Research on Portfolio Risk Prediction Based on Copula-GJR-Skewt Model

DOI

10.2991/etmhs-15.2015.73How to use a DOI?

Keywords

Copula; GJR-Skewt; Portfolio Risk; Prediction

Abstract

For risk prediction of diversified investment portfolio, we use the thick tail and the biased characteristics of GJR-Skewt model to depict a single asset and using Copula model to depict a diversified investment portfolio non-linear correlation structure, simulating the random distribution of financial assets with Monte Carlo method and combining with rolling time window method to conduct the sample dynamic forecast for the future portfolio risk. The empirical results show that Copula-GJR-Skewt model can achieve satisfactory results of predicting the risk of asset returns. For the VaR forecast performance, we use the GJR-Skewt model as the edge distribution functions and even if there is a system error, it can also achieve optimal prediction.

Copyright

© 2015, 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  - Xiangqing Wei
PY  - 2015/03
DA  - 2015/03
TI  - Research on Portfolio Risk Prediction Based on Copula-GJR-Skewt Model
BT  - Proceedings of the 2015 International Conference on Education Technology, Management and Humanities Science
PB  - Atlantis Press
SP  - 316
EP  - 319
SN  - 2352-5398
UR  - https://doi.org/10.2991/etmhs-15.2015.73
DO  - 10.2991/etmhs-15.2015.73
ID  - Wei2015/03
ER  -