選擇權市場資訊與股票報酬的兩篇論文

Abstract

隱含在選擇權交易活動中的資訊一直以來都是研究人員以及交易員關注的重要議題。本論文建基在大量有關於隱含波動率和選擇權或者股票交易量對未來股票報酬有影響的文獻上，從隱含波動率和交易量兩個不同的角度出發，嘗試找到過去文獻未發現的不同或者額外的資訊，並使其能夠成為可以在現實當中應用的投資訊號。 Stochastic Volatility Inspired (SVI) 模型是由五個參數所構成，每個參數都代表著對於隱含波動度曲線不同的影響，例如隱含波動度曲線的曲度、水平位置以及開口方向。SVI模型可以很好的擬合指數選擇權的隱含波動度曲線，並且相較於三個參數的Zhang–Xiang模型，SVI模型的五個參數讓我們能夠對隱含波動度曲線進行更廣泛的分析。因此，在第二章，我利用由所有個股選擇資料建構的SVI 模型，檢驗其對於未來股票報酬的預測能力，以及是否含有額外的市場訊息。 Option-to-stock trading volume (O/S) ratio或put call trading volume (P/C) ratio的資訊內含已經被廣泛的討論，然而多數的文獻只關注在個股和選擇權的交易量，或是基於不同選擇權價性 (option moneyness) 對於股票市場的影響，很少探討同時考慮所有的選擇權價性的影響。因此，在第三章，我利用一個由個股交易量、選擇權交易量以及選擇權價性所購成的moneyness option-to-stock trading volume ratio (MOS)指標，並檢驗其與選擇權隱含波動度之間的相互關係以及對於股票市場的影響。 最後，結果顯示SVI不僅可以被應用在擬合指數選擇權的隱含波動度曲線，也可以應用在個股選擇權，此外，以SVI模型的參數ρ或者以MOS和隱含波動度組合變數建構的資產組合可以產生顯著的報酬。

What kind of information embedded in option market trading activities has been a critical issue for researchers and traders for a long time. This dissertation is rooted in a rich strand of existing literature about the impacts of implied volatilities and option and/or stock trading volume on future stock returns. I start from two different perspectives, trading volume and implied volatilities, and attempt to find indicators that contain different or additional information compared to those documented in the literature and that can be implemented as investment signals in real world. The SVI model is a parametric model with five parameters, each of which represents different changes in the shape of the implied volatility curve, such as curvature, horizontal position, and opening direction of the curve. The SVI model has been shown to impressively fit the implied volatility curve of index options, and is chosen for its parameters’ abilities to capture different styles of changes in the implied volatility curve and provide a broader analysis of the implied volatility curve, compared to the Zhang–Xiang model, which has only three parameters. Thus, in Chapter 2, I apply the Stochastic Volatility Inspired (SVI) model, which considers all individual stock option data, to examine whether it demonstrates the predictive ability for future one-month stock returns and contain additional information in the option market. The information content of the option-to-stock trading volume ratio (O/S) or put call trading volume ratio (P/C), widely discussed in the literature, is another important channel for reflecting private information. However, most previous research focuses merely on trading volumes in options and stocks or examines the impact based on specific degrees of moneyness but not the entire range of moneyness. Thus, in Chapter 3, I manage the moneyness option-to-stock trading volume ratio (MOS) measures, which incorporate information regarding the entire option moneyness into the O/S ratio, to examine their interaction effect with the option trading volume and implied volatilities on the stock market. Finally, the excellent fitting performance of the SVI model demonstrates that it can be applied not only for index options but also for individual stock options. Interaction effects are found between the MOS measures and average implied volatilities, showing the amplifying effect on future one-week stock return. Moreover, I also suggest that the SVI parameter ρ_put and the combined variable PutMOSxIV_Put can be treated as trading signals in the real world, as they can generate substantial profits—especially the latter.