Stress-Testing Model for Corporate Borrower Portfolios
Vladimir Seleznev, Denis Surzhko, and Nikolay Khovanskiy
Abstract Despite the significant attention to the stress-testing issues in finances world-wide, the ways of quantitative assessment of the stress impact on the portfolios of non-public (in the absence of equity or debt market quotes) corporate borrowers are currently not sufficiently developed or standardized. The aim of this article is to propose high-level universal requirements to the quantitative models of stress-testing of non-public corporate borrower portfolios, and to describe the model, developed by the authors, which meets such requirements. Details of the model’s calibration, implementation (using Monte-Carlo simulations) and some practical issues are covered in the article.
Keywords Credit risk • Quantitative risk assessment • Stress-testing
Stress-testing has become one of the most important risk-management instruments worldwide. Despite the increasing interest in this subject, currently the problem of constructing stress-testing models for credit portfolios of non-public companies (further—stress-testing models) is covered by research and regulatory papers only fragmentarily and usually at a very high-level. Therefore, the main goals of this article are to formulate clear overall requirements for quantitative stress-testing models, and to propose one of the possible practical implementations of those requirements based on the modification of the Vasicek model—the model that underpins current international capital requirements (IRB approaches of Basel II—III).
According to our view, a quantitative stress-testing model for a portfolio of nonpublic corporate borrowers should fulfill the following requirements:
1. The approach should not be based only on default event modeling, but the model should also produce estimates of the changes in the portfolio rating structure.
V. Seleznev • D. Surzhko (H) • N. Khovanskiy OJSC VTB Bank, Moscow, Russia e-mail: SurzhkoDA@msk. vtb. ru
© Springer International Publishing Switzerland 2015
A. K. Bera et al. (eds.), Financial Econometrics and Empirical Market
Microstructure, DOI 10.1007/978-3-319-09946-0_____ 19
This will allow us to estimate potential losses (due to defaults) and RWA-changes (rating migrations) simultaneously and consistently.
2. Historical experience shows that concentration of credit risk in asset portfolios has been one of the major causes of bank distress; therefore the model should take into account concentration risks and correlation between default events.
3. The model should be based on the functional dependence between the defaults and dynamics of macro-variables. This property will allow us to model both potential losses based on real historical experience and losses based on hypothetical but plausible scenarios (produced by macro forecasters). Moreover, this property extends the scope of possible validation procedures, because the model could estimate losses during stress as well as expansion scenarios of economic development.
4. The model should allow us to estimate the marginal contribution of a single borrower to the stress-test results. Therefore, we could determine particular borrowers that are the main source of losses in a stress environment (potentially, it could be taken into account during risk-based pricing).
5. The approach should be universal; for example, it should allow us to make a consistent and transparent transformation of the stress-testing model into a portfolio model. This property will allow us to make a consistent comparison between stress-testing results and economic capital estimates. Moreover, it significantly reduces model development team efforts and increases the scope of possible validation procedures.