Download or read book Dynamic Factor Model and Predictability of Stock Returns written by Alexandre Kopoin and published by . This book was released on 2013 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Multi dynamic factor Model for Stock Returns written by Victor K. Ng and published by . This book was released on 1991 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Time Series in High Dimension the General Dynamic Factor Model written by Marc Hallin and published by World Scientific Publishing Company. This book was released on 2020-03-30 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides an extensive account of the so-called General Dynamic Factor Model methods. The topics covered include: asymptotic representation problems, estimation, forecasting, identification of the number of factors, identification of structural shocks, volatility analysis, and applications to macroeconomic and financial data.

Download or read book A Structural Dynamic Factor Model for Daily Global Stock Market Returns written by Oliver Linton and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Statistics 9 written by José M. Bernardo and published by Oxford University Press. This book was released on 2011-10-06 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian statistics is a dynamic and fast-growing area of statistical research and the Valencia International Meetings provide the main forum for discussion. These resulting proceedings form an up-to-date collection of research.

Download or read book Dynamic Factor Models written by Jörg Breitung and published by . This book was released on 2016 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: Factor models can cope with many variables without running into scarce degrees of freedom.

Download or read book The Predictability of Stock Returns written by Zhong-guo Zhou and published by . This book was released on 1993 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Stock Return Predictability written by Arthur Ritter and published by GRIN Verlag. This book was released on 2015-05-27 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paper (postgraduate) from the year 2015 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, grade: 17 (1,3), University of St Andrews (School of Management), course: Investment and Portfolio Management, language: English, abstract: Empirical evidence of stock return predictability obtained by financial ratios or macroeconomic factors has received substantial attention and remains a controversial topic to date. This is no surprise given that the existence of return predictability is not only of interest to practitioners but also introduces severe implications for financial models of risk and return. Founded on the assumption of efficient capital markets, research on capital asset pricing models has instigated this emergence of stock return predictability factors. Analysing these factors categorically, this paper will provide a balanced discussion of advocates as well as sceptics of stock return predictability. This essay will commence by firstly outlining the fundamental assumptions of an efficient capital market and its implications for return predictability. Subsequently, a thorough focus will be placed on the most significant predictability factors, including fundamental financial ratios and macroeconomic indicators as well as the validity of sampling methods used to attain return forecasts. Lastly this essay will reflect on the findings while proposing areas of further research.

Download or read book Generalized Dynamic Factor Model GARCH Exploiting Multivariate Information for Univariate Prediction written by and published by . This book was released on 2007 with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns. In this financial analysis, both these components are modeled as a GARCH.We compare GDFM+GARCH and standard GARCH performance on two samples up to 171 series, providing one-step-ahead volatility predictions of returns. The GDFM+GARCH model outperforms the standard GARCH in most cases. These results are robust with respect to different volatility proxies. -- Dynamic Factors ; GARCH ; volatility forecasting

Download or read book Factor Structure of Cross Sectional Stock Returns written by Yuxiao Jiao and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a unsupervised learning approach to construct latent factor model for cross sectional asset returns where firm characteristics instrument for the dynamic factor exposures. Firm characteristics are clustered with consideration to their prior economic content. Our method can also be viewed as a constrained version of Instrumented Principal Components Analysis (IPCA) model by Kelly et al (2019). We apply the method to a set of 94 firm characteristics to form clustered factor models. The model outperforms all benchmark models, and outperforms IPCA latent factor model out-of-sample.

Download or read book Conditional Factor Models and Return Predictability written by Alex P. Taylor and published by . This book was released on 2005 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper develops a new approach to examining the time variation of risk premia within the framework of conditional asset pricing models. By combining conditional factor models with approximate present-value relationships we derive a linear relationship between the log stock price and investors' expectations of future factor loadings, risk premia, and cashlows. This framework allows us to estimate conditional risk premia from a cross-sectional regression of log prices on proxies for expected factor loadings and cashflows. We apply this technique to various factor specifications including the CAPM, the three factors advocated by Fama and French (1996), and a five-factor model with economically motivated factors similar to Chen et al. (1986). Consistent with rational pricing we find that, for the majority of the risk factors, the estimated risk premia contain significant information about the future expected returns of the factor portfolios over the sample 1938-2004. Our framework abstracts from the use of ad-hoc conditioning variables, and offers a theoretically appealing approach to modelling the predictable components of stock returns. In recent samples (1978-2004) our estimates of the market risk premium prove to be better forecasters of market returns than the dividend-price ratio and other commonly used forecasting variables. Results from the economic factor model provide evidence that current levels of treasury and corporate bond yields are embedded in the cross section of equity market prices.

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 Dynamic Factor Model with Infinite Dimensional Factor Space written by Mario Forni and published by . This book was released on 2016 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper compares the pseudo real-time forecasting performance of three Dynamic Factor Models: (i) The standard principal-component model, Stock and Watson (2002a), (ii) The model based on generalized principal components, Forni et al. (2005), (iii) The model recently proposed in Forni et al. (2015b) and Forni et al. (2015a). We employ a large monthly dataset of macroeconomic and financial time series for the US economy, which includes the Great Moderation, the Great Recession and the subsequent recovery. Using a rolling window for estimation and prediction, we find that (iii) neatly outperforms (i) and (ii) in the Great Moderation period for both Industrial Production and Inflation, and for Inflation over the full sample. However, (iii) is outperfomed by (i) and (ii) over the full sample for Industrial Production.

Download or read book Dynamic Factors and the Source of Momentum Profits written by Tong Yao and published by . This book was released on 2006 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper uses the dynamic principal component method to estimate a dynamic factor model for stock returns and identify the source of momentum profits. We find that momentum is a systematic-return phenomenon - momentum profits are primarily due to stock return response to a small number of dynamic systematic factors, and the contribution by the idiosyncratic component of stock return is statistically insignificant. We also find that the estimated dynamic factors can be partially related to observed economic factors.

Download or read book Complex Systems in Finance and Econometrics written by Robert A. Meyers and published by Springer Science & Business Media. This book was released on 2010-11-03 with total page 919 pages. Available in PDF, EPUB and Kindle. Book excerpt: Finance, Econometrics and System Dynamics presents an overview of the concepts and tools for analyzing complex systems in a wide range of fields. The text integrates complexity with deterministic equations and concepts from real world examples, and appeals to a broad audience.

Download or read book Portfolio Diversification written by Francois-Serge Lhabitant and published by Elsevier. This book was released on 2017-09-26 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Portfolio Diversification provides an update on the practice of combining several risky investments in a portfolio with the goal of reducing the portfolio's overall risk. In this book, readers will find a comprehensive introduction and analysis of various dimensions of portfolio diversification (assets, maturities, industries, countries, etc.), along with time diversification strategies (long term vs. short term diversification) and diversification using other risk measures than variance. Several tools to quantify and implement optimal diversification are discussed and illustrated. Focuses on portfolio diversification across all its dimensions Includes recent empirical material that was created and developed specifically for this book Provides several tools to quantify and implement optimal diversification

Download or read book A Latent Factor Model with Global Country and Industry Shocks for International Stock Returns written by Mr.Marco Del Negro and published by INTERNATIONAL MONETARY FUND. This book was released on 2005-03-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We estimate a latent factor model that decomposes international stock returns into global, country-, and industry-specific shocks and allows for stock-specific exposures to these shocks. We find that across stocks there is substantial dispersion in these exposures, which is partly explained by the extent to which firms operate across countries. We show that portfolios consisting of stocks with low exposures to country shocks achieve substantial variance reduction relative to the global market, both in- and out-of-sample. The shock exposures are thus a stock-selection device for international portfolio diversification.