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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

Manager Uliana Nepryakhina

+7 495-772-95-90 (add. 27190)

Senior Administrator Olesya Galyanina

+7 495-772-95-90 (add. 27447)

Administrator Tatyana Lipatova

+7 495-772-95-90 (add. 27947)

Administrator Irina Skobeleva

+7 495-772-95-90 (add. 27946)

Article
Resilience Index Development for Digital Ecosystems and Its Implementation: The Case of Russian Companies

Grishunin S., Ivashkovskaya I., Brendeleva N. et al.

Journal of Corporate Finance Research. 2025. Vol. 19. No. 1. P. 25-40.

Book chapter
Beyond Claims: CSR Reports, ESG Initiatives, and the Consequences of Impressions Management; Empirical Analysis

Badr I., Rawnaa Ibrahim, Hussainey K.

In bk.: Opportunities and Risks in AI for Business Development. Vol. 2: Opportunities and Risks in AI for Business Development. Prt. 636. Springer, 2025. P. 385-399.

Working paper
A New Approach to Identifying Political Connections: Evidence from the Russian Banking Sector

Kozlov N., Semenova M.

Financial Economics. WP HSE. HSE University, 2025. No. 1/FE/2025.

Research Seminar «Empirical Research in Corporate Finance»

Event ended

29/03/2022 16:00  online Research Seminar «Empirical Research in Corporate Finance»


Ella Khromova
, Lecturer of the School of Finance: «Prediction synergy of credit ratings and probability of default models».

 

ABSTRACT: The research 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. The paper demonstrates that rating models, if applied alone, tend to overestimate credit risk of a bank, whereas probability of default models give underestimated results. As a result of the assignment of optimal weights and monotonic transformations to these models, the new synergic model of banks’ credit risks with higher forecasting power was obtained. The research broadens the scope of the PhD thesis towards sophistication of separate models that improves the synergy's model forecasts. The new branches include comparative analysis of Russian and international banks as well as an analysis of COVID-19 effects.

Zoom

Conference ID: 860 2082 4430

Access code: 578429

Webinar (in case of Zoom issues)