Testing Conditional Factor Models PDF Download
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| Author | : Andrew Ang |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2011 |
| Genre | : Economics |
| ISBN | : |
Download Testing Conditional Factor Models Book in PDF, ePub and Kindle
Using nonparametric techniques, we develop a methodology for estimating conditional alphas and betas and long-run alphas and betas, which are the averages of conditional alphas and betas, respectively, across time. The tests can be performed for a single asset or jointly across portfolios. The traditional Gibbons, Ross, and Shanken (1989) test arises as a special case of no time variation in the alphas and factor loadings and homoskedasticity. As applications of the methodology, we estimate conditional CAPM and multifactor models on book-to-market and momentum decile portfolios. We reject the null that long-run alphas are equal to zero even though there is substantial variation in the conditional factor loadings of these portfolios.
| Author | : Liyan Yang |
| Publisher | : |
| Total Pages | : 39 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
Download Testing Conditional Factor Models Book in PDF, ePub and Kindle
Recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama-French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.
| Author | : Yan Li |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
Download A Combined Approach to the Inference of Conditional Factor Models Book in PDF, ePub and Kindle
This paper develops a new methodology for estimating and testing conditional factor models in finance. We propose a two-stage procedure that naturally unifies the two existing approaches in the finance literature -- the parametric approach and the nonparametric approach. Our combined approach possesses important advantages over both methods. Using our two-stage combined estimator, we derive new test statistics for investigating key hypotheses in the context of conditional factor models. Our tests can be performed on a single asset or jointly across multiple assets. We further propose a novel test to directly check whether the parametric model used in our first stage is correctly specified. Simulations indicate that our estimates and tests perform well in finite samples. In our empirical analysis, we use our new method to examine the performance of the conditional CAPM, which has generated controversial results in the recent asset-pricing literature.
| Author | : Gabriele Fiorentini |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2001 |
| Genre | : |
| ISBN | : |
Download Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Models Book in PDF, ePub and Kindle
We investigate the effects of dynamic heteroskedasticity on statistical factor analysis. We show that identification problems are alleviated when variation in factor variances is accounted for. Our results apply to dynamic APT models and other structural models. We also find that traditional ML estimation of unconditional variance parameters remains consistent if the factor loadings are identified from the unconditional distribution, but their standard errors must be robustified. We develop a simple preliminary LM test for ARCH effects in the common factors, and discuss two-step consistent estimation of the conditional variance parameters. Finally, we conduct a detailed simulation exercise.
| Author | : Daniele Bianchi |
| Publisher | : |
| Total Pages | : 42 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
Download A Dynamic Test of Conditional Asset Pricing Models Book in PDF, ePub and Kindle
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.
| Author | : Devraj Basu |
| Publisher | : |
| Total Pages | : 43 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
Download Asset Pricing Anomalies and Time-Varying Betas Book in PDF, ePub and Kindle
In this paper, we develop a new measure of specification error, and thus derive new statistical tests, for conditional factor models, i.e. models in which the factor loadings (and hence risk premia) are allowed to be time-varying. Our test exploits the close links between the stochastic discount factor framework and mean-variance efficiency. We show that a given set of factors is a true conditional asset pricing model if and only if the efficient frontiers spanned by the traded assets and the factor-mimicking portfolios, respectively, intersect. In fact, we show that our test is proportional to the difference in squared Sharpe ratios of these two frontiers.We draw three main conclusions from our empirical findings. First, optimal scaling clearly improves the performance of asset pricing models, to the point where several of the scaled models are capable of explaining asset pricing anomalies. However, even the optimally scaled models fall short of being true conditional asset pricing models in that they fail to price actively managed portfolios correctly. Second, there is significant time-variation in factor loadings and hence risk premia, which plays a significant role in asset pricing. Moreover, the optimal factor loadings display a high degree of non-linearity in the conditioning variables, suggesting that the linear scaling prevalent in the literature is sub-optimal and does not capture the inter-temporal pattern of risk premia. Third, skewness and kurtosis do matter in the conditional setting, while adding little to unconditional performance.
| Author | : John Knight |
| Publisher | : Elsevier |
| Total Pages | : 298 |
| Release | : 2004-12-01 |
| Genre | : Business & Economics |
| ISBN | : 0080455328 |
Download Linear Factor Models in Finance Book in PDF, ePub and Kindle
The determination of the values of stocks, bonds, options, futures, and derivatives is done by the scientific process of asset pricing, which has developed dramatically in the last few years due to advances in financial theory and econometrics. This book covers the science of asset pricing by concentrating on the most widely used modelling technique called: Linear Factor Modelling. Linear Factor Models covers an important area for Quantitative Analysts/Investment Managers who are developing Quantitative Investment Strategies. Linear factor models (LFM) are part of modern investment processes that include asset valuation, portfolio theory and applications, linear factor models and applications, dynamic asset allocation strategies, portfolio performance measurement, risk management, international perspectives, and the use of derivatives. The book develops the building blocks for one of the most important theories of asset pricing - Linear Factor Modelling. Within this framework, we can include other asset pricing theories such as the Capital Asset Pricing Model (CAPM), arbitrage pricing theory and various pricing formulae for derivatives and option prices. As a bare minimum, the reader of this book must have a working knowledge of basic calculus, simple optimisation and elementary statistics. In particular, the reader must be comfortable with the algebraic manipulation of means, variances (and covariances) of linear combination(s) of random variables. Some topics may require a greater mathematical sophistication. * Covers the latest methods in this area. * Combines actual quantitative finance experience with analytical research rigour * Written by both quantitative analysts and academics who work in this area
| Author | : Manuel Ammann |
| Publisher | : |
| Total Pages | : 41 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
Download Testing Conditional Asset Pricing Models Using a Markov Chain Monte Carlo Approach Book in PDF, ePub and Kindle
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.
| Author | : Neil R. Ericsson |
| Publisher | : |
| Total Pages | : 436 |
| Release | : 1994 |
| Genre | : Business & Economics |
| ISBN | : 9780198774044 |
Download Testing Exogeneity Book in PDF, ePub and Kindle
This book discusses the nature of exogeneity, a central concept in standard econometrics texts, and shows how to test for it through numerous substantive empirical examples from around the world, including the UK, Argentina, Denmark, Finland, and Norway. Part I defines terms and provides the necessary background; Part II contains applications to models of expenditure, money demand, inflation, wages and prices, and exchange rates; and Part III extends various tests of constancy and forecast accuracy, which are central to testing super exogeneity. About the Series Advanced Texts in Econometrics is a distinguished and rapidly expanding series in which leading econometricians assess recent developments in such areas as stochastic probability, panel and time series data analysis, modeling, and cointegration. In both hardback and affordable paperback, each volume explains the nature and applicability of a topic in greater depth than possible in introductory textbooks or single journal articles. Each definitive work is formatted to be as accessible and convenient for those who are not familiar with the detailed primary literature.
| Author | : Kerry Back |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
Download Testing Factor Models on Characteristic and Covariance Pure Plays Book in PDF, ePub and Kindle
We test the recent Fama-French five-factor model and Hou-Xue-Zhang four-factor model using test assets from Fama-MacBeth regressions, which are pure plays on particular characteristics or covariances. Our tests resolve the errors-in-variable bias in Fama-MacBeth regressions with estimated betas. Monte Carlo evidence shows that the tests are unbiased even with time-varying stock betas and characteristics. For both factor models, characteristic pure plays generally have positive alphas, and covariance pure plays have negative alphas. The models fail especially in explaining returns to investment and when pure plays are momentum-neutral. The rejections are economically significant.
