Ranking of Parametric Value at Risk Models with Consideration of Trader Position (Application of Asymmetric Distribution Functions in GARCH Models)

Heidari, Hadi; K. Haddad, GholamReza

doi:10.22054/joer.2017.8205

Document Type : Research Paper

Authors

Hadi Heidari ¹
GholamReza K. Haddad ²

¹ PhD Candidate, Graduate School of Management and Economics, Sharif University

² GSME, Sharif University of Technology

https://doi.org/10.22054/joer.2017.8205

Abstract

In this paper, we estimate the value at risk of Tehran stock exchange (TSE) index by using GARCH family models in short and long trading positions. Because of asymmetric behavior of returns for long and short positions in TSE, for enhanced accuracy of model, we apply asymmetric normal and t-student distribution functions. By developing Sener et. al (2012) measurement for considering trading positions in performance assessment of parametric models, we show that EGARCH and GJRGARCH models with asymmetric normal and t-student distribution functions are more accurate than other models. Also complementary forecast ability test explain that, with a benchmark model such as GJRGARCH, other models do not have equal mean error, so the asymmetric distribution functions in EGARCH and GJRGARCH models improve their ranks.

Keywords

References

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Economics Research

Ranking of Parametric Value at Risk Models with Consideration of Trader Position (Application of Asymmetric Distribution Functions in GARCH Models)

References

References

Volume 17, Issue 66
October 2017
Pages 151-178

Ranking of Parametric Value at Risk Models with Consideration of Trader Position (Application of Asymmetric Distribution Functions in GARCH Models)

References

References

Volume 17, Issue 66October 2017Pages 151-178

Volume 17, Issue 66
October 2017
Pages 151-178