英文标题：
《Comparing Asset Pricing Models: Distance-based Metrics and Bayesian
Interpretations》
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作者：
Zhongzhi Lawrence He
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最新提交年份：
2018
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英文摘要：
In light of the power problems of statistical tests and undisciplined use of alpha-based statistics to compare models, this paper proposes a unified set of distance-based performance metrics, derived as the square root of the sum of squared alphas and squared standard errors. The Bayesian investor views model performance as the shortest distance between his dogmatic belief (model-implied distribution) and complete skepticism (data-based distribution) in the model, and favors models that produce low dispersion of alphas with high explanatory power. In this view, the momentum factor is a crucial addition to the five-factor model of Fama and French (2015), alleviating his prior concern of model mispricing by -8% to 8% per annum. The distance metrics complement the frequentist p-values with a diagnostic tool to guard against bad models.
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中文摘要：
针对统计测试的威力问题和基于α的统计数据在比较模型时的无纪律使用，本文提出了一组统一的基于距离的性能度量，其导出为α平方和标准误差平方之和的平方根。贝叶斯投资者将模型性能视为其在模型中的教条信念（模型隐含分布）和完全怀疑（基于数据的分布）之间的最短距离，并倾向于产生低α离散度和高解释力的模型。在这种观点下，动量因素是Fama和French（2015）五因素模型的一个重要补充，将他之前对模型错误定价的担忧每年减少了-8%至8%。距离度量用诊断工具补充了频繁出现的p值，以防止出现不良模型。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Portfolio Management 项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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