Trending Mixture Copula Models with Copula Selection

Bingduo Yang, Zongwu Cai, Christian Hafner and Guannan Liu
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Bingduo Yang: Lingnan (University) College, Sun Yat-sen University, Guangzhou, China
Zongwu Cai: Department of Economics, The University of Kansas
Guannan Liu: The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, China

No 201809, WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS from University of Kansas, Department of Economics

Abstract: Modeling the joint tails of multiple nancial time series has important implications for risk management. Classical models for dependence often encounter a lack of fit in the joint tails, calling for additional flexibility. In this paper we introduce a new nonparametric time-varying mixture copula model, in which both weights and dependence parameters are deterministic functions of time. We propose penalized trending mixture copula models with group smoothly clipped absolute deviation (SCAD) penalty functions to do the estimation and copula selection simultaneously. Monte Carlo simulation results suggest that the shrinkage estimation procedure performs well in selecting and estimating both constant and trending mixture copula models. Using the proposed model and method, we analyze the evolution of the dependence among four international stock markets, and find substantial changes in the levels and patterns of the dependence, in particular around crisis periods.

Keywords: Copula; Time-Varying Copula; Mixture Copula; Copula Selection (search for similar items in EconPapers)
JEL-codes: C31 C32 C51 (search for similar items in EconPapers)
Date: 2018-09, Revised 2018-09
New Economics Papers: this item is included in nep-ecm, nep-ore and nep-rmg
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Working Paper: Trending Mixture Copula Models with Copula Selection (2018)
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