does not occur or is weak). Our study highlights the limitation of standard notions; we document the conditional nature of momentum and identify the characteristics of companies and their stocks and market states, allowing investors to earn positive momentum profit in the Japanese market (the statistically significant positive monthly return of zero cost portfolios is not less than 1%). It is shown that investors should take into account the seasonal pattern (for the Japanese stocks this revealed two months when we do not recommend taking investment activity) to increase portfolio profits. We explain the results from the specifics of the Japanese financial and governance systems, the ownership structure of listed Japanese firms and socio-cultural factors.
We analyze a static Kyle (Continuous auctions and insider trading. Princeton University, Princeton, 1983) model in which a risk-neutral informed trader can use arbitrary (linear or non-linear) deterministic strategies, and a finite number of market makers can use arbitrary pricing rules. We establish a strong sense in which the linear Kyle equilibrium is robust: the first variation in any agent’s expected payoff with respect to a small variation in his conjecture about the strategies of others vanishes at equilibrium. Thus, small errors in a market maker’s beliefs about the informed speculator’s trading strategy do not reduce his expected payoffs. Therefore, the original equilibrium strategies remain optimal and still constitute an equilibrium (neglecting the higher-order terms). We also establish that if a non-linear equilibrium exists, then it is not robust. © 2015 Springer-Verlag Berlin Heidelberg
This article investigates how the combination of positions between the Board of Directors and the management affects bank’s profitability. We use the 2010 bank-level data from 112 countries (Bankscope). Our results suggest that the positions combination reduce both banks’ ROA and ROE. We also show that the higher is the proportion of the Board members, who also hold a managerial position, the lower is the profitability of a bank. Thus, the corporate governance regulation should go beyond a simple restriction on holding simultaneously the CEO and the head of Board of Directors positions.
Researchers have long tried to define the impact of corporate mergers and acquisitions on company performance. We contribute to the existing literature by examining the performance of M&A deals in emerging capital markets based on the economic profit model and comparing the results with ones obtained by means of traditional method—accounting studies. Examining a sample of 80 deals initiated by companies from emerging capital markets over 2003–2009, we find that M&As are value-destroying deals for the combined firms. Results from the long-run analysis prove the negative industry-adjusted differences between post-acquisition and preacquisition performance measures. The difference is equal to a significant −3.3% for the EBITDA/sales ratio. The economic profit approach demonstrates a similar result. Economic profit has declined due to M&A deals by $4 million. We also analyze the determinants of M&A performance, such as method of payment, business similarity, and type of geographical expansion (cross-border versus local deals).
The article examines the role of the state in the Russian banking industry.
What is the relationship between the two largest emerging financial markets of Eastern Europe, Russia and Poland, and how do they impact the region’s stock markets? The purpose of this paper is to examine the role of these two countries in regional volatility by examining their effect on two separate phenomena: financial volatility, defined here as long-term interrelations, and contagion, a more short-term phenomenon. Utilizing bivariate DCC-GARCH modeling, this paper estimates long-term volatility spillover effects and short-term contagion effects and their origins during several periods of financial crisis in the Central and Eastern European region. Our results show that the long-term impact of volatility in the Russian market is much more substantial than that of Poland in Central and Eastern Europe, with this disparate impact corresponding to each country’s level of market capitalization. Additionally, our results show that Russia served as a source of short-term contagion for neighboring countries during its banking crisis in 2004 and during the Russian stock market fall in 2008. Poland had comparatively less effect on the region during the Global Financial Crisis. Moreover, the entrance of Poland into the European Union in May 2004 had no impact on stock markets in the region in terms of enhancing contagion.
We suppose that the agency conflicts between shareholders and bondholders may affect the level of risk of company's debt instruments, therefore, increasing the cost of debt of the firm. A number of corporate governance mechanisms are developed to alleviate the conflicts. This paper surveys research on the relationship between corporate governance and the cost of debt. We pay special attention to the empirical papers with specific findings on cost of debt's nonfinancial determinants in emerging markets.
