近日，据MS官网显示，来自香港城市大学的冯冠豪、西南财经大学的兰伟、北京大学的王汉生、东南大学的张军，合作撰写的论文“ Selecting and Testing Asset-Pricing Models: A Stepwise Approach ”在国际管理学顶刊 Management Science 线上正式发表。

# 论文简介 #

 

Title：

Selecting and Testing Asset-Pricing Models: A Stepwise Approach

 

Author：

Guanhao Feng, Wei Lan, Hansheng Wang, Jun Zhang

 

Abstract：
The asset-pricing literature emphasizes factor models that minimize pricing errors but overlooks unselected candidate factors that could enhance the performance of test assets. This paper proposes a framework for factor model selection and testing by (i) selecting the optimal model that spans the joint efficient frontier of test assets and all candidate factors and (ii) testing pricing performance on both test assets and unselected candidate factors. Our framework updates a baseline model (e.g., capital asset-pricing model) sequentially by adding or removing factors based on asset-pricing tests. Ensuring model selection consistency, our framework utilizes the asset-pricing duality; minimizing cross-sectionally unexplained pricing errors aligns with maximizing the Sharpe ratio of the selected factor model. Empirical evidence shows that workhorse factor models fail asset-pricing tests, whereas our proposed eight-factor model is not rejected and exhibits robust out-of-sample performance.

 

 

标题： 

 

资产定价模型的选择与检验：逐步法

 

中文摘要：

资产定价文献强调最小化定价误差的因子模型，但忽略了那些未被选入模型、却可能提升测试资产表现的未选候选因子。本文提出了一个用于因子模型选择与检验的框架，具体包括：(i) 选择能够跨越测试资产与所有候选因子联合有效前沿的最优模型；（ii）同时检验模型在待检验资产与未被选中的候选因子上的定价表现。该框架基于资产定价检验，通过逐步向基准模型（如资本资产定价模型）中加入或剔除因子来更新模型。为确保模型选择的一致性，我们利用了资产定价的对偶性：最小化横截面上的未解释定价误差，等价于最大化所选因子模型的夏普比率。实证结果表明，常用的因子模型均未通过资产定价检验，而我们提出的八因子模型不仅无法被拒绝，而且展现出稳健的样本外表现。