The Empirical Comparison of Risk Models in Estimating Value at Risk and Expected Shortfall

DOI

10.2991/assehr.k.201202.116How to use a DOI?

Keywords

Value at Risk, Expected Shortfall, Back-test, Violation Ratio, Risk Model

Abstract

Risk measurement is the core content of risk management which is one of the three pillars of modern finance research. Value at risk model is the main model to depict risks of financial time series. This paper analyzes empirically the non-parametric and parametric methods to forecast Value at risk and Expected shortfall by the Dow Jones Industrial Index under the confidence level of 99%, 95% respectively, and make back-test on different models’ result by Bernoulli coverage test and independence coverage test to make comparison of their applicability. The empirical analysis result is as follow: EVT is best for rare events, EWMA and GARCH are preferred for observed volatility clustering and historical simulation is most suitable for simplicity.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yanan Wang
PY  - 2020
DA  - 2020/12/03
TI  - The Empirical Comparison of Risk Models in Estimating Value at Risk and Expected Shortfall
BT  - Proceedings of the Second International Symposium on Management and Social Sciences (ISMSS 2020)
PB  - Atlantis Press
SP  - 192
EP  - 199
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.201202.116
DO  - 10.2991/assehr.k.201202.116
ID  - Wang2020
ER  -