以 Stochastic Volatility Inspired 模型為基礎的隱含波動度曲線來預測資產報酬

Abstract

不少文獻說明隱含波動度偏斜和買賣權波動度的差異對於股票未來報酬的預測性。本研究試圖利用 Stochastic Volatility Inspired 隱含波動率曲線改善利用特定執行價對現貨價格比例的建立隱含波動度的偏斜衡量的方式。我們使用的公式可以很好的擬合現有的波動度資料。在 1996 到 2019 的標普 500 成分股公司中，我們發現負偏向的波動度曲線對資產報酬有正相關。另一方面，以本論文提出的波動度尋找方式建立隱含波動度的偏斜衡量，可以達到更好的效果。本研究說明文獻中提供的特定執行價對現貨價格比例並不是建立偏斜衡量的唯一方式，也沒有發現最佳比例。同時投資人對於行權價與當前股價之間的最小價格區間數是具有敏感性的。

Abundant literatures have demonstrated the predictive power of the implied volatility skew and the call-put volatility spread for future stock returns. This study attempts to use smoothing curves to facilitate the use of the information of the implied volatilities corresponding to specific strike-to-spot prices. I employ the Stochastic Volatility Inspired (SVI) model fits empirical volatility data well and obtain the SVI IV (implied volatility) curve. Among S&P 500 companies from 1996 to 2019, This study find that a negatively skewed volatility smile is positively correlated with asset returns. On the other hand, it can achieve better results by establishing the skew measure of implied volatility with the volatility finding method proposed in this paper. This study illustrates that the specific strike-to-spot ratios provided in the literature are not the only way to establish the skew measures, and no optimal ratio has been found. Thus, investors are sensitive to the step size of the option’s distance from the current stock price.