Recent empirical research suggests that country-level and firm-level governance institutions are substitutes with respect to their effect on firm value. In this paper we demonstrate that during a crisis these institutions may actually become complements. Specifically, we find that the decline in companies’ valuation during the financial crisis of 2007–2009 was more sensitive to firm-level transparency in countries with stronger investor protection. We propose a theoretical model that reconciles our findings with the results in the literature. In our model, during “normal times” strong firm-level governance is crucial to attract outside financing in countries with weak investor protection, but is less important in countries with good investor protection. During a crisis, however, investment opportunities decline even in countries with strong investor protection, and, as a result, relative importance of firm-level governance increases in such places.
This paper examines mean-to-mean, volatility-to-mean and volatility-to-volatility spillover effects for stock markets of BRIC countries
We revisit the Kyle (1985) model of price formation in the presence of private information. We begin by using Back's (1992) approach, demonstratingthat if standard assumptions are imposed, the model has a unique equilibrium solution, and that the insider's trading strategy has a martingale property. That in turn implies that the insider's strategies are linear in total order flow. We also show that for arbitrary prior distributions, the insider's trading strategy is uniquely determined by a Doob h-transform that expresses the insider's informational advantage. This allows us to reformulate the model so that Kyle's liquidity parameter is characterized by a Lagrange multiplier that is the marginal value or shadow price of information. Based on these findings, we can then interpret liquidity as the marginal value of information.
We examine the impact on the quality of a securities market of hiding versus displaying orders that provide liquidity. Display expropriates informational rents from informed agents who trade as liquidity providers. The informed then exit liquidity provision in favor of demanding liquidity where they trade less aggressively. Trading costs to uninformed liquidity demanders are higher, bid-ask spreads are wider and midquotes are less informationally ecient when orders that provide liquidity are displayed. Our analysis suggests that market innovations, which might seem to favor the informed over the uninformed, can enhance market quality by intensifying competition among the informed.
Competitive pressure from dark pools has led securities exchanges to offer a variety of ways by which traders can hide orders that provide liquidity. These are the pricecontingent orders (limit orders) that aggregate to the market’s supply schedule, and against which orders to trade at the market price (market orders) are executed. Hidden orders account for about 30% of transaction volume on some exchanges, and their proliferation raises questions for exchanges and regulators concerning the effect of hidden orders on market quality. In classic microstructure models, adverse selection arises because informed traders can conceal their market orders among the orders of the uninformed. The intuition from these models suggests that explicitly allowing hidden orders will increase adverse selection and the losses suffered by uninformed traders.
We study the risk sharing implications that arise from introducing a disaster relief fund to the cat insurance market. Such a form of intervention can increase efficiency in the private market, and our design of disaster relief suggests a prominent role of catastrophe reinsurance. The model predicts buyers to increase their demand in the private market, and the seller to lower prices to such an extent that her revenues decrease upon introduction of disaster relief. We test two predictions in the context of the Terrorism Risk Insurance Act (TRIA). It is already known the introduction of TRIA led to negative abnormal returns in the insurance industry. In addition, we show this negative effect is stronger for larger and for low risk-averse firms -- two results that are consistent with our model. The seller's risk aversion plays an important role in quantifying such feedback effects, and we point towards possible distortions in which a firm may even be overhedged upon introduction of disaster relief.
Researchers have long tried to define the impact of corporate diversification on firm value. Academic papers mainly concentrate on the effects of corporate diversification in mature markets while its consequences in emerging capital markets are less explored. This article presents the results of an empirical analysis of corporate diversification strategies of a sample of companies from BRIC countries that expanded via acquisitions during 2000–2013. We contribute to the existing literature by examining the effects of corporate diversification on firm value during the pre- and post-crisis periods. In line with other studies, we distinguish between related and unrelated diversification and in contrast to them we single out and separately analyze horizontal, conglomerate and vertical acquisitions. Based on a sample of 319 deals initiated by companies from BRIC countries, we found positive (3.32% and 9.01%) and statistically significant cumulative abnormal returns for conglomerate acquisitions during the pre- and post-crisis periods, correspondingly. We also found that the market reacts positively and statistically significant to the announcements of horizontal and vertical integration only during the pre-crisis period.
