Download or read book Equity Premium Prediction Out of sample Reliability and Improvements written by Nenad Ćurčić and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Out of Sample Equity Premium Prediction written by David Rapach and published by . This book was released on 2009 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: While a host of economic variables have been identified in the literature with the apparent in-sample ability to predict the equity premium, Goyal and Welch (2008) find that these variables fail to deliver consistent out-of-sample forecasting gains relative to the historical average. Arguing that substantial model uncertainty and instability seriously impair the forecasting ability of individual predictive regression models, we recommend combining individual model forecasts to improve out-of-sample equity premium prediction. Combining delivers statistically and economically significant out-of-sample gains relative to the historical average on a consistent basis over time. We provide two empirical explanations for the benefits of the forecast combination approach: (i) combining forecasts incorporates information from numerous economic variables while substantially reducing forecast volatility; (ii) combination forecasts of the equity premium are linked to the real economy.
Download or read book Out of Sample Equity Premium Prediction written by Loukia Meligkotsidou and published by . This book was released on 2013 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper extends the complete subset linear regression framework to a quantile regression setting. We employ complete subset combinations of quantile forecasts in order to construct robust and accurate equity premium predictions. Our recursive algorithm that selects, in real time, the best complete subset for each predictive regression quantile succeeds in identifying the best subset in a time- and quantile-varying manner. We show that our approach delivers statistically and economically signi𓏊nt out-of-sample forecasts relative to both the historical average benchmark and the complete subset mean regression approach.
Download or read book Predicting the Equity Premium Out of Sample written by John Y. Campbell and published by . This book was released on 2009 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of variables are correlated with subsequent returns on the aggregate US stock market in the 20th Century. Some of these variables are stock market valuation ratios, others reflect patterns in corporate finance or the levels of short- and long-term interest rates. Amit Goyal and Ivo Welch (2004) have argued that in-sample correlations conceal a systematic failure of these variables out of sample: None are able to beat a simple forecast based on the historical average stock return. In this note we show that forecasting variables with significant forecasting power in-sample generally have a better out-of-sample performance than a forecast based on the historical average return, once sensible restrictions are imposed on thesigns of coefficients and return forecasts. The out-of-sample predictive power is small, but we find that it is economically meaningful. We also show that a variable is quite likely to have poor out-of-sample performance for an extended period of time even when the variable genuinely predicts returns with a stable coefficient.
Download or read book Equity Premium Prediction by Sparse Pooling of Parsimonious State Dependent Models written by Daniel de Almeida and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: A large set of macroeconomic variables have been suggested as equity risk premium predictors in the literature. This paper proposes a forecasting approach for the equity risk premium with two novel features. First, individual month-ahead forecasts are obtained from parsimonious threshold regression models that exploit from one to at most three macroeconomic predictors jointly, and a binary technical indicator as an observable state variable to accommodate expansion versus recession predictability states. Second, a sparse combination of those forecasts is carried out through a robust predictability test. A comprehensive out-of-sample forecast evaluation exercise based on statistical criteria and asset-allocation criteria demonstrates that both features of the proposed approach enable gains versus existing forecasting techniques. However, the state-dependent aspect of the forecasts delivers larger improvements in forecast accuracy that the sparse combination aspect. The results are robust to sub-period analyses, expanding versus rolling estimation windows, and different investors' risk aversion levels.
Download or read book A Comprehensive Look at the Empirical Performance of Equity Premium Prediction written by Ivo Welch and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Our article comprehensively reexamines the performance of variables that have been suggested by the academic literature to be good predictors of the equity premium. We find that by and large, these models have predicted poorly both in-sample (IS) and out-of-sample (OOS) for 30 years now; these models seem unstable, as diagnosed by their out-of-sample predictions and other statistics; and these models would not have helped an investor with access only to available information to profitably time the market.
Download or read book Out of sample Equity Premium Prediction written by Manuel Martino and published by . This book was released on 2011 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Comprehensive Look at the Empirical Performance of Equity Premium Prediction written by Amit Goval and published by . This book was released on 2004 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the historically high equity premium, is it now a good time to invest in the stock market? Economists have suggested a whole range of variables that investors could or should use to predict: dividend price ratios, dividend yields, earnings-price ratios, dividend payout ratios, net issuing ratios, book-market ratios, interest rates (in various guises), and consumption-based macroeconomic ratios (cay). The typical paper reports that the variable predicted well in an *in-sample* regression, implying forecasting ability. Our paper explores the *out-of-sample* performance of these variables, and finds that not a single one would have helped a real-world investor outpredicting the then-prevailing historical equity premium mean. Most would have outright hurt. Therefore, we find that, for all practical purposes, the equity premium has not been predictable, and any belief about whether the stock market is now too high or too low has to be based on theoretical prior, not on the empirically variables we have explored.
