| 摘要: | Blanco and Wehrheim (2015) 利用個股選擇權交易資訊,分析其選擇權交易量與公司創新之 間的關係,他們的研究發現選擇權交易量增加能讓股票市場變得更有效率,進而使得公司願意 進行更多創新投資.然而他們並沒有考慮到選擇權的買權與賣權間相對交易量是隱含有投資人 對未來的市場預期.他們利用的是加總過後的選擇權交易量,也就是說他們並沒有去考慮投資 人對未來預期的方向性對公司創新的影響.但是文獻上卻有許多研究在探討個股選擇權投資人 交易資訊(包括投資人情緒)對未來股栗報酬及或投資之預測能力.文獻上衡量個股選擇權投資 人交易資訊,例如賣權買權交易量比(put-call ratios; Ex. Pan and Poteshman, 2006), 選擇權對股 票交易量比 (the relative trading activity in options and stock (O/S); Ex. Roll et al., 2010), volatility smirks (Xing et al., 2010), 和選擇權隱含波動度差 (option implied volatility spread; Ex. Cremers and Weinbaum, 2010; Chan et al., 2013; Atilgan, 2014; Gharghori et al., 2015; Hao, 2016). 這些研究皆發現,用選擇權市場投資人交易資訊(具方向性),確實對於未來股栗報酬有預測能 力. 此外,有一些在探討選擇權市場投資人情緒 (investor sentiment)的文獻包括 Figlewski (1989), Figlewski and Green (1999), Han (2008), Lemmon and Ni (2010), and Ofek et al. (2004). 這些學 者的研究發現選擇權市場存在投資人情緒會讓價格偏離且能影響對股票報酬的預測.然而,在 股票市場上已有許多文獻在探討投資人情緒對公司投資(包括創新)間的關係.Antoniou, Doukas, and Subrahmanyam (2015) 指出投資人情緒會影響權益資金成本. Grundy and Li (2010) 提出投 資人樂觀主義會影響公司投資的程度. 晚近Byun et al.(2015) 利用有方向性股票交易量較文 獻更能確實捕捉投資人過度反應(overreaction) 的現像. 基於Byun et al 之概念,本研究亦利用 有方向性的個股選擇權投資人交易資訊,來探討其對公司創新的影響, 以補足Blanco and Wehrheim (2015) 較狹隘觀點(僅以選擇權總合交易量)之研究結果. 在第一年計畫裡,我們將花時間來處理龐大的資料,進行基本統計分析,及計算主要變數,在 計畫第二年,我們進一步探討投資人交易資訊對公司創新的影響,並以投資人情緒做Robustness 檢驗.接著利用第二年計劃裡的市場資料及研究成果,在第三年的計劃裡,我們更進一步探討衡 量資訊變數是否能預測公司創新效率. ;Blanco and Wehrheim (2015) investigate whether option trading information can affect corporate innovation. They find that there exists positive relation between option trading volumes and corporate innovation since the increase in option trading volumes will increase the efficiency of stock markets. However, they use aggregated option trading volumes which cannot reflect the direction of investor expectation on the future stock movements. There are several studies using options investor trading information which can more or less reflect the direction of investor expectation on future stock price movements to investigate whether those investor trading information measures extracted from option markets can predict the future stock returns. The most popular trading information measures from option markets include put-call ratios (Pan and Poteshman, 2006), the relative trading activity in options and stock (O/S) (Roll et al., 2010), volatility smirks (Xing et al., 2010), and option implied volatility spread (Cremers and Weinbaum, 2010; Chan et al., 2013; Atilgan, 2014; Gharghori et al., 2015; Hao, 2016). Generally speaking, the above literature finds that various investor trading information can significantly predict future stock returns. Additionally, several scholars also find that investor sentiment can affect investor investment behaviors, and hence result in the stock prices deviated from the equilibrium price. Therefore, the information measures extracted from option markets cannot accurately predict future stock returns. The representative ones are Figlewski, (1989), Figlewski and Green (1999), Ofek et al. (2004), Han (2008), and Lemmon and Ni (2010). More recently, several studies investigate the relationship between investor sentiment and corporate investment decisions. For examples, Antoniou, Doukas, and Subrahmanyam (2015) demonstrate that investor sentiment can affect the cost of equity capital. Furthermore, Grundy and Li (2010) find that the corporate investment level is related to the investor optimism. More recently, Byun et al.(2015) construct weighted trading volumes which can reflect investor expectation on future stock movements. They find that their new measure can more accurately to capture investor overreaction. Inspired by Byun et al.(2015), I will use the investor trading information measures with direction to investigate whether option trading information can affect corporate innovation in this project. Hence this project can provide deeper studies on the issue about how investor trading information affects the corporate innovation. For the first-year project, we focus on dealing with data and provide some basic statistical analysis, and calculate our main variables. In the second-year project, doing a further step analysis, we will carry out the test whether investor trading information with different measures can affect the corporate innovation or not. Based on the data and results obtained at the second-year project, we go on testing that whether investor trading information measures extracted from stock options markets can predict corporate innovation efficiency. |
