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Regular version of the site
Contacts

119049 Moscow, Russia
11 Pokrovskiy boulevard, room S629

Phone:

+7 (495) 772-95-90*27447, *27947, *27190
+7 (495) 916-88-08 (Master’s Programme Corporate Finance)

- Email: df@hse.ru

finance@hse.ru 

Administration
Head of the School Irina Ivashkovskaya

Head of Corporate Finance Research Center, Dr., tenured professor

Anna Rayn
Administrator Anna Rayn

+7495-772-95-90 (add. 27447)

Tatyana Gennadevna Lipatova
Administrator Tatyana Gennadevna Lipatova

+7495-772-95-90 (add. 27947)

Article
Investment in ESG Projects and Corporate Performance of Multinational Companies

Cherkasova V. A., Nenuzhenko I.

Journal of Economic Integration. 2022. Vol. 37. No. 1. P. 54-92.

Article
Bankruptcy factors at different stages of the lifecycle for Russian companies

Zelenkov Y., Fedorova E.

Electronic Journal of Applied Statistical Analysis. 2022. Vol. 15. No. 1. P. 187-210.

Working paper
Do Non-Interest Income Activities Matter For Banking Sector Efficiency? A Net Interest Margin Perspective

Kolade S. A., Semenova M.

Financial Economics. FE. Высшая школа экономики, 2022. No. WP BRP 87/FE/2022.

Book chapter
Validation of the effectiveness of the bank retail portfolio risk management procedure

Pomazanov M. V.

In bk.: The 8th International Conference on Information Technology and Quantitative Management (ITQM 2020 & 2021): Developing Global Digital Economy after COVID-19. Vol. 199: The 8th International Conference on Information Technology and Quantitative Management (ITQM 2020 & 2021): Developing Global Digital Economy after COVID-19. Manchester: Elsevier, 2022. P. 798-805.

Article
CEO Power and Risk-taking: Intermediate Role of Personality Traits

Korablev D., Poduhovich D.

Journal of Corporate Finance Research. 2022. Vol. 16. No. 1. P. 136-145.

Article
Economic Growth Models and FDI in the CIS Countries During the Period of Digitalization

Olkhovik V., Lyutova O. I., Juchnevicius E.

Научно-исследовательский финансовый институт. Финансовый журнал. 2022. Vol. 14. No. 2. P. 73-90.

Article
Special issue with the 2019 Future Directions in Accounting and Finance Education Conference, Moscow, Russia

Churyk N. T., Anna Vysotskaya, Kolk B. v.

Journal of Accounting Education. 2022. Vol. 58.

Book
Тенденции развития интернета: от цифровых возможностей к цифровой реальности

Абдрахманова Г. И., Васильковский С. А., Вишневский К. О. и др.

М.: Национальный исследовательский университет "Высшая школа экономики", 2022.

Article
Разработка рейтинга проектных рисков для телекоммуникационной компании

Гришунин С. В., Сулоева С. Б., Пищалкина И. И.

Организатор производства. 2022. Т. 30. № 1. С. 60-72.

Article
Разработка механизма гибкого управления рисками в сфере телекоммуникаций

Гришунин С. В., Сулоева С. Б., Пищалкина И. И.

Экономический анализ: теория и практика. 2022. Т. 21. № 3. С. 478-496.

Article
Development of the horizon index to evaluate long-termism of Russian non-financial companies

S. Grishunin, E. Naumova, N. Lukshina et al.

Russian Management Journal. 2021. Vol. 19. No. 4. P. 475-493.

Book chapter
Analysing the Determinants of Insolvency and Developing the Rating System for Russian Insurance Companies

Grishunin S., Bukreeva Alesya, Alyona A.

In bk.: The 8th International Conference on Information Technology and Quantitative Management (ITQM 2020 & 2021): Developing Global Digital Economy after COVID-19. Vol. 199: The 8th International Conference on Information Technology and Quantitative Management (ITQM 2020 & 2021): Developing Global Digital Economy after COVID-19. Manchester: Elsevier, 2022. P. 190-197.

