||The Optimal Loadings on Fundamental and Technical Variables
||Graduate Institute of Finance
analyst dispersion of forecast earnings
本研究主要目的為尋找在不同情形下投資人所應採取之最適權重，在過往研究股票報酬的文獻中主要採行基本面或是技術面分析，鮮少結合兩種分析方法，然而，透過文獻我們確實可以證實不論是基本面分析抑或是技術面分析兩者皆可以解釋股票報酬，因此，在本研究中為了獲得最多的資訊我們將採取混合模型。我們從COMPSTAT 和CRSP 資料庫中蒐集了10,460樣本，樣本期間涵蓋1993年至2009年。
The purpose of this study is to find the optimal loadings between fundamental and technical approach. Most previous researchers have only employed one kind of information to predict stock returns. However, in our study, we combine accounting-based and market-based information and collect data from COMPSTAT and CRSP databases. The sample period cover from 1993 to 2009. We also employ three determinant variables, which are firm size, discretionary accruals and analyst dispersion, to control optimal loadings. The empirical results indicate that first investors should put more loadings on the fundamental approach in the case of small firms. Second, when management inflates earnings, investors should place more emphasis on technical approaches. Third, a higher dispersion of analysts forecast earnings and investors lower loadings on the fundamental approach. Finally, we also consider the market tendency factor. It finds that when the economy is growing, investors should put more weight on the technical approach.
摘 要 II
誌 謝 IV
1. Introduction 1
2. Literature Review 4
2.1 Fundamentals Approaches 4
2.2 Chartist Function 5
2.3 Hybrid prediction model 6
2.4 Determinants of loadings 6
2.4.1 Firm size 6
2.4.2 Earning management 7
2.4.3 Analyst dispersion 7
2.5 Research question and development of hypothesis 7
3. Econometric models 10
3.1 Model specifications 10
3.1.1 Fundamental approach (ModelⅠ) 10
3.1.2 Technical approach (Model Ⅱ) 11
3.1.3 Hybrid approach (Model Ⅲ) 12
3.2 Measure of the determinant variables 13
3.2.1 Firm size 13
3.2.2 Discretionary accruals 13
3.2.3 Dispersion 14
3.3 Validation methodology 14
4. Empirical results 16
4.1 Data 16
4.2 Highbred versus hybrid model 17
4.2.1 Result of model estimation 17
4.2.2 Measure of predictive power 18
4.3 Optimal loadings of various conditions 19
4.3.1 Optimal loadings of firm size 19
4.3.2 Optimal loadings of earning management 20
4.3.3 Optimal loadings of analyst dispersion 21
4.3.4 Optimal market loadings 21
5. Conclusions 23
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