In recent years corporate international diversification has become a widely used growth strategy for companies from both developed and emerging markets. Nevertheless, academic papers provide contradictory results on whether the influence of international diversification on firm performance is positive or negative. This chapter presents the results of an empirical analysis of corporate international diversification – performance relationship on a sample of companies from BRIC countries, which expanded geographically in 2005-2015. We contribute to the existing literature by applying a new methodology to identify the performance effects of corporate international diversification based on an economic profit measure. The results indicate that there is a non-linear relationship between the degree of international diversification and economics profit spread. Additionally, for BRIC companies international diversification on average does not have a significant impact on expected long term performance, measured by Tobin’s Q.
This chapter surveys the recent trends in the literature on the performance of M&A deals in developed and emerging capital markets. This literature is voluminous, diverse and challenging. We focus on the transactions within one country – domestic M&As – in particular focusing on the methods that the researchers use to estimate whether M&A deals promote efficiency gains or not. We discuss the research instruments which allow an assessment of the effects of M&As on firm operating performance and on firm value. Analysing the results of latest empirical studies we reveal that target shareholders gain significantly in M&A deals. The evidence suggests that in most cases acquiring shareholders receive negative or insignificant returns in the short-run in developed capital markets, while in emerging economies acquiring shareholders mostly gain in M&A deals. Operating performance analysis reveals mixed results in developed and emerging capital markets, while the analysis of papers which use value performance indicators show the destruction of company value due to M&As in developed and emerging capital markets. The review also analyses studies that examine the relationship between different methods.
This chapter contributes to the literature on M&A performance by examining the impact of M&A deals on company value over the long-run in developed and emerging economies. Examining a sample of 153 and 125 deals from Western European and emerging capital markets respectively, 2002-2013, and employing economic profit as a performance measure,we find that transactions in developed markets create more value for shareholders than M&As in emerging economies over the two-year period surrounding the deals. After adjustments for industry trends, economic profit significantly decreases for firms in emerging capital markets, taking negative values, while for companies in developed markets we observe insignificant improvements in economic profit values following acquisitions. These results indicate that companies in emerging capital markets cannot achieve the planned synergies, integrate successfully and improve the performance of the combined firms. We find that industry and geographical diversification influence the performance of M&A deals in emerging and developed countries respectively. We also find that the effects on company value differ for stock and cash deals, and for high- and low-tech transactions in both markets. Testing the impact of economic crisis of 2007-2008 on the performance of M&A deals we reveal that the adjusted economic profit does not differ significantly between pre- and post-crisis M&As.
The literature on M&As provides ample evidence for the variability of premiums paid in M&As deals over time and in different types of deals. Most work has been done on the data from developed markets. Using a sample of M&A deals in the largest emerging markets (BRIC) for 2000–2015, we examine three types of factors (acquirer characteristics, target characteristics, deal characteristics). To measure the premium, the event studies method is used, therefore the data on cumulative average abnormal returns (CAAR) is adjusted to the market movements in each respective country. We focus on three levels of acquired stakes (>25%, >50% and 100%). The study contributes to a deeper understanding the differences in the size of premiums among the countries and the interaction of the main determinants which influence the magnitude of the premium. The regression results document positive drivers of the size of the premium including, the percentage of the stake and industry relatedness. Besides these stylized determinants, the premium increases if the deal is made in a crisis year and by a domestic bidder. The negative determinants include the target size, its financial leverage and the pre-bid stake of the acquirer (toehold).
The paper is dedicated to developing a system for identifying and assessing cyber-risks to support investment decision-making in a machine industry enterprise. It is designed for projects related to high-tech equipment development and introduction. The problem is acute because the existing methods of cyber-risk analysis have some drawbacks, which prevent them from being used at a time of growing information threats. A structural-logical scheme for the cyber-risk analysis system has been developed, and detailed descriptions are provided for some blocks of the system and their tools. The research methods include system approach to problem-studying, analysis of fundamental statements given in literature, and analysis of the existing tools used in practice for solving these problems. The presented system has some advantages in comparison with such common approaches as risk maps or factor analysis of information risks (FAIR). Since it is built on risk-control principles, it ensures that all actions of management concerning cyber-risk-control are integrated and coordinated.
