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Terence Tai-Leung Chong, Yue Ding and Tianxiao Pang
 
''Extreme Risk Value and Dependence Structure of the China Securities Index 300''
( 2017, Vol. 37 No.1 )
 
 
A time-varying copulas–conditional value at risk (CVaR) model is estimated to analyze the extreme risk value and dependence structure of the China Securities Index 300 (CSI 300) and index futures portfolios. The goodness-of-fit test as well as the in-sample and out-of-sample tests show that time-varying copulas outperform constant copulas. Specifically, the Student's t, normal, Plackett, and the rotated Gumbel copulas outperform the rotated Clayton copulas.
 
 
Keywords: CVaR model, Time-varying copulas
JEL: C2 - Single Equation Models; Single Variables: General
 
Manuscript Received : Apr 06 2016 Manuscript Accepted : Mar 20 2017

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