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Relationship of the Change in Implied Volatility with the Underlying Equity Index Return in Thailand

Author

Listed:
  • Supachok Thakolsri

    (Public Enterprise Policy Office, Ministry of Finance, Bangkok, Thailand)

  • Yuthana Sethapramote

    (School of Development Economics, National Institute of Development Administration, Bangkok, Thailand)

  • Komain Jiranyakul

    (School of Development Economics, National Institute of Development Administration, Bangkok, Thailand)

Abstract

In this study, we examine the relationship between the change in implied volatility index and the underlying stock index return in the Thai stock market. The data used are daily data during November 2010 to December 2013. The regression analysis is performed on stationary series. The empirical results reveal that there is evidence of significantly negative and asymmetric relationship between the underlying stock index return and the change in implied volatility. In addition, the size effect of the underlying stock index return and the one-period lagged implied volatility change also affect the change in implied volatility. The finding in this study gives implication for risk management.

Suggested Citation

  • Supachok Thakolsri & Yuthana Sethapramote & Komain Jiranyakul, 2016. "Relationship of the Change in Implied Volatility with the Underlying Equity Index Return in Thailand," Economic Research Guardian, Weissberg Publishing, vol. 6(2), pages 74-86, December.
    • Handle: RePEc:wei:journl:v:6:y:2016:i:2:p:74-86
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    References listed on IDEAS

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    1. Jeff Fleming & Barbara Ostdiek & Robert E. Whaley, 1995. "Predicting stock market volatility: A new measure," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 15(3), pages 265-302, May.
    2. George Skiadopoulos, 2004. "The Greek implied volatility index: construction and properties," Applied Financial Economics, Taylor & Francis Journals, vol. 14(16), pages 1187-1196.
    3. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    4. Siriopoulos, Costas & Fassas, Athanasios, 2012. "An investor sentiment barometer — Greek Implied Volatility Index (GRIV)," Global Finance Journal, Elsevier, vol. 23(2), pages 77-93.
    5. Supachok Thakolsri & Yuthana Sethapramote & Komain Jiranyakul, 2016. "Implied Volatility Transmissions Between Thai and Selected Advanced Stock Markets," SAGE Open, , vol. 6(3), pages 21582440166, July.
    6. Bart Frijns & Christian Tallau & Alireza Tourani‐Rad, 2010. "The information content of implied volatility: Evidence from Australia," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(2), pages 134-155, February.
    7. Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
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    More about this item

    Keywords

    Equity index return; Option prices; Implied volatility; Asymmetric effect;
    All these keywords.

    JEL classification:

    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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