第二篇文章研究隱含波動度差和選擇權報酬間的關係，過去文獻指出買賣權隱含波動度差能正向預測未來股票報酬，然而，Doran, Fodor and Jiang (2013)的研究指出隱含波動度差能正向預測股票報酬，但卻負向預測未來的買權報酬。Atilgan (2014) 和 Chan, Ge, and Lin (2015)探討在考慮財務事件下，隱含波動度差能顯著預測財務事件後的股票報酬，不同於過去文獻，本文則探討在考慮盈餘宣告事件下，隱含波動度差是否能正向預測未來的買權報酬。在實證分析上，結果發現在考慮財務事件期間，隱含波動度差反而更為負向預測未來的買權報酬。因此，本文進一步再去探討是否是投資人的情緒影響預測的結果，結果發現，隱含波動度差負向預測未來的買權報酬在投資人情緒越高漲的期間更為顯著。此外，本文亦去驗證投資人是否會透過學習，進而去降低預測偏誤，結果發現，當選擇權市場存在更多有資訊交易者時，即有越多的資訊釋放到市場上，投資人會透過學習使得預測偏誤下降。 ;This essay contains two studies on the option illiquidity premium and volatility spread in the stock option market. One is the relationship between option illiquidity and expected option returns under information environments and another is volatility spread and expected option returns.
First Essay: The Impacts of Asymmetric Information and Short Sales on the Illiquidity Risk Premium in the Stock Option Market
The illiquidity risk premium hypothesis implies the existence of a positive relationship between illiquidity in the option markets and option returns. Based on numerous studies within the extant literature examining the roles of informed traders in the option markets,we explore the ways in which asymmetric information and short sales can affect the illiquidity risk premium hypothesis. Our findings reveal that the illiquidity risk premium is higher for the options of those firms with higher information asymmetry, as well as those firms with higher short sales demand or supply. These results are found to be particularly robust for short-term options contracts.
Second Essay: Implied Volatility Spreads and Future Options Returns
While numerous studies have documented that call-put implied volatility spreads positively predict future stock returns,the predictive relationship is recently found to be negative for future call option returns. We further investigate whether and how the predictive relationship for options returns is influenced by various information events and conditions. In addition to confirming the existence of the opposite predictive relationships for both call and put returns, our empirical results reveal that the predictive relationships are stronger during periods of earnings announcement and/or high sentiment. In addition, we find that investors learn from informed trading and revise their predictability bias by examining the impacts of information asymmetry, stock liquidity, and options liquidity on the predictive relationships.
