Construction and Backtesting of a Multi-Factor Stress-Scenario for the Stock Market

Kirill Boldyrev, Dmitry Andrianov, and Sergey Ivliev

Abstract Nowadays stress-testing is a popular framework for the analysis of the financial stability of different markets’ institutes and objects. This work proposes a new approach to trading book stress-testing by building price paths based on generalized autoregressive conditional the heteroskedasticity (GARCH) model with Pareto distribution for the random fluctuation of prices and t-copula for describing the dependency structure between factors.

Keywords Copula theory • Extreme value theory • GARCH • Pareto distribution • Stress-testing • Stylized facts

JEL Classification C49, G17

1 Introduction

Stress-testing is a set of various techniques which allows the gauging of an institute’s vulnerability to “severe, but plausible” events (Basel Committee on Banking Supervision 2009). Nowadays most interest in this comes not from financial market participants, but from regulators. The recent crisis shows that risk estimation methods have to be more flexible and versatile if we would like to see the real picture (Sorge 2004). We have to take into account not only of large single events which shock a situation, but also of their aftermath. Therefore we should consider the dynamics of the market’s conditions, and stress-testing allows us to do that.

This paper provides an approach to the stress-testing of a trading portfolio. As a test portfolio for consideration we use the MICEX-10 index, which includes major Russian blue chip stocks (HYDR, GMKN, VTBR, ROSN, GAZP, SNGS, URKA, LKOH, SBERP, SBER). The proposed approach is based on two models: the risk factors evolution model and the risk factors interrelation model.

K. Boldyrev (H) • D. Andrianov • S. Ivliev

Department of Economics, Perm State National Research University, Perm, Russia e-mail: boldyrev@prognoz. ru

© Springer International Publishing Switzerland 2015 37

A. K. Bera et al. (eds.), Financial Econometrics and Empirical Market Microstructure, DOI 10.1007/978-3-319-09946-0 4

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