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Author: Devraj Basu Publisher: ISBN: Category : Languages : en Pages : 30
Book Description
The failure of the static-beta CAPM to explain the cross-section of returns on portfolios sorted on firm size, book-to-market ratio, momentum, and even portfolios sorted on past CAPM betas, is well documented. In this paper we show that the model's performance dramatically improves when portfolio betas are allowed to be time-varying functions of (lagged) business cycle variables. We use an approach based on Hansen and Richard (1987) to construct a candidate stochastic discount factor (SDF), using the excess return on the market portfolio as the single factor, scaled by a time-varying coeplusmn;cient. The result is a model in which the conditional factor risk premium is a non-linear function of the business cycle variables. We assess the performance of our model by computing the R2 of the cross-sectional regression of realized on model-implied expected returns, as for example in Jagannathan and Wang (1996). While this is not a formal test of the model's ability to price the assets correctly, it does provide an informative summary statistic that allows us to compare the performance of our scaled model with that of the static version, and also to compare our findings to those of other similar studies.In the post-1980 period, where the static CAPM is known to perform particularly poorly, our scaled model explains around 60% of the cross-sectional variation in returns on beta and book-to-market portfolios, and 87% for momentum portfolios. Moreover, the model captures 70% of the value premium (the return spread between the highest and lowest book-to-market decile portfolios), and 75% of the momentum premium (the spread between the past 'winner' and 'loser' portfolios). Our results thus confirm the crucial importance of time-varying risk premiums in explaining the cross-section of average returns on these sets of portfolios. Moreover, the conditional market risk premium and hence also the betas implied by our model exhibits considerable non-linearity in the business cycle instruments.
Author: Devraj Basu Publisher: ISBN: Category : Languages : en Pages : 30
Book Description
The failure of the static-beta CAPM to explain the cross-section of returns on portfolios sorted on firm size, book-to-market ratio, momentum, and even portfolios sorted on past CAPM betas, is well documented. In this paper we show that the model's performance dramatically improves when portfolio betas are allowed to be time-varying functions of (lagged) business cycle variables. We use an approach based on Hansen and Richard (1987) to construct a candidate stochastic discount factor (SDF), using the excess return on the market portfolio as the single factor, scaled by a time-varying coeplusmn;cient. The result is a model in which the conditional factor risk premium is a non-linear function of the business cycle variables. We assess the performance of our model by computing the R2 of the cross-sectional regression of realized on model-implied expected returns, as for example in Jagannathan and Wang (1996). While this is not a formal test of the model's ability to price the assets correctly, it does provide an informative summary statistic that allows us to compare the performance of our scaled model with that of the static version, and also to compare our findings to those of other similar studies.In the post-1980 period, where the static CAPM is known to perform particularly poorly, our scaled model explains around 60% of the cross-sectional variation in returns on beta and book-to-market portfolios, and 87% for momentum portfolios. Moreover, the model captures 70% of the value premium (the return spread between the highest and lowest book-to-market decile portfolios), and 75% of the momentum premium (the spread between the past 'winner' and 'loser' portfolios). Our results thus confirm the crucial importance of time-varying risk premiums in explaining the cross-section of average returns on these sets of portfolios. Moreover, the conditional market risk premium and hence also the betas implied by our model exhibits considerable non-linearity in the business cycle instruments.
Author: Aslihan Altay Salih Publisher: ISBN: Category : Languages : en Pages : 24
Book Description
Although there is a consensus about time variation in market betas, it is not clear how this variation should be captured. Several researchers continue to analyze different versions of the conditional CAPM. However, Ghysels (1998) shows that these conditional CAPM models fail to capture the dynamics of beta risk. In this study, we introduce a new model, threshold CAPM, which outperforms both the conditional and unconditional CAPMs by generating smaller pricing errors. We also show that the beta risk changes through time with the changes in the economic environment and the dynamics of time variation of beta differ across industries. These findings have important implications for asset allocation, portfolio selection, and hedging decisions.
Author: Groupe HEC (Jouy-en-Josas, Yvelines). Direction de la recherche Publisher: ISBN: 9782854188288 Category : Languages : en Pages : 41
Book Description
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: Gilles Dufrénot Publisher: Springer Nature ISBN: 3030542521 Category : Business & Economics Languages : en Pages : 387
Book Description
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: Ly H. Anh Publisher: Springer ISBN: 3319731505 Category : Technology & Engineering Languages : en Pages : 1089
Book Description
This book addresses both theoretical developments in and practical applications of econometric techniques to finance-related problems. It includes selected edited outcomes of the International Econometric Conference of Vietnam (ECONVN2018), held at Banking University, Ho Chi Minh City, Vietnam on January 15-16, 2018. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. An extremely important part of economics is finances: a financial crisis can bring the whole economy to a standstill and, vice versa, a smart financial policy can dramatically boost economic development. It is therefore crucial to be able to apply mathematical techniques of econometrics to financial problems. Such applications are a growing field, with many interesting results – and an even larger number of challenges and open problems.
