The Empirical Performance of TXO Sell Strangle StrategiesThe Empirical Performance of TXO Sell Strangle Strategies

碩士 === 國立高雄應用科技大學 === 金融資訊研究所 === 98 ===   We discuss the return of Sell Strangle strategies based on exercise price ranges with different degrees of out of the money by separating the exercise prices into asymmetric price range and symmetric one. Which of performance of the Sell Strangle strategies...

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Bibliographic Details
Main Authors: Chung-Yu Yeh, 葉仲玉
Other Authors: Yen-Shin Cheng
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/69886900821652607831
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Summary:碩士 === 國立高雄應用科技大學 === 金融資訊研究所 === 98 ===   We discuss the return of Sell Strangle strategies based on exercise price ranges with different degrees of out of the money by separating the exercise prices into asymmetric price range and symmetric one. Which of performance of the Sell Strangle strategies with holding to maturity, hedge, and hedge and stopping profit is the optimal? We adopt Sharpe ratio, Sortino ratio, and UP ratio to measure performance. In additional, we also drive the conditional expected return model of Sell Strangle option under risk neutral approach. Further, our study analyzes by Stepwise Regression to discuss the facts would impact the return of the Sell Strangle strategy. Moreover, we compare performance of Sell Strangle and Guts which is better.   The empirical evidence, resulting from comparing strategy of the asymmetric price range with of the symmetric, exhibits that the return of the asymmetric price range where calls run out of the money deeper is the highest, of the symmetric price range is the secondary, and of the asymmetric price range where puts run out of the money deeper is the lowest. Next, we find that the strategy with holding to maturity would display a weakest performance; according to a slightly improved performance across 25% stopping profit and hedge, our study suggests necessary stopping loss and profit for investors. Further more, the result of stepwise regression via the conditional expected return model which we drive in this paper is that the coefficient is positive and significantly affects the actual return. Due to out of the sample with less mean squared error, we discuss our model enables to forecast effectively. And then, we find the performance to select the good timing is better. Final, the performance of Sell Guts is better than Sell Strangle.