學者研究如何去預測整個市場或是特定產業的走勢，而時間序列的使用在這個層面也被廣泛使用。實務者跟學者近年來也逐漸開始專注於技術指標的分析上，而近年來越來越多的理論架構是根據行為財務學而產生，像是過度反應以及反應不足。本篇研究的目的旨在透過實務與學術的交流，將兩者的優勢互相結合，首先在詳述其投資策略之方法論後，將其想法透過時間序列分析模型化，再則藉由專業的學術訓練修改其模型。簡言之，本篇論文結論如下:1.實務者的方法確實有其洞察力與預測上的價值。2.在將變數從動能訊號轉換成外資持有市值後，回歸的結果確實有進一步的改善。3.外國機構投資人在不同的產業所持有之市值比例確實在統計上顯著受到報酬率跟現金比率兩者的T值與係數之影響。

Abstract
Researchers have been exploring the subject of how to forecast the trends of overall market and certain of sectors from adequate information so far. The analysis and forecasting of time series are also extensively utilized in a variety of applications. Not only practitioners but also academics have been focus on technical indicators. And recently more and more theories based on behavior finance, such as overreaction and underreaction. This study is attempting to investigate the approach of an analyst according to time series analysis, and especially concerned about the momentum indicator, which is combined with overreaction and underreaction.
Briefly, our conclusions are as follows： 1. The practitioner’s approach does really have its insight and predictive value. 2. After replacing variable from signals to holdings, the regression results have been improved. 3. We could indicate that the market value holding percentage of FINI in different sectors do really have significant influence toward T-statistics and coefficients of returnt-1 and cash ratiot-1.

Key words：Momentum, Overreaction, Underreaction.

楊奕農 (2005)。“時間序列分析 財務與經濟上之應用”。台北：雙葉。
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