The system also contains effective tools and methods for assessing cyber-risks in quantitative terms, calculating a consolidated effect with due consideration of risks, assessing the impact this effect makes on the strategic goal indicator of a project, comparing project implementation scenarios given cyber threats with risk appetite to evaluate the acceptability of the project. These advantages make the system dynamic and integrative, reactive to the changes of the cyberspace and emergence of new threats. It can have a substantial practical application in managing investment projects related to the development and introduction of high-tech equipment in enterprises of the sector.
We developed the mechanism of assessing cyber risks for Internet of Things (IoT) projects. The relevance of this topic is explained by growing sophistication of cyber-attacks, the speed of new threats emergence and increasing damage from the attacks. The paper addresses decreasing efficiencies of existing mechanisms of cyber risk assessment and fills the research gaps in this area. Results include development of the mechanism’s concept, its block diagram, the specification and description of its comprising tools and the case study. Unlike peers, the mechanism provided holistic approach to cyber risk assessment; integrated and coordinated all related activities and tools. It simulated the confidence interval of project return on investments (ROI) and showing the chances to go above risk appetite. It makes cyber risk assessment dynamic, iterative, responsive to changes in cyber environment. These advantages let us conclude that the mechanism should have a significant scientific and practical use.
In 2016 passenger service on the Moscow Central Circle (MCC, a circular urban rail line in Moscow) was reintroduced after its closure in 1934. The launch of this line allowed us to study the effects of a transport infrastructure project using observed rather than model-forecasted data.
We collected empirical data on changes in real estate values, land use, transportation flows and travel behaviour as consequences of integration of the new rail line into existing urban transit system.
The research project consists of several parts. First, we studied residential rent rates. The rent growth effect was most substantial in the residential areas around Moscow Central Circle stations without access to existing metro stations.
Second, we used the Node-Place model to evaluate the magnitude of the potential (and officially planned) land use changes in the long-run, i.e. the increase in the place value. We revealed that the long-term MCC impact is modest, because the opportunities for land use change around the MCC stations are currently limited and therefore the increased node value is not accompanied by the proportional change of the place value.
Third, we used Moscow Metro origin-destination matrices for typical working days in March 2016 and March 2017 to evaluate the impact of the MCC on the redistribution of passenger traffic volumes. We observed an insignificant decline in load level of Metro Circle line and radial lines and interchanges in the city centre.
Finally, we studied changes in travel behaviour. The majority of respondents do not use the MCC to reach locations near new stations but use it mostly to optimise their existing routes, which also supports the findings of the relatively low place value of the territories around the new stations.
Repeating the same measurements regularly will allow us to monitor the changes in the use of the MCC and track its performance and its effects over time. This paper covers the short-term effects that occurred in the first 12 months of the MCC operation.
The main goal of this paper is to study interconnections between credit ratings and financial indicators of industrial companies from BRICS countries. We use method of patterns, one of the modern methods of nonlinear modeling, to identify groups of heterogeneous objects with different influence on ratings. Additionally, in this research, we evaluate Tobit regression model for selected groups and establish some credit rating patterns for the BRICS industrial companies. Our results of Tobin model, may have practical implementation in short-term financial management.
We study the relationship between SMS (small medium size) firm ownership structure and obstacle to finance. The empirical research considers both the concentration of the company's ownership (controlling owner) and the presence of foreign participants in the equity capital. Our aim is to identify those determinants of financial markets (bond market development), legal institutions and firms characteristics in the transition economies of the post soviet countries that can be considered as barriers to attracting financial resources. This paper sheds light on large shareholders’ influence on obstacle to finance.
The purpose of the article is to identify the specifics of political leadership from the standpoint of morality and the dominant model of the political system in the developed countries of the world. Leadership is a necessary element of the management system of any organized human activity. The leader is the head of the team aimed at fulfilling the common goal. If the goal is directly related to the interests of society as a whole then such a leader is a political leader. Political leadership becomes possible only if a person expresses the interests of certain groups (segments) of society. But since there is no unity of interests in the society, the leader has a risk of political leadership.
Leaders often succeed each other in the course of an acute political struggle due to the organization of the country's political system. Therefore, no continuity of their political goals is usually possible. The only exception is the political organization of the society in which the leader has the opportunity to remain in office for a period of 10-20 years. The realization of really meaningful social goals is possible only at such terms measured by the life expectancy of generations of people.
