Tests of the Conditional Asset Pricing Model
Tests of the Conditional Asset Pricing Model

Author: Stuart Hyde

Publisher:

Published: 2017

Total Pages:

ISBN-13:

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We investigate the relationship between consumption and the term structure using U.K. interest rate data. We demonstrate that the term structure contains information about future economic activity as implied by the benchmark time separable power utility consumption based capital asset pricing model (C-CAPM) since the yield spread has forecasting power for future consumption growth. Further, we analyze the ability of this benchmark and two alternative models which adopt utility functions characterized by non-separability, namely, the extension to the habit formation model of Campbell and Cochrane (1999) proposed by Wachter (2006) and the housing C-CAPM proposed by Piazzesi et al. (2007). Our findings are supportive of the habit formation specification of Wachter (2006), other models fail to yield economically plausible parameter values.

A Dynamic Test of Conditional Asset Pricing Models
A Dynamic Test of Conditional Asset Pricing Models

Author: Daniele Bianchi

Publisher:

Published: 2019

Total Pages: 42

ISBN-13:

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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.

Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach
Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach

Author: Manuel Ammann

Publisher:

Published: 2014

Total Pages: 41

ISBN-13:

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We propose a new approach for the estimation of conditional asset pricing models based on a Markov Chain Monte Carlo (MCMC) approach. In contrast to existing approaches, it is truly conditional because the assumption that time variation in betas is driven by a set of conditioning variables is not necessary. Moreover, the approach has exact finite sample properties and accounts for errors-in-variables in a one-step estimation procedure. Using Samp;P 500 panel data, we analyze the empirical performance of the CAPM and the Fama and French (1993) three-factor model. We find that time-variation of betas in the CAPM and the time variation of the coefficients for the size factor (SMB) and the distress factor (HML) in the three-factor model improve the empirical performance by a similar amount. Therefore, our findings are consistent with time variation of firm-specific exposure to market risk, systematic credit risk and systematic size effects. However, a Bayesian model comparison trading off goodness of fit and model complexity indicates that the conditional CAPM performs best, followed by the conditional three-factor model, the unconditional CAPM, and the unconditional three-factor model.

Time-Varying Conditional Covariances in Tests of Asset Pricing Models
Time-Varying Conditional Covariances in Tests of Asset Pricing Models

Author: Campbell R. Harvey

Publisher:

Published: 2005

Total Pages: 36

ISBN-13:

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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.

Evaluating Conditional Asset Pricing Models for the German Stock Market
Evaluating Conditional Asset Pricing Models for the German Stock Market

Author: Andreas Schrimpf

Publisher:

Published: 2008

Total Pages: 45

ISBN-13:

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We study the performance of conditional asset pricing models in explaining the German cross-section of stock returns. Our test assets are portfolios sorted by size and book-to-market as in the paper by Fama and French (1993). Our results show that the empirical performance of the Capital Asset Pricing Model (CAPM) can be improved substantially when allowing for time-varying parameters of the stochastic discount factor. A conditional CAPM with the term spread as a conditioning variable is able to explain the cross-section of German stock returns about as well as the Fama-French model. Structural break tests do not indicate parameter instability of the model - whereas the reverse is found for the Fama-French model. Unconditional model specifications however do a better job than conditional ones at capturing time-series predictability of the test portfolio returns.

Empirical Asset Pricing
Empirical Asset Pricing

Author: Wayne Ferson

Publisher: MIT Press

Published: 2019-03-12

Total Pages: 497

ISBN-13: 0262039370

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An introduction to the theory and methods of empirical asset pricing, integrating classical foundations with recent developments. This book offers a comprehensive advanced introduction to asset pricing, the study of models for the prices and returns of various securities. The focus is empirical, emphasizing how the models relate to the data. The book offers a uniquely integrated treatment, combining classical foundations with more recent developments in the literature and relating some of the material to applications in investment management. It covers the theory of empirical asset pricing, the main empirical methods, and a range of applied topics. The book introduces the theory of empirical asset pricing through three main paradigms: mean variance analysis, stochastic discount factors, and beta pricing models. It describes empirical methods, beginning with the generalized method of moments (GMM) and viewing other methods as special cases of GMM; offers a comprehensive review of fund performance evaluation; and presents selected applied topics, including a substantial chapter on predictability in asset markets that covers predicting the level of returns, volatility and higher moments, and predicting cross-sectional differences in returns. Other chapters cover production-based asset pricing, long-run risk models, the Campbell-Shiller approximation, the debate on covariance versus characteristics, and the relation of volatility to the cross-section of stock returns. An extensive reference section captures the current state of the field. The book is intended for use by graduate students in finance and economics; it can also serve as a reference for professionals.