Download or read book A Bayesian Approach to the Estimation of the Capital Asset Pricing Model written by Kok Phun Yap and published by . This book was released on 1993 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Methods in Finance written by Svetlozar T. Rachev and published by John Wiley & Sons. This book was released on 2008-02-13 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Methods in Finance provides a detailed overview of the theory of Bayesian methods and explains their real-world applications to financial modeling. While the principles and concepts explained throughout the book can be used in financial modeling and decision making in general, the authors focus on portfolio management and market risk management—since these are the areas in finance where Bayesian methods have had the greatest penetration to date.
Download or read book Bayesian Estimation of Capital Asset Pricing Models with Many Assets written by Michael Smith and published by . This book was released on 1999 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Bayesian Estimation of Capital Asset Pricing Models with Many Assets written by Michael S. Smith and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Bayesian Approach to Estimate the Time Varying Security Beta written by Cheng F. Lee and published by . This book was released on 1978 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Machine Learning in Asset Pricing written by Stefan Nagel and published by Princeton University Press. This book was released on 2021-05-11 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.
Download or read book Financial Risk Management with Bayesian Estimation of GARCH Models written by David Ardia and published by Springer Science & Business Media. This book was released on 2008-05-08 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents in detail methodologies for the Bayesian estimation of sing- regime and regime-switching GARCH models. These models are widespread and essential tools in n ancial econometrics and have, until recently, mainly been estimated using the classical Maximum Likelihood technique. As this study aims to demonstrate, the Bayesian approach o ers an attractive alternative which enables small sample results, robust estimation, model discrimination and probabilistic statements on nonlinear functions of the model parameters. The author is indebted to numerous individuals for help in the preparation of this study. Primarily, I owe a great debt to Prof. Dr. Philippe J. Deschamps who inspired me to study Bayesian econometrics, suggested the subject, guided me under his supervision and encouraged my research. I would also like to thank Prof. Dr. Martin Wallmeier and my colleagues of the Department of Quantitative Economics, in particular Michael Beer, Roberto Cerratti and Gilles Kaltenrieder, for their useful comments and discussions. I am very indebted to my friends Carlos Ord as Criado, Julien A. Straubhaar, J er ^ ome Ph. A. Taillard and Mathieu Vuilleumier, for their support in the elds of economics, mathematics and statistics. Thanks also to my friend Kevin Barnes who helped with my English in this work. Finally, I am greatly indebted to my parents and grandparents for their support and encouragement while I was struggling with the writing of this thesis.
Download or read book Estimating the Parameters of the Capital Asset Pricing Model CAPM written by Michael R. Gibbons and published by . This book was released on 1980 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Resurrecting the Capital Asset Pricing Model written by Hammad Siddiqi and published by . This book was released on 2016 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: The capital asset pricing model is generally considered incapable of explaining the stock market behavior. I show that this conclusion is premature, and incorporating a pragmatic approach to approximating optimal Bayesian inference in the model resurrects CAPM. The adjusted CAPM internalizes the well-known size, value, and momentum effects, high-alpha-of-low-beta-stocks, accruals, low volatility anomaly, stock-split anomaly, and reverse stock-split anomaly. The market equity premium is also larger with anchoring. Immediate applications of the adjusted CAPM include improved cost of equity calculation, and improved evaluation of managed portfolio performance.
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-12 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Bayesian Estimation of Dynamic Asset Pricing Models with Informative Observations written by Andras Fulop and published by . This book was released on 2018 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: In dynamic asset pricing models, when the model structure becomes complex and derivatives data are introduced in estimation, traditional Bayesian MCMC methods converge slowly, are difficult to design efficient proposals for parameters, and have large computational cost. We propose a two-stage sequential Monte Carlo sampler based on common random numbers and a smooth particle filter. This method is robust to potential model misspecification and can deliver almost full-likelihood-based inference at a much smaller computational cost. It is applied to estimate a class of volatility models that take into account price-volatility co-jumps, non-affineness, and self-excitation. An empirical study using S&P 500 index and variance swap rates shows that both non-affineness and self-excitation need to be introduced in modeling volatility dynamics.
Download or read book Bayes and Empirical Bayes Methods for Data Analysis Second Edition written by Bradley P. Carlin and published by Chapman and Hall/CRC. This book was released on 2000-06-22 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, Bayes and empirical Bayes (EB) methods have continued to increase in popularity and impact. Building on the first edition of their popular text, Carlin and Louis introduce these methods, demonstrate their usefulness in challenging applied settings, and show how they can be implemented using modern Markov chain Monte Carlo (MCMC) methods. Their presentation is accessible to those new to Bayes and empirical Bayes methods, while providing in-depth coverage valuable to seasoned practitioners. With its broad appeal as a text for those in biomedical science, education, social science, agriculture, and engineering, this second edition offers a relatively gentle and comprehensive introduction for students and practitioners already familiar with more traditional frequentist statistical methods. Focusing on practical tools for data analysis, the book shows how properly structured Bayes and EB procedures typically have good frequentist and Bayesian performance, both in theory and in practice.
Download or read book A Multivariate GARCH in Mean Estimation of the Capital Asset Pricing Model written by S. G. Hall and published by . This book was released on 1988 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A New Model of Capital Asset Prices written by James W. Kolari and published by Springer Nature. This book was released on 2021-03-01 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes a new capital asset pricing model dubbed the ZCAPM that outperforms other popular models in empirical tests using US stock returns. The ZCAPM is derived from Fischer Black’s well-known zero-beta CAPM, itself a more general form of the famous capital asset pricing model (CAPM) by 1990 Nobel Laureate William Sharpe and others. It is widely accepted that the CAPM has failed in its theoretical relation between market beta risk and average stock returns, as numerous studies have shown that it does not work in the real world with empirical stock return data. The upshot of the CAPM’s failure is that many new factors have been proposed by researchers. However, the number of factors proposed by authors has steadily increased into the hundreds over the past three decades. This new ZCAPM is a path-breaking asset pricing model that is shown to outperform popular models currently in practice in finance across different test assets and time periods. Since asset pricing is central to the field of finance, it can be broadly employed across many areas, including investment analysis, cost of equity analyses, valuation, corporate decision making, pension portfolio management, etc. The ZCAPM represents a revolution in finance that proves the CAPM as conceived by Sharpe and others is alive and well in a new form, and will certainly be of interest to academics, researchers, students, and professionals of finance, investing, and economics.
Download or read book Bayesian Estimation of a DSGE Model with Asset Prices written by Martin Kliem and published by . This book was released on 2016 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a novel Bayesian method for estimating dynamic stochastic general equilibrium (DSGE) models subject to a constrained posterior distribution of the implied Sharpe ratio. We apply our methodology to a DSGE model with habit formation in consumption and leisure, using an estimate of the Sharpe ratio to construct the constraint. We show that the constrained estimation produces a quantitative model with both reasonable asset-pricing as well as business-cycle implications.
Download or read book Testing the Capital Asset Pricing Model Efficiently Under Elliptical Symmetry written by Douglas J. Hodgson and published by . This book was released on 2008 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive estimation; capital asset pricing model; efficiency.
Download or read book The Capital Asset Pricing Model written by and published by Bookboon. This book was released on with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt:
