Option price forecasting and trading strategy with preset return

• Main Authors: PING-CHEN TSENG, 曾炳誠
• Other Authors: Nen-Jing chen
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/38472229942159818451

碩士 === 輔仁大學 === 經濟學研究所 === 93 === This study analyses the performance of a preset return options trading strategies. The investor is assumed to hold one call option and adjust the put option position based on the option price forecast or theta forecast. Under the former strategy, the option price of KOSPI 200 stock price index is forecasted by gene algorithm and back propagation neural network model. Two forecasting models are set up and compared. Six parameters of Black-Scholes (1973) option pricing model are selected as the input of neural network model. The better forecasting model is chosen to forecast the option price of the nearby contract and second nearby contract. Under the latter strategy, the theta value from the Black and Scholes (1973) model is estimated. The put option position can be buy straddles or reversals. Finally, the portfolio return associated with the two strategies is calculated and compared. This study also considers strategy with a max loss constraint. The empirical results indicate that if the investors don’t limit maximum loss, they can adopt the forecasting price strategy for nearby options with 1<X/S<1.03. If the investors limit max loss, they can adopt the forecasting theta strategy for nearby options with 0.94>X/S. For second nearby contract portfolios, no matter the investors limit their maximum loss or not, they can only invest in option with 0.97<X/S<1, and the forecasting theta strategy is better than the forecasting price strategy. In respect of the seasonal performance of the strategy, no matter nearby or second nearby portfolios, the fourth seasons is the best for the investment strategy designed in this study.