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Asymmetric volatility of the Thai stock market: evidence from high-frequency data

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  • Thakolsri, Supachok
  • Sethapramote, Yuthana
  • Jiranyakul, Komain

Abstract

This study employs the daily data of the Stock Exchange of Thailand to test for the leverage and volatility feedback effects. The period of investigation is during January 4, 2005 to December 27, 2013, which includes the Subprime crisis period in the US that might affect the volatility of stock market return in emerging stock markets. The results from this study show that the US subprime crisis imposes a minimal positive impact on volatility. In addition, the estimations of the three parametric asymmetric volatility models give the results showing some evidence of the volatility feedback and leverage effects. The findings give implications for portfolio diversification and risk management.

Suggested Citation

  • Thakolsri, Supachok & Sethapramote, Yuthana & Jiranyakul, Komain, 2015. "Asymmetric volatility of the Thai stock market: evidence from high-frequency data," MPRA Paper 67181, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:67181
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    References listed on IDEAS

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    2. Kumar SANTOSH & Meher Kumar BHARAT & Ramona BIRAU & Mircea Laurentiu SIMION & Anand ABHISHEK & Singh MANOHAR, 2023. "Quantifying Long-Term Volatility for Developed Stock Markets: An Empirical Case Study Using PGARCH Model on Toronto Stock Exchange (TSX)," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 2, pages 61-68.

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    More about this item

    Keywords

    Asymmetric volatility; feedback effect; leverage effect; emerging stock market;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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