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The paper illustrates how a Bayesian approach to yield fitting can be implemented in a non-parametric framework with automatic smoothing inferred from the data. It also briefly illustrates the advantages of such an an approach using real data.
The paper uses an infinite dimensional (functional space) approach to inverse problems. Numerical computations are carried out using a Markov Chain Monte-Carlo algorithm with several tweaks to ensure good performance. The model explicitly uses bid-ask spreads to allow for observation errors and provides automatic smoothing based on them.
A non-parametric framework allows to capture complex shapes of zero-coupon yield curves typical for emerging markets. Bayesian approach allows to assess the precision of estimates, which is crucial for some applications. Examples of estimation results are reported for three different bond markets: liquid (German), medium liquidity (Chinese) and illiquid (Russian).
The result shows that infinite-dimensional Bayesian approach to term structure estimation is feasible. Market practitioners could use this approach to gain more insight into interest rates term structure. For example, they could now be able to complement their non-parametric term structure estimates with Bayesian confidence intervals, which would allow them to assess statistical significance of their results.
The model does not require parameter tuning during estimation. It has its own parameters, but they are to be selected during model setup.
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.
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 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.
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.
Puzzling Premiums on FX Markets: Carry Trade, Momentum, and Value Alone and Strategy Diversification.
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.
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.
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.
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.
The paper considers the parametric hedging of non-parallel shifts in the yield curve. In order to determine capital requirements and stress testing, Basel committee recommends taking into account the risk of non-parallel interest rate shifts. (Basel Committee on Banking Supervision, 2016). As of April 2017, only one Russian bank took this risk into account in calculating interest rate risk, and one was developing a methodology (Central bank of Russia, 2017). We use several term structure models for hedging non-parallel interest rate shifts. The study uses a 5-year span of Russian bond market data. We use VaR and MAE to assess the effectiveness of hedging approaches.
The novelty of the work lies in the application of different term structure models, most of which have not previously been used for parametric hedging. We also present an original methodology for assessing the effectiveness of hedging. For the first time a study is conducted on the Russian bond market.
Cross-validation shows that the Nelson-Siegel (and also its shortened version), Svensson and Cox-Ingersoll-Ross models within the parametric hedging problem give better results than the generally accepted Fisher-Weil duration model. The results of this work have practical significance for fixed income managers.