Effective options trading strategies based on volatility forecasting recruiting investor sentiment

Authors:
Her-Jiun Sheu;Yu-Chen Wei
Affiliations:
Department of Banking and Finance and President, National Chi Nan University, 1, University Rd., Puli, Nantou 54561, Taiwan, ROC;Department of Management Science, National Chiao Tung University, 1001, University Rd., Hsinchu 300, Taiwan, ROC and Finance Department, Ming Chuan University, 250, Zhong Shan N. Rd., Sec. 5, Shih ...
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

This study investigates an algorithm for an effective option trading strategy based on superior volatility forecasts using actual option price data for the Taiwan stock market. The forecast evaluation supports the significant incremental explanatory power of investor sentiment in the fitting and forecasting of future volatility in relation to its adversarial multiple-factor model, especially the market turnover and volatility index which are referred to as the investors' mood gauge and proxy for overreaction. After taking into consideration the margin-based transaction cost, the simulated trading indicates that a long or short straddle 15days before the options' final settlement day based on the 60-day in-sample-period volatility forecasting recruiting market turnover achieves the best average monthly return of 15.84%. This study bridges the gap between option trading, market volatility, and the signal of the investors' overreaction through the simulation of the option trading strategy. The trading algorithm based on the volatility forecasting recruiting investor sentiment could be further applied in electronic trading and other artificial intelligence decision support systems.