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Modeling and forecasting Hang Seng index volatility with day-of-week effect, spillover effect based on ARIMA and HAR

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Listed:
  • Yanhui Chen
  • Kin Lai
  • Jiangze Du

Abstract

This paper investigates whether implied volatility index can be predicted and whether the prediction of implied volatility index can improve option trading performances by checking Hang Seng Index Volatility (VHSI). The results indicate that VHSI can be predicted more accurately when considering day-of-week effect and spillover effect. Furthermore, this paper uses straddle to examine the trading performance with the real data from Hong Kong option trading market. The results suggest that option trading based on the prediction of VHSI can generate extra returns, and model specifications with day-of-week and spillover effects perform better than ones without these two effects. The results also suggest that the prediction of VHSI adds value to practical investors. Copyright Eurasia Business and Economics Society 2014

Suggested Citation

  • Yanhui Chen & Kin Lai & Jiangze Du, 2014. "Modeling and forecasting Hang Seng index volatility with day-of-week effect, spillover effect based on ARIMA and HAR," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 113-132, December.
    • Handle: RePEc:spr:eurase:v:4:y:2014:i:2:p:113-132
    DOI: 10.1007/s40822-015-0013-x
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    References listed on IDEAS

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    More about this item

    Keywords

    Implied volatility index; VHSI; ARIMA; HAR; Day-of-week effect; Spillover effect; C53; G17;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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