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研究生: 黃進鵬
Jin-pon Huang
論文名稱: 資產定價模型的非巢式檢定
Non-nested Tests of Asset Pricing Models
指導教授: 周賓凰
Pin-Huang Chou
口試委員:
學位類別: 碩士
Master
系所名稱: 管理學院 - 財務金融學系
Department of Finance
畢業學年度: 97
語文別: 英文
論文頁數: 40
中文關鍵詞: 非巢式資產定價模型
外文關鍵詞: non-nested, asset pricing models
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  • 在財務領域中有許多配適資產報酬率的訂價模型, 但是很少有將數個模型放在
    一起比較的相關討論。非巢式的模型定式檢定提供我們比較這許多模型的計量工
    具。在許多的資產定價模型中, 我們選擇了較常見的四個模型做為比較的標的, 分
    別是Fama-French三因子模型、Ferguson and Shockley 的模型、Liu’s 流動性
    二因子模型以及Petkova 的模型。檢定的結果因不同的投組報酬而異。當使用以
    size 及B/M 排序而得的二十五投組報酬時, 結果呈現出愈晚被提出來的模型其
    解釋報酬率的能力也愈高。當使用十二個產業別的投組報酬時,Liu’s 流動性二因
    子模型則較為弱勢。


    Many asset pricing models have been proposed to fit the asset returns
    in the literature, but few studies discuss the relative performance between
    them. Non-nested model specification tests provide the econometric tools to
    compare the performance of many models. Of many asset pricing models,
    we choose popular Fama-French three factor model, Ferguson and Shockley’s
    model, Liu’s liquidity-augmented model and Petkova’s model as competing
    models. The results are different with 25 size- and B/M- sorted returns and
    12 industry returns. When using 25 portfolio returns, the result has the
    pattern that the later proposed model has the better ability to explain the
    variation on returns. While the 12 industry returns is used, Liu’s liquidityaugmented
    model tends to be the worst model to fit the returns.

    Contents 1 Introduction 1 2 Methodology 2 2.1 Competing Models . . . . . . . . . . . . . . . . . . . . . . . . 3 2.2 Econometric Methods . . . . . . . . . . . . . . . . . . . . . . . 4 2.3 Artificial Compound Models . . . . . . . . . . . . . . . . . . . 5 2.3.1 J Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.3.2 Ja Tests . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.3.3 P1 Tests . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.4 SUR Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.5 The Tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Data and Empirical Results 12 3.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 3.2 Empirical Results . . . . . . . . . . . . . . . . . . . . . . . . . 14 4 Bootstrap Test 16 5 Conclusion 17 Reference 33

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