近年來，愈來愈多文獻指出流通於廣泛媒體間的公開資訊對於金融市場有莫大的影響性，例如:資產價格的變動間接反映了資訊內涵。本研究首先探討以媒體資訊為基準的情緒衡量是否能有效預測波動率指數期貨的價格變化。根據Webhose.io提供規模龐大且各式型態的媒體資料，該情緒指數的建立是利用文字探勘的技術來分析並量化在線新聞報導、部落格文章以及論壇留言中所涵蓋的資訊及情緒語調。實證結果表明，媒體所發布的資訊介於前一日收盤後至當日開盤前，該區間的情緒指數對於當日波動率指數期貨的報酬具有顯著預測力。接著探討在週頻率基礎下，波動率指數期貨報酬的預測力能持續多久。根據結果顯示，新聞報導下的週平均情緒指數僅能預測一週後的波動率指數期貨週報酬。此外，絕大多數的總經宣告衝擊並未提升情緒指標對於波動率指數期貨報酬的解釋力，反而削弱情緒指數的預測力。依據市場及資訊流之特性來逐一分組，發現情緒指數對於波動率指數期貨的預測及影響性在以下四種情況較為強烈:(1)大量資訊發布、(2)交易活動頻繁、(3)價格波動性大、(4)市場較不具流動性。最後，從投資角度來看，無論是避險抑或是未避險部位，根據情緒指數來放空或買進波動率指數期貨的獲利性皆非常可觀。相較於其他類型的媒體，新聞報導下所計算的情緒指數，其預測性和獲利能力皆具有強烈的顯著性。整體研究結果意味著媒體情緒不僅具有統計上顯著的波動率指數期貨報酬之可預測性，同時在交易實務上具有高獲利性的經濟價值。

With the circulation of information in a wider variety of social media, this study first explores the predictive relation between measurements of media-based sentiment extracted from large-scale web data feeds on Webhose.io and the VIX futures returns. The media-based sentiment measure is constructed based on textual analysis to quantify tone of information included in the online news stories, blog posts and discussions messages. The substantial evidence show that daily VIX futures returns are predictable using sentiment index calculated during overnight hours after closing of previous day and before the opening of the day. On the basis of longer horizon, the weekly average sentiment index of news articles can only predict future return after one week. Moreover, most macroeconomic announcements shocks weaken the predictability of sentiment index. According to analyzing the different characteristics, the sentiment effect is stronger during large number of postings are released, high trading volume, high volatility, and high illiquidity days. From an investment perspective, simulated trading on VIX futures in accordance with media-based sentiment measure is highly profitable. Both predictive power and profitability of sentiment measure is strongly significant in news articles. While the overall findings demonstrate that media-based sentiment appears to carries not only statistically significant return predictability of VIX futures but economic value while evaluated with the simulated trading strategies.

論文審定書 i
摘要 ii
ABSTRACT iii
I. Introduction 1
II. Literature Review 6
III. Data and Methodology 17
3.1 Implied Volatility Index Futures 17
3.2 Media Data 19
3.3 Sentiment Index of Media Data Feed 21
IV. Empirical Analysis 22
4.1 Return Predictability of Sentiment index on VIX Futures 22
4.2 The Effect of Macroeconomic Announcements Surprises 25
4.3 Day of the Week 28
4.4 Information Flow and Market Characteristics 30
4.5 How Long does the Return Predictability Last? 34
V. Profitability of Sentiment based on Trading Strategies 36
5.1 Performance of Unhedged VIX Futures Positions 36
5.2 Performance of Hedged VIX Futures Positions 41
5.3 Jensen's alpha 45
VI. Conclusions 49
Reference 54

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