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Bayesian Analysis Of A Variance Decomposition For Stock Returns
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Book Synopsis A Bayesian Analysis of a Variance Decomposition for Stock Returns by : Burton Hollifield
Download or read book A Bayesian Analysis of a Variance Decomposition for Stock Returns written by Burton Hollifield and published by . This book was released on 2009 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: We apply Bayesian methods to study a common VAR-based approach for decomposing the variance of excess stock returns into components reflecting news about future excess stock returns, future real interest rates, and future dividends. We develop a new prior elicitation strategy which involves expressing beliefs about the components of the variance decomposition. Previous Bayesian work elicited priors from the difficult-to-interpret parameters of the VAR. With a commonly used data set, we find that the posterior standard deviations for the variance decomposition based on these previously used priors, including quot;non-informativequot; limiting cases, are much larger than classical standard errors based on asymptotic approximations. Therefore, the non-informative researcher remains relatively uninformed about the variance decomposition after observing the data. We show the large posterior standard deviations arise because the quot;non-informativequot; prior is implicitly very informative in a highly undesirable way. However, reasonably informative priors using our elicitation method allow for much more precise inference about components of the variance decomposition.
Book Synopsis Bayesian Analysis of a Variance Decomposition for Stock Returns by :
Download or read book Bayesian Analysis of a Variance Decomposition for Stock Returns written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Finance Division of the Faculty of Commerce and Business Administration at the University of British Columbia in Vancouver, British Columbia, Canada, presents the full text of a working paper entitled " A Bayesian Analysis of a Variance Decomposition for Stock Returns," by Burton Hollifield, Gary Koop, and Kai Li. The paper discusses using Bayesian methods to study the variance of excess stock returns.
Book Synopsis A variance decomposition for stock returns by : John Y. Campbell
Download or read book A variance decomposition for stock returns written by John Y. Campbell and published by . This book was released on 1990 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on the Predictability and Volatility of Returns in the Stock Market by : Ruojun Wu
Download or read book Essays on the Predictability and Volatility of Returns in the Stock Market written by Ruojun Wu and published by . This book was released on 2008 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation studies the effect of parameter uncertainty on the return predictability and volatility of the stock market. The first two chapters focus on the decomposition of market volatility, and the third chapter studies the return predictability. When facing imperfect information, the investors tend to form a learning scheme that encompasses both historical data and prior beliefs. In the variance decomposition framework, the introducing of learning directly impacts the way that return forecasts are revised and consequently the relative component of market volatility based on these forecasts, namely the price movements from revision on future discount rates and those from future cash flows. According to the empirical study in Chapter 1, the former is not necessarily the major driving force of market volatility, which provides an alternative view on what moves stock prices. Learning is modeled and estimated by Bayesian method. Chapter 2 follows the topic in Chapter 1 and studies the role of persistent state variables in return decomposition in order to provide more robust inference on variance decomposition. In Chapter 3 we propose to utilize theoretical constraints to help predict market returns when in sample data is very noisy and creates model uncertainty for the investors. The constraints are also incorporated by Bayesian method. We show in the out-of-sample forecast experiment that models with theoretical constraints produce better forecasts.
Book Synopsis Tactical Industry Allocation and Model Uncertainty by : Manuel Ammann
Download or read book Tactical Industry Allocation and Model Uncertainty written by Manuel Ammann and published by . This book was released on 2013 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: We use Bayesian model averaging to analyze the sample evidence on industry return predictability within the U.S. stock market in the presence of model uncertainty. The posterior analysis shows the importance of inflation and earnings yield in predicting industry returns. The out-of-sample performance of the Bayesian approach is, in general, superior to that of other statistical model selection criteria. However, the out-of-sample forecasting power of a naive iid forecast is similar to the Bayesian forecast. A variance decomposition into model risk, estimation risk, and forecast error shows that model risk is less important than estimation risk.
Book Synopsis What moves the stock and bond markets? a variance decomposition for long-term asset returns by : John Y. Campbell
Download or read book What moves the stock and bond markets? a variance decomposition for long-term asset returns written by John Y. Campbell and published by . This book was released on 1991 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Measuring Capital in the New Economy by : Carol Corrado
Download or read book Measuring Capital in the New Economy written by Carol Corrado and published by University of Chicago Press. This book was released on 2009-02-15 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the accelerated technological advances of the past two decades continue to reshape the United States' economy, intangible assets and high-technology investments are taking larger roles. These developments have raised a number of concerns, such as: how do we measure intangible assets? Are we accurately appraising newer, high-technology capital? The answers to these questions have broad implications for the assessment of the economy's growth over the long term, for the pace of technological advancement in the economy, and for estimates of the nation's wealth. In Measuring Capital in the New Economy, Carol Corrado, John Haltiwanger, Daniel Sichel, and a host of distinguished collaborators offer new approaches for measuring capital in an economy that is increasingly dominated by high-technology capital and intangible assets. As the contributors show, high-tech capital and intangible assets affect the economy in ways that are notoriously difficult to appraise. In this detailed and thorough analysis of the problem and its solutions, the contributors study the nature of these relationships and provide guidance as to what factors should be included in calculations of different types of capital for economists, policymakers, and the financial and accounting communities alike.
