TY - JOUR
T1 - A comparison of some univariate models for Value-at-Risk and expected shortfall
AU - Marinelli, Carlo
AU - D'Addona, Stefano
AU - Rachev, Svetlozar T.
N1 - Funding Information:
C. Marinelli acknowledges the hospitality and financial support of IMPAN, Warsaw and IHÉS, Bures-sur-Yvette, through an IPDE fellowship. S. T. Rachev gratefully acknowledges research support by grants from the Division of Mathematical, Life and Physical Sciences, College of Letters and Science, University of California, Santa Barbara, the German Research Foundation (DFG) and the German Academic Exchange Service (DAAD).
PY - 2007/9
Y1 - 2007/9
N2 - We compare in a backtesting study the performance of univariate models for Valueat-Risk (VaR) and expected shortfall based on stable laws and on extreme value theory (EVT). Analyzing these different approaches, we test whether the sum-stability assumption or the max-stability assumption, that respectively imply α-stable laws and Generalized Extreme Value (GEV) distributions, is more suitable for risk management based on VaR and expected shortfall. Our numerical results indicate that α-stable models tend to outperform pure EVT-based methods (especially those obtained by the so-called block maxima method) in the estimation of Value-at-Risk, while a peaks-over-threshold method turns out to be preferable for the estimation of expected shortfall. We also find empirical evidence that some simple semiparametric EVT-based methods perform well in the estimation of VaR.
AB - We compare in a backtesting study the performance of univariate models for Valueat-Risk (VaR) and expected shortfall based on stable laws and on extreme value theory (EVT). Analyzing these different approaches, we test whether the sum-stability assumption or the max-stability assumption, that respectively imply α-stable laws and Generalized Extreme Value (GEV) distributions, is more suitable for risk management based on VaR and expected shortfall. Our numerical results indicate that α-stable models tend to outperform pure EVT-based methods (especially those obtained by the so-called block maxima method) in the estimation of Value-at-Risk, while a peaks-over-threshold method turns out to be preferable for the estimation of expected shortfall. We also find empirical evidence that some simple semiparametric EVT-based methods perform well in the estimation of VaR.
KW - Expected shortfall
KW - Extreme value theory
KW - Paretian stable laws
KW - Value-at-Risk
UR - http://www.scopus.com/inward/record.url?scp=34848829142&partnerID=8YFLogxK
U2 - 10.1142/S0219024907004548
DO - 10.1142/S0219024907004548
M3 - Article
AN - SCOPUS:34848829142
SN - 0219-0249
VL - 10
SP - 1043
EP - 1075
JO - International Journal of Theoretical and Applied Finance
JF - International Journal of Theoretical and Applied Finance
IS - 6
ER -