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The Dependence Structure and Portfolio Optimization in Economic Cycles: An Application in ASEAN Stock Market

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11471))

Abstract

Investigation is made on the dependence structure of ASEAN stock markets, including Thailand, Indonesia, Malaysia, the Philippines, Vietnam and Singapore. Technically, data is divided into boom and recession periods during 2008–2017. The econometric tools employed for the analysis are the Markov-Switching model (MS-model), D-vine trees and Markowitz Portfolio selection model. Empirically, the results of MS-model prescribe 649 and 1,600 stock trading days in the ASEAN stock markets for the bull and the recession period, respectively. Second, the findings of the relationship among ASEAN stock markets show that there are strongly positive dependent structures in bull period. On the other hand, in the bear periods, Vietnam stock market has the negative relation among stock markets in ASEAN countries. Third, the empirical results from the Markowitz portfolio selection indicated that the choice to minimize risk value in the bull period is more efficient than to maximize the return. The proportion to invest in this period is to invest Singapore that is the sensible choice to make the investment. Conversely, the best alternative way in recession period is to maximize return, and the diversification investment is more suitable to get lower risks since their dependent structure has the negative connection.

Supported by Puay Ungpakoyn Centre of Excellence in Econometrics, Faculty of Economics, Chiangmai University.

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Correspondence to Jittima Singvejsakul .

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Singvejsakul, J., Chaiboonsri, C., Sriboonchitta, S. (2019). The Dependence Structure and Portfolio Optimization in Economic Cycles: An Application in ASEAN Stock Market. 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_14

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  • DOI: https://doi.org/10.1007/978-3-030-14815-7_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-14814-0

  • Online ISBN: 978-3-030-14815-7

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