Conditional Asset Pricing Predicting Time Varying Beta Factors With Group Method Of Data Handling Methods
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Author | : Sebastian Schneider |
Publisher | : |
Total Pages | : 27 |
Release | : 2005 |
Genre | : |
ISBN | : |
Allowing for time-varying risk premia yields sophisticated asset pricing models, but the search for adequate model specifications is more challenging. We introduce, to our knowledge, previously in conditional asset pricing not used Group Method of Data Handling (GMDH) that rests on sorting out requiring statsitical models for complex problems of unknown structure but does not require a model to predict conditional variation in betas. We find that lagged instruments used to proxy for expected returns in conditional asset pricing provide a challenge not only for the unconditional CAPM but also the Fama-French-model. Thereby non-linear GMDH-algorithms challenge traditional models of conditional asset pricing as we find a highly non-linear influence of lagged instruments on both conditional alphas and betas. Therefore, predetermining a structure for functional relationships between conditional alphas as well as betas and lagged instruments may lead to a significant misspecification of asset pricing models.
Author | : Wayne Ferson |
Publisher | : MIT Press |
Total Pages | : 497 |
Release | : 2019-03-12 |
Genre | : Business & Economics |
ISBN | : 0262039370 |
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.
Author | : Daniele Bianchi |
Publisher | : |
Total Pages | : 42 |
Release | : 2019 |
Genre | : |
ISBN | : |
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 | : Wayne E. Ferson |
Publisher | : |
Total Pages | : 38 |
Release | : 2010 |
Genre | : |
ISBN | : |
This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become baised. Previous studies overstate the significance of time-varying alphas.
Author | : Wayne E. Ferson |
Publisher | : |
Total Pages | : 31 |
Release | : 2006 |
Genre | : Assets (Accounting) |
ISBN | : |
This paper studies the estimation of asset pricing model regressions with conditional alphas and betas, focusing on the joint effects of data snooping and spurious regression. We find that the regressions are reasonably well specified for conditional betas, even in settings where simple predictive regressions are severely biased. However, there are biases in estimates of the conditional alphas. When time-varying alphas are suppressed and only time-varying betas are considered, the betas become baised. Previous studies overstate the significance of time-varying alphas.
Author | : Gilles Dufrénot |
Publisher | : Springer Nature |
Total Pages | : 387 |
Release | : 2020-11-21 |
Genre | : Business & Economics |
ISBN | : 3030542521 |
The book provides a comprehensive overview of the latest econometric methods for studying the dynamics of macroeconomic and financial time series. It examines alternative methodological approaches and concepts, including quantile spectra and co-spectra, and explores topics such as non-linear and non-stationary behavior, stochastic volatility models, and the econometrics of commodity markets and globalization. Furthermore, it demonstrates the application of recent techniques in various fields: in the frequency domain, in the analysis of persistent dynamics, in the estimation of state space models and new classes of volatility models. The book is divided into two parts: The first part applies econometrics to the field of macroeconomics, discussing trend/cycle decomposition, growth analysis, monetary policy and international trade. The second part applies econometrics to a wide range of topics in financial economics, including price dynamics in equity, commodity and foreign exchange markets and portfolio analysis. The book is essential reading for scholars, students, and practitioners in government and financial institutions interested in applying recent econometric time series methods to financial and economic data.
Author | : Michelle L. Barnes |
Publisher | : |
Total Pages | : 40 |
Release | : 2005 |
Genre | : |
ISBN | : |
Standard approaches to the estimation and testing of conditional CAPM models with time-varying or random beta have ignored the potential panel nature of financial data. We test for whether or not homogeneity restrictions on the time-variation component of multifactor betas and on the slope parameters for the conditioning variables can be rejected. We find that such homogeneity restrictions are not rejected, and show that there are resultant benefits for testing conditional CAPM and forecasting expected returns and beta. Further, this panel approach yields more precise parameter estimates, and a greater understanding of the significance of both conditional variables and multi-factors.
Author | : Groupe HEC (Jouy-en-Josas, Yvelines). Direction de la recherche |
Publisher | : |
Total Pages | : 41 |
Release | : 2006 |
Genre | : |
ISBN | : 9782854188288 |
This paper explores the theoretical and empirical implications of time-varying and unobservable betas. Investors infer factor loadings from the history of returns via the Kalman filter. Due to learning, the history of beta matters. Even though the conditional CAPM holds, standard OLS tests can reject the model if the evolution of investor's expectations is not properly modelled. We use our methodology to explain returns on the twenty-five size and book-to-market sorted portfolios. Our learning version of the conditional CAPM produces pricing errors that are significantly smaller than standard conditional or unconditional CAPM and the model is not rejected by the data.
Author | : Victor Ng |
Publisher | : |
Total Pages | : 216 |
Release | : 1989 |
Genre | : Stocks |
ISBN | : |
Author | : Devraj Basu |
Publisher | : |
Total Pages | : 43 |
Release | : 2019 |
Genre | : |
ISBN | : |
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.