Download or read book IBSS: Economics: 1993 Vol 42 written by and published by Psychology Press. This book was released on 1994 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This bibliography lists the most important works published in economics in 1993. Renowned for its international coverage and rigorous selection procedures, the IBSS provides researchers and librarians with the most comprehensive and scholarly bibliographic service available in the social sciences. The IBSS is compiled by the British Library of Political and Economic Science at the London School of Economics, one of the world's leading social science institutions. Published annually, the IBSS is available in four subject areas: anthropology, economics, political science and sociology.
Download or read book Return Decomposition written by Long Chen and published by . This book was released on 2008 with total page 45 pages. Available in PDF, EPUB and Kindle. Book excerpt: A crucial issue in asset pricing is to understand the relative importance of discount rate (DR) news and cash flow (CF) news in driving the time-series and cross-sectional variations of stock returns. Many studies directly estimate the DR news but back out the CF news as the residual. We argue that this approach has a serious limitation because the DR news cannot be accurately measured due to the small predictive power, and the CF news, as the residual, inherits the large misspecification error of the DR news. We apply this residual-based decomposition approach to Treasury bonds and equities, and find results that are either counter-intuitive or unrobust. Potential solutions, including modeling both DR news and CF news directly, the Bayesian model averaging approach, and the principal component analysis, are explored.
Book Synopsis Stock Returns and Real Growth by : Qiao Yang
Download or read book Stock Returns and Real Growth written by Qiao Yang and published by . This book was released on 2019 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: This study constructs a Bayesian nonparametric model to investigate whether stock market returns predict real economic growth. Unlike earlier studies, our use of an infinite hidden Markov model enables parameters to be time-varying across an infinite number of Markov-switching states estimated from data rather than fixed like a prior. Our model exhibits significantly greater accuracy in out-of-sample density forecasts. We uncover strong evidence of the time-varying power of lagged stock returns to predict economic growth.
Book Synopsis Empirical Asset Pricing by : Wayne Ferson
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.
Book Synopsis Empirical Asset Pricing by : Wayne Ferson
Download or read book Empirical Asset Pricing written by Wayne Ferson and published by MIT Press. This book was released on 2019-03-26 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.
Book Synopsis Nonlinear Time Series Analysis of Economic and Financial Data by : Philip Rothman
Download or read book Nonlinear Time Series Analysis of Economic and Financial Data written by Philip Rothman and published by Springer Science & Business Media. This book was released on 1999-01-31 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Time Series Analysis of Economic and Financial Data provides an examination of the flourishing interest that has developed in this area over the past decade. The constant theme throughout this work is that standard linear time series tools leave unexamined and unexploited economically significant features in frequently used data sets. The book comprises original contributions written by specialists in the field, and offers a combination of both applied and methodological papers. It will be useful to both seasoned veterans of nonlinear time series analysis and those searching for an informative panoramic look at front-line developments in the area.
Download or read book Finance India written by and published by . This book was released on 2004-07 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Stock Return Predictability by : Martijn Cremers
Download or read book Stock Return Predictability written by Martijn Cremers and published by . This book was released on 2002 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Attempts to characterize stock return predictability have generated a plethora of papers documenting the ability of various variables to explain conditional expected returns. However, there is little consensus on what the important conditioning variables are, giving rise to a great deal of model uncertainty and data snooping fears. In this paper, we introduce a new methodology that explicitly takes the model uncertainty into account by comparing all possible models simultaneously and in which the priors are calibrated to reflect economically meaningful prior information. Therefore, our approach minimizes data snooping given the information set and the priors. We compare the prior views of a skeptic and a confident investor. The data imply posterior probabilities that are in general more supportive of stock return predictability than the priors for both types of investors, over a wide range of prior views. Furthermore, the stalwarts such as dividends and past returns do not perform well. The out-of- sample results for the Bayesian average models show improved forecasts relative to the classical statistical model selection methods, are consistent with the in-sample results and show some, albeit small, evidence of predictability.
Download or read book JOURNAL OF FINANCIAL ECONOMICS written by and published by . This book was released on 2002 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Asset Pricing Theory by : Costis Skiadas
Download or read book Asset Pricing Theory written by Costis Skiadas and published by Princeton University Press. This book was released on 2009-02-09 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Asset Pricing Theory is an advanced textbook for doctoral students and researchers that offers a modern introduction to the theoretical and methodological foundations of competitive asset pricing. Costis Skiadas develops in depth the fundamentals of arbitrage pricing, mean-variance analysis, equilibrium pricing, and optimal consumption/portfolio choice in discrete settings, but with emphasis on geometric and martingale methods that facilitate an effortless transition to the more advanced continuous-time theory. Among the book's many innovations are its use of recursive utility as the benchmark representation of dynamic preferences, and an associated theory of equilibrium pricing and optimal portfolio choice that goes beyond the existing literature. Asset Pricing Theory is complete with extensive exercises at the end of every chapter and comprehensive mathematical appendixes, making this book a self-contained resource for graduate students and academic researchers, as well as mathematically sophisticated practitioners seeking a deeper understanding of concepts and methods on which practical models are built. Covers in depth the modern theoretical foundations of competitive asset pricing and consumption/portfolio choice Uses recursive utility as the benchmark preference representation in dynamic settings Sets the foundations for advanced modeling using geometric arguments and martingale methodology Features self-contained mathematical appendixes Includes extensive end-of-chapter exercises
