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Testing Beta-Pricing Models Using Large Cross-Sections
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DOI：10.1093/rfs/hhz064.png)
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Abstract
En 中文
We propose a methodology for estimating and testing beta-pricing models when a large number of assets is available for investment but the number of time-series observations is fixed. We first consider the case of correctly specified models with constant risk premia, and then extend our framework to deal with time-varying risk premia, potentially misspecified models, firm characteristics, and unbalanced panels. We show that our large cross-sectional framework poses a serious challenge to common empirical findings regarding the validity of beta-pricing models. In the context of pricing models with Fama-French factors, firm characteristics are found to explain a much larger proportion of variation in estimated expected returns than betas.
Keywords:
DISCOUNT FACTOR MODELS
RISK PREMIA
MIMICKING PORTFOLIOS
ROBUST INFERENCE
PERFORMANCE
ARBITRAGE
IDENTIFICATION
RETURNS
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