隨著開戶人數持續創新高，且開戶人口結構日益年輕化，散戶在市場中的比重逐漸增加。由於年輕投資者通常資金相對較少，散戶的市場影響力逐漸受到重視。本研究旨在識別一個能夠反映散戶對市場看法的相關指標，並探索其與市場表現之間的關聯性，為投資者提供一個能即時反映散戶情緒的指標。
本研究分析了2018年至2023年的每日數據，此資料囊括了中美貿易戰、2020年COVID-19等歷史事件，透過小型台指期貨所以算出來的散戶多空比與台灣加權指數之報酬率進行分析，由於散戶多空比是當日收盤後透過期貨交易所公布的資料，因此我們將台灣加權指數之報酬率分成三個不同時間軸去和散戶多空比做分析。透過DCC-GARCH模型，我們探討了其條件相關性和變異性。研究發現，散戶多空比與當日大盤報酬率呈現顯著的負相關且具有持續性。
此外，本研究透過手動記錄了小型台指期貨盤中的大單內外盤資料，以探討是否可以在當日盤中找出散戶多空比之相關信息。結果顯示，我們可以即時透過小型台指期貨的盤中內外盤成交明細來獲得散戶多空比的信息。這一發現使得投資者能夠更迅速地掌握散戶對市場的看法，為廣大投資者提供了一個實用的參考依據，從而提高投資勝率。

As the number of new accounts reaches record highs and these account holders increasingly skew younger, retail investors are growing in market prominence. Young investors often have less capital, highlighting the importance of understanding retail market influence. This study aims to identify an indicator reflective of retail investor sentiment and explore its correlation with market performance, providing investors with a real-time sentiment gauge.
This research analyzed daily data from 2018 to 2023, encompassing events like the US-China trade war and the COVID-19 pandemic in 2020. It examines the relationship between the retail long-short ratio calculated from Mini-Taiwan Futures and the return rates of the Taiwan Weighted Index. Since the retail long-short ratio is published post-market by the futures exchange, we segmented the Taiwan Weighted Index return rates into three different time frames for analysis. Using the DCC-GARCH model, we investigated their conditional correlation and variability. Findings reveal a significant and persistent negative correlation between the retail long-short ratio and same-day market returns.
Furthermore, by manually recording transaction data of large orders during trading hours for Mini-Taiwan Futures, this study explored the potential for discerning intraday retail sentiment. The results demonstrate that real-time retail long-short information can be gleaned from intraday transaction details of Mini-Taiwan Futures, enabling investors to quickly grasp retail market sentiment. This insight provides a practical reference for investors, potentially increasing their success rate.

論文審定書 i
摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 vii
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 2
1.3研究架構 3
第二章 文獻回顧 4
2.1散戶投資者與大盤報酬率關聯性文獻探討 4
2.2 DCC-GARCH模型應用文獻探討 6
第三章 研究方法與模型設定 9
3.1資料來源與分組介紹 9
3.1-1 資料選取與處理 9
3.1-2資料分組 10
3.2資料初步檢定 12
3.2-1常態分配檢定（Normality Test） 12
3.2-2序列相關檢定（Ljung-Box Q test） 13
3.2-3 ARCH檢定（ARCH test） 13
3.3實證模型設定 14
3.4診斷性檢定 17
第四章 實證結果與分析 18
4.1資料初步檢定結果 18
4.2DCC-GARCH模型結果 20
4.3診斷性檢定結果 29
4.4實證結果 30
第五章 結論與建議 36
參考文獻 37

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