Author: Sebastian Wilde Publisher: GRIN Verlag ISBN: 3346707598 Category : Business & Economics Languages : en Pages : 29
Book Description
Seminar paper from the year 2021 in the subject Economics - Finance, grade: 1,3, University of Hagen (Fakultät für Wirtschaftswissenschaft, Lehrstuhl für Angewandte Statistik), language: English, abstract: The CAPM provides a single state, single factor, general equilibrium theory of the risk-return relation. However, in the 1960s, Mandelbrot (1963) already observed stock returns to have a very peaked distribution with heavy tails and also periods of persistent volatility, which contradicts the CAPM. In response to these observations, the Conditional CAPM (C-CAPM) has been discussed by several authors. In a C-CAPM investors can price an asset or portfolio conditional on the available information at a point in time. This is done by replacing the unconditional by conditional moments of returns. Statistically, processes of ”Generalized Autoregressive Conditional Heteroscedasticity” (GARCH) can capture the so called ”stylized facts”, some observed by Mandelbrot (1963). GARCH models were developed by Engle (1982) and Bollerslev (1986) and try to model time-varying second moments of asset returns. If a GARCH process is assumed for the disturbance term in a C-CAPM, a GARCH-in mean model (GARCH-M) can be estimated, where the conditional variance or covariance impacts the conditional expectation of (excess) returns. The GARCH-M can model time-varying conditional moments, but also time-varying risk premia and the implied beta factor. As for this seminar paper, I mostly follow the comprehensive dissertation ”Das CAPM mit zeitabhängigen Beta-Faktoren” of Linnenbrink (1998) and the paper of Bollerslev et al. (1988). First, the theoretical foundations of the CAPM, the C-CAPM, GARCH processes and the GARCH-M extension are presented. Then, in the empirical part, I estimate a (univariate) GARCH-M representation of the C-CAPM. I compare its performance to a traditional CAPM with a single stock portfolio of an investor (selected stock: Tesla, Inc.).
Author: Publisher: ISBN: Category : Capital assets pricing model Languages : en Pages :
Book Description
"When risk-factor loadings are time-varying and unobservable, investors are forced to form beliefs about the levels of their loadings. The learning process involved in forming these beliefs has normative implications for asset-pricing tests. This paper develops an equilibrium model of learning about time-varying beta. In the model, the capital asset pricing model (CAPM) works for investors' probability distribution. However, mis-pricing can be observed if econometricians estimate betas without accounting for the investors' learning process. The empirical implication for asset-pricing tests is that the factor loadings must be estimated as latent variables. We provide an empirical application of this methodology to the cross section of returns on ten book-to-market and ten size-sorted portfolios. For these assets, the data do not reject a learning-augmented version of CAPM. This model performs better than other common empirical specifications, including the Fama-French three-factor model"--Federal Reserve Bank of New York web site.
Author: Jean-Pierre Danthine Publisher: Elsevier ISBN: 0080509029 Category : Business & Economics Languages : en Pages : 391
Book Description
The second edition of this authoritative textbook continues the tradition of providing clear and concise descriptions of the new and classic concepts in financial theory. The authors keep the theory accessible by requiring very little mathematical background. First edition published by Prentice-Hall in 2001- ISBN 0130174467. The second edition includes new structure emphasizing the distinction between the equilibrium and the arbitrage perspectives on valuation and pricing, as well as a new chapter on asset management for the long term investor. "This book does admirably what it sets out to do - provide a bridge between MBA-level finance texts and PhD-level texts.... many books claim to require little prior mathematical training, but this one actually does so. This book may be a good one for Ph.D students outside finance who need some basic training in financial theory or for those looking for a more user-friendly introduction to advanced theory. The exercises are very good." --Ian Gow, Student, Graduate School of Business, Stanford University Completely updated edition of classic textbook that fills a gap between MBA level texts and PHD level texts Focuses on clear explanations of key concepts and requires limited mathematical prerequisites Updates includes new structure emphasizing the distinction between the equilibrium and the arbitrage perspectives on valuation and pricing, as well as a new chapter on asset management for the long term investor
Author: Eric Ghysels Publisher: ISBN: Category : Languages : en Pages :
Book Description
There is now considerable evidence suggesting that estimated betas of unconditional CAPM models exhibit statistically significant time variation. Therefore, many have advocated the use of conditional CAPM models. If we succeed in capturing the dynamics of beta risk, we are sure to outperform constant beta models. However, if the beta risk is inherently misspecified there is a real possibility that we commit serious pricing errors, potentially larger than with a constant traditional beta model. In this paper we show that this is indeed the case, namely that pricing errors with constant traditional beta models are smaller than with conditional CAPM models.
Author: Devraj Basu
Author: Devraj Basu
Author: Tobias Adrian
Author: Aslihan Altay Salih
Author: Groupe HEC (Jouy-en-Josas, Yvelines). Direction de la recherche
Author: Gilles Dufrénot
Author: Ly H. Anh
Author: Sebastian Wilde
Author: 
Author: Jean-Pierre Danthine
Author: Eric Ghysels