Abstract
The aim of this paper is to propose smooth transition (ST) copula as new model to capture nonlinear or two regimes dependence structure between emerging and advanced stock markets, and compare the performance of ST copula with Markov-Switching (MS) copula and traditional copula. The data consists of two sets of stock markets, namely five emerging stock markets: China, India, Brazil, Indonesia, and Turkey, and two advanced stock markets: United Kingdom and United States of America. The results show that ST student-t copula for two-regime dependent structure outperforms MS copula, and one regime copula. Thus, ST copula is more appropriate model for the dependence structure between emerging and advanced stock markets.
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This research work was partially supported by Chiang Mai University and Faculty of Economics Chiang Mai University.
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Tansuchat, R., Yamaka, W. (2019). Nonlinear Dependence Structure in Emerging and Advanced Stock Markets. In: Seki, H., Nguyen, C., Huynh, VN., Inuiguchi, M. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2019. Lecture Notes in Computer Science(), vol 11471. Springer, Cham. https://doi.org/10.1007/978-3-030-14815-7_18
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