Systematic VaR model based on multi-resolution  analysis and extreme value theory

doi:10.3969/j.issn.0253-2778.2016.11.008

Abstract

Abstract: In order to capture time-varying features of volatility of asset price, multi-resolution analysis (MRA) was used to decompose financial returns into orthogonal components in different time domains. For each component, a certain ARMA-GARCH model was built. Extreme value theory (EVT) was then introduced so as to model the fat-tail of financial returns, and an MRA-EVT model was constructed. Finally, the proposed model was applied to predict VaR of CSI 300 index, and compared with traditional models, such as ARMA-GARCH model, unconditional EVT model and MRA model. Empirical results show that the MRA-EVT model significantly improves the accuracy of VaR estimation.

Key words: multi-resolution analysis, GARCH model, EVT, VaR

CLC Number:

F830.

WANG Chuanhao, FANG Zhaoben, HAN Yu. Systematic VaR model based on multi-resolution analysis and extreme value theory[J]. Journal of University of Science and Technology of China, 2016, 46(11): 928-938.

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Systematic VaR model based on multi-resolution analysis and extreme value theory

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