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Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment

Author

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  • Her-Jiun Sheu
  • Yu-Chen Wei

Abstract

Using options price data on the Taiwanese stock market, we propose an options trading strategy based on the forecasting of volatility direction. The forecasting models are constructed with the incorporation of absolute returns, heterogeneous autoregressive-realized volatility (HAR-RV), and proxy of investor sentiment. After we take into consideration the margin-based transaction costs, the results of our simulated trading indicate that a straddle trading strategy that considers the forecasting of volatility direction with the incorporation of market turnover achieves the best Sharpe ratios. Our trading algorithm bridges the gap between options trading, market volatility, and the information content of investor overreaction.

Suggested Citation

  • Her-Jiun Sheu & Yu-Chen Wei, 2011. "Options Trading Based on the Forecasting of Volatility Direction with the Incorporation of Investor Sentiment," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(2), pages 31-47, March.
    • Handle: RePEc:mes:emfitr:v:47:y:2011:i:2:p:31-47
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    Citations

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    Cited by:

    1. Kelvin Mutum, 2020. "Volatility Forecast Incorporating Investors’ Sentiment and its Application in Options Trading Strategies: A Behavioural Finance Approach at Nifty 50 Index," Vision, , vol. 24(2), pages 217-227, June.
    2. Tseng‐Chan Tseng & Hung‐Cheng Lai & Jih‐Kuang Chen, 2022. "Impacts of relatively rational and irrational investor sentiment on realized volatility," Asian Economic Journal, East Asian Economic Association, vol. 36(4), pages 458-478, December.
    3. Chunpeng Yang & Bin Gao & Jianlei Yang, 2016. "Option pricing model with sentiment," Review of Derivatives Research, Springer, vol. 19(2), pages 147-164, July.
    4. Atilgan, Yigit & Demirtas, K. Ozgur & Simsek, Koray D., 2016. "Derivative markets in emerging economies: A survey," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 88-102.

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