Short-term performance of the political leader is a political reason for the fact that society develops spontaneously, randomly. Only the long-term functioning of the leader or the continuity of the political goals of successive leaders is the political basis for such social development when society itself manages its development.
National Research University – Higher School of Economics (Moscow) and author has been researching the leasing market of Russia for 20 years. The article presents based on the author's survey of the leasing market by results of 2016, its dynamics on the value of new contracts and leasing portfolios, structure of the Russian leasing market in critical sectors, such as railway rolling stock, motor transport, air transport, energy, engineering, etc., the structure of leasing for regions of the Russian Federation. The article presents the structure of leasing 10 sources, including loans, own funding, advances, bond issue, etc.; a comparative analysis of the level of concentration of leasing in Russia and Italy; analysis of bad debts; Variant calculation of leverage in leasing on the basis of the author's methodology; tax design of the Russian leasing.
The article presents based on author's surveys of the leasing market for 19 years its dynamics on the value of new contracts, the structure of the Russian leasing market in critical industries, such as railway rolling stock, vehicles, air transport, energy, engineering and major lessors in these industries, the article presents the structure of leasing 10 sources, including loans, own funding, advances, bond issue, etc.; features of power equipment leasing and renewable sources of energy; analysis of bad debts; Variant calculation of leverage in leasing on the basis of the author's methodology; tax design of the Russian leasing.
Recent research on the international Monetary Fund [Global Financial Stability Report, 2015] outlines that participants of fixed income assets market in advanced and emerging market economies have become worried that both the level of market liquidity and its resilience may be declining.
The market liquidity is a many-dimensional concept and cannot be captured by any single measure. Nonetheless, depending on what dimension of market liquidity one is trying to estimate (for instance, time, cost, or quantity) some measures are more informative than others.
Based on the data provided by the National Settlement Depository and the National Fund Association and covered the period from the 6 January 2014 to 15 June 2015 the liquidity of 1497 different bond emissions was analyzed. We calculate a daily liquidity index for each bond using Pareto regularization approach [Gambarov, 2010]. This index is constructed from three bond emission characteristics: trading volume, number of trading days, and number of transactions. We found that the most important factor from these three for Russian bonds is the number of trading days due to the very low trade intensity of Russian fixed income market (the largest part of the Russian corporate bonds even has no active market).
Considering the average liquidity on the Russian bond market we conclude that during last year the deterioration tendency has been dominating on the market. Thus, the main purpose of current research is to analyze which factors bring the major impact on the market liquidity (in particular, weaken) in Russia and in other advanced and emerging market countries.
A lot of factors affect the liquidity of the markets, which can be broadly divided into three groups: risk-driven factors, cost-driven factors and investors and issuers characteristics. It is also worth mentioning that macroeconomic factors (e.g. restrictions on derivatives trading (such as those imposed by the European Union in 2012) have weakened the liquidity of the underlying assets) strongly affect markets in general and liquidity in particular.
We analyze institutional determinants of the development of local currency (LCY) corporate bond markets in the period from 2010 to 2016. We consider a wide range of indicators of the quality of institutional environment: the Heritage Foundation's Index of Economic Freedom, the Worldwide governance indicators, the World Economic Forum’s indicators of corporate culture, development and regulation of financial markets. Unlike most previous studies, we test not only static regression
models (multifactor linear regressions), but also dynamic models based on the generalized method of moments, which allows to solve the problem of endogeneity of variables.
The results show that low quality of institutional environment, macroeconomic and financial instability stimulate growth of the share of LCY corporate bonds in the total issuance volume. In the periods of instability LCY corporate bonds become less attractive for foreign investors, and issuers are forced to raise capital in the domestic market. The most significant factors in both static and dynamic model specifications are the World Bank’s indicators of regulatory quality and rule of law.
A decline in sovereign credit ratings also gives impetus to the development of LCY corporate bond markets.
An original result is that more developed stock markets suppress the growth of LCY corporate bond markets: equity and corporate bonds are competing financing sources for companies from developing countries. A developed banking sector contributes to the growth of the LCY corporate bond market: banks act as dealers and market makers. Devaluation of the national currency has a significant positive influence on the explained variable.
