A Dynamic Test of Conditional Asset Pricing Models


Book Description

I use Bayesian tools to develop a dynamic testing methodology for conditional factor pricing models, in which time-varying betas, idiosyncratic risks, and factors risk premia are jointly estimated in a single step. Based on this framework, I test over fifty years of post-war monthly data some of the most common factor pricing models on size, book-to-market, and momentum deciles portfolios, both in the time series and in the cross section. The empirical results show that, a conditional specification of the recent five-factor model of Fama and French (2015) outperforms a set of theory-based competing linear pricing models along several dimensions.




Conditional Asset Pricing with a Large Information Set


Book Description

Dynamic factors summarize the information in a large number of variables and are therefore intuitively appealing proxies for the information set available to investors. This paper demonstrates that conditioning on dynamic factors instead of commonly used instruments substantially reduces the pricing errors implied by conditional models. Dynamic factors are further shown to exhibit incremental explanatory power over benchmark conditioning variables. The results withstand a number of robustness tests and carry important implications for the specification of conditional asset pricing models in applied research and practice.













Time-Varying Conditional Covariances in Tests of Asset Pricing Models


Book Description

This paper proposes tests of asset pricing models that allow for time variation in conditional covariances. The evidence indicates that the conditional covariances do change through time. Estimates of the expected excess return on the market divided by the variance of the market (reward-to-risk ratio) are presented for the Sharpe-Lintner CAPM, as well as a number of tests of the model specification. The patterns of the pricing errors through time suggest the model's inability to capture the dynamic behavior of asset returns. This is the working paper version of my 1989 Journal of Financial Economics article.




A Cross-Sectional Test of an Investment-Based Asset Pricing Model


Book Description

I examine a factor pricing model for stock returns. The factors are returns on physical investment, inferred from investment data via a production function. I examine the model's ability to explain variation in expected returns across asset and over time. The model is not rejected. It performs about as well as the CAPM and the Chen, Roll, and Ross factor model, and it performs substantially better than a simple consumption-based model. I also provide an easy technique for estimating and testing dynamic, conditional asset pricing models--one simply includes factors and returns scaled by instruments in an unconditional estimate--and for comparing such models.




A Cross-Sectional Test of a Production-Based Asset Pricing Model


Book Description

This paper tests a factor pricing model for stock returns. The factors are returns on physical investment, inferred from investment data via a production function. The tests examine the model's ability to explain the variation in expected returns across assets and over time. The model is not rejected. It performs about as well as the CAPM and the Chen, Roll and Ross factor model, and it performs substantially better than a simple consumption-based model. In comparison tests, the investment return factors drive out all the other models. The paper also provides an easy technique for estimating and testing dynamic, conditional asset pricing models. All one has to do is include factors and returns scaled by instruments in an unconditional estimate. This procedure imposes none of the usual restrictions on conditional moments, and does not require prewhitened or orthogonalized factors.




A Cross-Sectional Test of a Production-Based Asset Pricing Model


Book Description

This paper tests a factor pricing model for stock returns. The factors are returns on physical investment, inferred from investment data via a production function. The tests examine the model's ability to explain the variation in expected returns across assets and over time. The model is not rejected. It performs about as well as the CAPM and the Chen, Roll and Ross factor model, and it performs substantially better than a simple consumption-based model. In comparison tests, the investment return factors drive out all the other models. The paper also provides an easy technique for estimating and testing dynamic, conditional asset pricing models. All one has to do is include factors and returns scaled by instruments in an unconditional estimate. This procedure imposes none of the usual restrictions on conditional moments, and does not require prewhitened or orthogonalized factors.




Dynamic Asset-pricing Models


Book Description

Presents a selection of the most important articles in the field of financial econometrics. Starting with a review of the philosophical background, this collection covers such topics as the random walk hypothesis, long-memory processes, asset pricing, arbitrage pricing theory, variance bounds tests, term structure models, and more.