Book
International Conference “Future Directions in Accounting and Finance Education”, 27-28 May 2019, Moscow, Russia

Edited by: А. Б. Высотская, B. v. Kolk.

Vol. 58. Elsevier, 2022.

Article
Prudential policies and systemic risk: The role of interconnections

Karamysheva M., Seregina E.

Journal of International Money and Finance. 2022. Vol. 127.

Article
How do fiscal adjustments work? An empirical investigation
In press

Karamysheva M.

Journal of Economic Dynamics and Control. 2022. Vol. 137.

Article
Do we reject restrictions identifying fiscal shocks? identification based on non-Gaussian innovations

Karamysheva M., Skrobotov A.

Journal of Economic Dynamics and Control. 2022. Vol. 138.

Article
ЛАТИНОАМЕРИКАНСКАЯ ТЕОЛОГИЯ ОСВОБОЖДЕНИЯ: ЭКОНОМИЧЕСКИЕ ПРЕДПОСЫЛКИ, СОСТОЯНИЕ, ОПЫТ ПРАВОСЛАВНОЙ РЕФЛЕКСИИ

Тихомиров Д. В.

Известия Санкт-Петербургского государственного экономического университета. 2022. № 4. С. 144-155.

Book chapter
Students’ Survey: Propensity to Innovate

Evdokimova M., Stepanova A. N.

In bk.: 38th EBES Conference - Program and Abstract Book. Istanbul: EBES, 2022. P. 39.

Article
Prove them wrong: Do professional athletes perform better when facing their former clubs?

Assanskiy A., Shaposhnikov D., Tylkin I. et al.

Journal of Behavioral and Experimental Economics. 2022. Vol. 98.

Article
Black-Litterman model with copula-based views in mean-CVaR portfolio optimization framework with weight constraints

Teplova T., Mikova E., Munir Q. et al.

Economic Change and Restructuring. 2023. Vol. 56. No. 1. P. 515-535.

Article
Институциональные инвесторы, инвестиционный горизонт и корпоративное управление

Повх К. С., Кокорева М. С., Степанова А. Н.

Экономический журнал Высшей школы экономики. 2022. Т. 26. № 1. С. 9-36.

Article
Credit scoring methods: latest trends and points to consider

Anton Markov, Zinaida Seleznyova, Victor Lapshin.

Journal of Finance and Data Science. 2022. Vol. 8. P. 180-201.

Modeling the behavior of retail borrowers of the Bank

On February 14 at the research seminar “Empirical Researches of Bank Activity” School of finance were presented the results of the study Kosarev V.R. postgraduate, School of finance, HSE faculty of Economics: Modeling the behavior of retail borrowers of the Bank

Modeling the behavior of retail borrowers of the Bank

Postgraduate of School of Finance Kosarev Vladislav answered the questions about the content of the study

What input data do you use to predict the borrower's payment behavior?

To predict payment behavior, you need fairly detailed data about the loan, namely the number of payments the client makes in repayment of his loan.

What is the percentage of reliability (accuracy) of prediction of the borrower's payment behavior?

Now the accuracy of prediction is quite modest-45%, such results do not suit anyone, but due to the use of more suitable modelling techniques (finite mixture regression models), they can be improved. In my opinion, the error should be reduced to 20 percent or less.

You offer several ways to apply a prediction of the borrower's payment behavior, and in what direction in your opinion there are the greatest prospects of development? And why?

The first method I told you about - this is an "on the forehead" simulation of the number of payments. There are obvious advantages in it - knowing the number of payments you can get anything you like, incl. accurately calculate the expected cash flow. The disadvantage here is that for the modeling of such a value, standard econometric techniques are not suitable because the distribution is multimodal.

The second is the modeling of the probability that a loan will be paid 0, 1, 2, 3, and so on. In it from the point of view of econometric modeling the situation is ambiguous. On the one hand, it is sufficient to use multinomial regression, but on the other hand it is not clear how much of the payment is limited - how many probabilities should 10 or 50 be modeled?