This article deals with the important issues of adults and schoolchildren financial literacy development. The authors explore possible ways for development of financial literacy of schoolchildren as well as potential development tendency of financial education in the context of dynamically developing information environment. The introduction describes the importance of developing the financial literacy of people (starting from school age), immediacy of the problem in connection with education modernization in the face of intensively changing information environment. Importance of this topic is associated with the need for students to acquire knowledge and practical skills in financial markets functioning and regulation, financial methods, and economy instruments aimed at ensuring effective interaction of citizens with the economic institutions of society. Some of author's tasks are presented for monitoring the achievements of students and determining their skills to navigate in the economic space, making optimal decisions in life situations to avoid financial risks. The study results allow us to draw conclusions about the effectiveness of methods and tools for implementing special programs to increase financial literacy and financial sustainability of the population. The study may be of interest for graduate students, methodologists, teachers of secondary schools, secondary specialized institutions, and universities in the relevant areas.
This book gathers both theoretical and practical perspectives, by including research issues, methodological approaches, practical case studies, uses of new policy and other points of view related to equity market efficiency to help address the future challenges facing the global equity markets and economies. Information Efficiency and Anomalies in Asian Equity Markets: Theories and evidence is an insightful resource that will be useful for students, academics and professionals alike.
National Research University – Higher School of Economics (Moscow) and author has been researching the leasing market of Russia for 19 years. The article presents based on the author's survey of the leasing market dynamics on the value of new contracts and leasing portfolios, structure of the Russian leasing market on major industries such as aircraft leasing, leasing of mechanical equipment, railway rolling stock, car leasing, leasing of real estate, etc., as well as regional structure of leasing. The article contains the author's calculations of the three options of leverage in leasing on the basis of the methodology developed by the author. The article presents the regression model that identifies four factors influence the cost of real estate leasing contracts for 118 deals, identified by the author.
The Empirical evidence on fiscal multipliers is very heterogenous. In this paper we first survey available estimates of fiscal multipliers to try to understand their heterogeneity. We provide a general framework that allows to make the identification and specification choices made by the different authors explict and leads hopefully to a better understanding of the heterogeneity of results.
In article the system of indicators of an estimation of use of social and economic potential of region, approaches to its forecasting and maintenance of unity of received estimations is considered.
This article is devoted to the analysis of coherence of financial recommendations with respect to securities of the Russian companies. The study is based on the analysis of approximately 4000 recommendations and forecasts of 23 investment banks with respect to around forty securities of Russian stock market over the period of 2012-2014 years. The predictive history of each of the investment bank was considered as evidence in the framework of evidence theory. The coherence of recommendations was evaluated with the help of the so-called conflict measure between the evidence, which determined on the subsets of the set of all evidence. Then the study of coherence was reduced to analysis of values of the conflict measure. This analysis was performed with the help of game-theoretic methods (Shapley index, interaction index), network analysis methods (centralities), fuzzy relation methods, hierarchical clustering methods.
A refined definition of bank revenue, controlling for the effect of currency and securities revaluation, yields meaningful results in comparative bank efficiency computations.
Our research is devoted to trade strategy’s profits and study of financial anomalies in stocks pricing. We analyze Momentum (and Reversal) strategies construction that is based on historical prices of assets. The main feature of the momentum strategy
is that past stocks relative return (higher or lower than mean return or benchmark set) is used for selecting assets in portfolio.
The accent in our paper is made on revealing the nature of momentum and reversal (or contrarian) effects over time periods up to one year through the analysis of two basic determinants of abnormal profits of arbitrage portfolios of different design:
cross-sectional variance of mean returns (rational explanation) and time-series predictability of asset returns (irrational explanation according EMH). The analyzed period embraces, from January 2006 to December 2014. Our research of Russian
stock market has shown that, considering the choice of portfolio design (temporal windows for selecting stocks for portfolio and investment, and weight of stocks in the portfolio) and stock sample for constructing strategies (the sample should include
major companies with liquid stocks) momentum and reversal effects do take place. Momentum profit is demonstrated in short-term strategies (3 to 6 months), while reversal effect is marked for ultra-short (less than a month) and long periods
(11–12 months). Profit decomposition shows that the component responsible for rational explanations is statistically significant and its weight prevails in most momentum strategies with investment period not exceeding 9 months.
