Minimum capital requirements for banks in market risk: The challenge of a shift from value at risk to expected shortfall risk measure
MetadataShow full item record
Financial Institutions today are, more than ever before, subject to various types of risks which shareholders, investors and regulators expect to be timely and accurately evaluated in order to prevent financial crises. Market Risk has become one of the most important risk sources for Financial Institutions and Basel Committee on Banking Supervision Accords have been evolved to take into account lessons from the past. This Thesis analyzes Expected Shortfall, the new risk measure introduced by BCBS in a recent paper (Fundamental Review of the Trading Book, 2012) in order to capture ‘tail risk’ more effectively. Various models for Value at Risk and Expected Shortfall estimation are presented and evaluated by backtesting techniques in two separate periods, representing US subprime loan crisis and after crisis market conditions respectively, for a univariate equity portfolio, using data of S&P index returns. The findings show that parametric methods like normal and t distributions as well as the non parametric model of historical simulation fail to produce reliable VAR and Expected Shortfall estimates for the crisis period, as they do not respond timely in growing market volatility. Contrary to these results, econometric models capturing volatility dynamics, represented by an EGARCH model, seem to perform best. For this kind of models, Expected Shortfall and VAR estimation and backtesting results indicate that these models could have acted proactively in the beginning of the US subprime loan crisis, determining reliable and accurate market risk limits and equivalent capital requirements. This conclusion becomes very important for future revisions of the BCBS framework, as the vast majority of banks adapt the simple but inefficient method of Historical Simulation for the calculation of their Market Risk capital requirements (ΕΒΑ Report, 2017: 31, Perignon&Smith, 2009: 367). Contrary to that, the EGARCH model fails to produce reliable risk measure estimates in a low volatility, tranquil market condition.