A Non-Gaussian Approach to Risk Measures

Details A Non-Gaussian Approach to Risk Measures A Non-Gaussian Approach to Risk Measures

2006-05-17

arxiv.org/abs/physics/0605146v2

Physica A, 376 (2007) p. 532-542

Physics

Physics and Society

Latex 15 pages, 3 figures and 5 tables 68% c. levels for tail exponents corrected, conclusions unchanged

Scientific paper

10.1016/j.physa.2006.10.008

Reliable calculations of financial risk require that the fat-tailed nature of prices changes is included in risk measures. To this end, a non-Gaussian approach to financial risk management is presented, modeling the power-law tails of the returns distribution in terms of a Student-t distribution. Non-Gaussian closed-form solutions for Value-at-Risk and Expected Shortfall are obtained and standard formulae known in the literature under the normality assumption are recovered as a special case. The implications of the approach for risk management are demonstrated through an empirical analysis of financial time series from the Italian stock market and in comparison with the results of the most widely used procedures of quantitative finance. Particular attention is paid to quantify the size of the errors affecting the market risk measures obtained according to different methodologies, by employing a bootstrap technique.

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