The aim of this work is to compare shifts in the consumer behaviour of Russian households since the mid-nineties till nowadays. The research considers the consumer behaviour of the Russians over almost the maximum possible available data RLMS period, focusing on the crisis years. Special attention is paid to analysis of the effects of crises in 1998 and 2008. To reveal effects as shifts in consumer behaviour in the aftermath of two crises panel data analysis is used to estimate QAIDS model. Due to the complete sample attrition observed in RLMS dataset since 1994, pseudo-panel approach is used.
National Research University – Higher School of Economics (Moscow) and author has been researching the leasing market of Russia for 18 years. Particular attention in the article presents the dynamics that characterizes the development of market in the country by value of new contracts, the largest leasing portfolios, calculated author of segmental structure of the leasing market and regional structure. This article presents the results of the econometric analysis of the relationship of the value of new contracts with the amount of advances, terms of contracts and lease rate per cent. Exploring the structure of financing of leasing operations, the author has developed a new approach to determining leverage leasing projects.
The article describes proposed by the authors methodology of analysis of the Russian mutual funds. The aim of this methodology is to find out how attractive they are to investors and if they are able to provide the possibility of obtaining higher returns with less risk than the market in general. The study determines what type of fund management (active or passive) is more optimal. It also explains the effectiveness of focusing on past performance of the funds for making future investments. In addition, the ability of the management companies to repeat their past results is analyzed. Moreover, it is shown if it makes sense to focus on management companies that achieved the best results in the past while making decisions about future investments. These and other results achieved in this article reveal the features of the Russian market of collective investments and allow investors to form more competent policy of mutual funds’ investments. The methodology proposed by the authors is universal. Its application for the analysis of the other markets of collective investments will allow revealing their features.
Research of nonlinear dynamics of finance series has been widely discussed in literature since the 1980s with chaos theory as the theoretical background. Chaos methods have been applied to the S&P 500 stock index, stock returns from the UK and American markets, and portfolio returns. This work reviews modern methods as indicators of nonlinear stochastic behavior and also shows some empirical results for MICEX stock market high-frequency microstructure variables such as stock price
and return, price change, spread and relative spread. It also implements recently developed recurrence quantification analysis approaches to visualize patterns and dependency in microstructure data.
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Econophysics is a relatively new discipline. It is one of the most interesting and promising trends in modeling complex economic systems such as financial markets. In this paper we use the approach of econophysics to explain various mechanisms of price formation in the stock market. We study a model, which was proposed by Jean-Philippe Bouchaud and Dietrich Stauffer (Bouchaud 2002; Chang et al. 2002; Stauffer 2001; Stauffer and Sornette 1990), and used to describe the agents’ cooperation in the market. The most important point of this research is the calibration of the model, using real market conditions to proof the model’s possibility of setting out a real market pricing process
The aim of this paper is to consider some problems with evaluation of the impact of high frequency trading on market liquidity. The first part is devoted to difficulties of disentangling the impact of high frequency on market liquidity from other relevant factors. The remainder of the paper is intended to discuss some issues affecting the evaluation of the influence of high frequency trading on particular aspects of market liquidity.
National Research University – Higher School of Economics (Moscow) and author has been researching the leasing market of Russia for 17 years. According to Leaseurope and author of Russia took the 7-th place in World and 4-th place in Europe after Germany, Britain, France. Particular attention in the article presents the dynamics that characterizes the development of market in the country by value of new contracts, the largest leasing portfolios, calculated author of segmental structure of the leasing market and regional structure. Exploring the structure of financing of leasing operations, the author has developed a new approach to determining leverage leasing projects.
In our research we have made an attempt to partially make up for lack of knowledge about the economy of mutual funds in Russia. Based on financial reports of mutual funds we composed the sample of different characteristics of 709 open and interval unit investment funds for a period 2007-2013. The sample consists of 344 equity, index and commodity market funds, and 365 hybrid, bonds, money market mutual funds and funds of funds. In a given set of 709 mutual funds, 467 mutual funds carried out at the beginning of 2013, 242 funds were eliminated at different times. In the sequel, from the sample was excluded 174 mutual funds with incomplete information, but the remaining sample of funds has remained fairly representative for the econometric studies.
We examine the synergy of the credit rating agencies’ efforts. This
question is important not only for regulators, but also for commercial
banks if the implementation of the internal ratings and the advanced
Basel Approach are discussed. We consider Russian commercial banks
as a good example where proposal methods might be used. Firstly, a
literature overview was supplemented with an analysis of the activities
of rating agencies in Russia. Secondly, we discussed the methods and
algorithms of the comparison of rating scales. The optimization task
was formulated and the system of rating maps onto the basic scale was
obtained. As a result we obtained the possibility of a comparison of
different agencies’ ratings. We discussed not only the distance method,
but also an econometric approach. The scheme of correspondence
for Russian banks is presented and discussed. The third part of the
paper presents the results of econometric modeling of the international
agencies’ ratings, as well as the probability of default models for Russian
banks. The models were obtained from previous papers by the author,
but complex discussion and synergy of their systematic exploration
were this paper’s achievement. We consider these problems using the
example of financial institutions. We discuss the system of models and
their implementation for practical applications towards risk management
tasks, including those which are based on public information and a
remote estimation of ratings. We expect the use of such a systemic
approach to risk management in commercial banks as well as in
The objective of this paper is to find out which banks the Russian households trust more and whether they really prefer to keep their savings in the institutions that they verbally prefer. Russian households traditionally trust state-controlled banks and particularly the national champion (Sberbank) at the expense of privately-owned deposit-taking institutions. The gap in the level of trust between state-controlled banks and all others remains deep and unlikely to disappear. There is little hope in self-sustaining business of private banks that would rest on the inflow of private savings at reasonable rates. The policy implication of this finding is that the authorities will face the dilemma of ever increasing the level of private savings protection under the deposit insurance scheme (as well as the resulting public costs) in order to keep the smaller market participants afloat, or give up on the idealistic drive to artifically enhance competition in the household savings market.
Currently, the venture capital becomes more and more advanced and effective source of the innovation project financing, connected with a high risk level. In the developed countries it plays a key role in transforming innovation projects into successful businesses and creating prosperity of the modern economy. Actually in Russia there are many necessary preconditions for creation of the effective venture investment system: the network of the public institutes for innovation financing operates, there is a significant number of the small and medium-sized enterprises, capable to sell production with good market potential. However the current system does not confirm the necessary level of efficiency in practice that can be substantially explained by the absence of the accurate plan of action to form the national venture model and by the lack of experience of successful venture deals with profitable exits in Russian economy. This paper studies the influence of various factors on the venture industry development by the example of the IT-sector in Russia. The choice of the sector is based on the fact, that this segment is the main driver of the venture capital market growth in Russia, and the necessary set of data exists. The size of investment of the second round is used as the dependent variable. To analyze the influence of the previous round such determinant as the volume of the previous (first) round investments is used. There is also used a dummy variable in regression to examine that the participation of an investor with high reputation and experience in the previous round can influence the size of the next investment round. The regression analysis of short-term interrelations between studied variables reveals prevailing influence of the volume of the first round investments on the venture investments volume of the second round. As a result of the research, the participation of investors with first-class reputation has a small impact on an indicator of the value of investment of the second round. The expected positive dependence of the second round investments on the forecasted market growth rate at the moment of the deal is also rejected. So, the most important determinant of the value of the second-round investment is the value of first–round investment, so it means that the most competitive on the Russian market are the startup teams which can attract more money on the start, and the target market growth is not the factor of crucial importance.
The chapter describes the current state of corporate governance in Russia and the dynamics of recent years. Important features of the environment that affect corporate governance include weak legal institutions that lead to high private benefits to control, underdeveloped capital markets, high levels of ownership concentration and significant state involvement in business. In this situation, the main conflict of interest is not between a manager and a large number of dispersed shareholders, but between large and small shareholders, between different large shareholders, and between minority shareholders and managers/board members in state-owned companies. Many of these features are very similar to other emerging markets, but substantially different from conditions faced by firms in developed countries. Despite substantial improvement during the 2000s, the quality of corporate governance in Russia is still much lower than in developed countries, primarily because of the low quality of Russian institutions.