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 Out of Sample Equity Premium Predictability and Sample Split Invariant Inference written by Gueorgui I. Kolev and published by . This book was released on 2014 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: For a comprehensive set of 21 equity premium predictors we find dramatic disagreement between out-of-sample predictability results depending on the choice of the sample split date. To resolve this issue we propose reporting in graphical form the out-of-sample predictability criteria for every possible sample split, and two out-of-sample tests that are invariant to the sample split choice. We provide Monte Carlo evidence for the validity of the bootstrap based inference we propose. We find that many investors making decisions in real time could have benefited from conditional predictions. The in-sample, and the sample split invariant out-of-sample mean and maximum tests that we propose, are in broad agreement. We also show how one can construct sample split invariant out-of-sample predictability tests that simultaneously control for data mining across many variables.
Download or read book Data Snooping in Equity Premium Prediction written by Hubert Dichtl and published by . This book was released on 2019 with total page 49 pages. Available in PDF, EPUB and Kindle. Book excerpt: We analyze the performance of a comprehensive set of equity premium forecasting strategies. All strategies were found to outperform the mean in previous academic publications. However, using a multiple testing framework to account for data snooping, our findings support Welch and Goyal (2008) in that almost all equity premium forecasts fail to beat the mean out-of-sample. Only few forecasting strategies that are based on Ferreira and Santa-Clara's (2011) “sum-of-the-parts” approach generate robust and statistically significant economic gains relative to the historical mean even after controlling for data snooping and accounting for transaction costs.
Download or read book Equity Premium Prediction written by Jiahan Li and published by . This book was released on 2016 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper shows that the equity premium is predictable out of sample when we use a predictive regression that conditions on a large set of economic fundamentals, subject to: (i) economic constraints on the sign of coefficients and return forecasts, and (ii) statistical constraints imposed by shrinkage estimation. Equity premium predictability delivers a certainty equivalent return of about 2.7% per year over the benchmark for a mean-variance investor. Our predictive framework outperforms a large group of competing models that also condition on economic fundamentals as well as models that condition on technical indicators.
Download or read book Forecasting the Equity Risk Premium with Frequency Decomposed Predictors written by Gonçalo Faria and published by . This book was released on 2017 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: We show that the out-of-sample forecast of the equity risk premium can be significantly improved by taking into account the frequency-domain relationship between the equity risk premium and several potential predictors. We consider fifteen predictors from the existing literature, for the out-of-sample forecasting period from January 1990 to December 2014. The best result achieved for individual predictors is a monthly out-of-sample R2 of 2.98% and utility gains of 549 basis points per year for a mean-variance investor. This performance is improved even further when the individual forecasts from the frequency-decomposed predictors are combined. These results are robust for different subsamples, including the Great Moderation period, the Great Financial Crisis period and, more generically, periods of bad, normal and good economic growth. The strong and robust performance of this method comes from its ability to disentangle the information aggregated in the original time series of each variable, which allows to isolate the frequencies of the predictors with the highest predictive power from the noisy parts.
Download or read book A Comprehensive Look at the Empirical Performance of Equity Premium Prediction written by Amit Goyal and published by . This book was released on 2006 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economists have suggested a whole range of variables that predict the equity premium: dividend price ratios, dividend yields, earnings-price ratios, dividend payout ratios, corporate or net issuing ratios, book-market ratios, beta premia, interest rates (in various guises), and consumption-based macroeconomic ratios (cay). Our paper comprehensively reexamines the performance of these variables, both in-sample and out-of-sample, as of 2005. We find that [a] over the last 30 years, the prediction models have failed both in-sample and out-of-sample; [b] the models are unstable, in that their out-of-sample predictions have performed unexpectedly poorly; [c] the models would not have helped an investor with access only to information available at the time to time the market.
Download or read book The Equity Risk Premium written by William N. Goetzmann and published by Oxford University Press. This book was released on 2006-11-16 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is the return to investing in the stock market? Can we predict future stock market returns? How have equities performed over the last two centuries? The authors in this volume are among the leading researchers in the study of these questions. This book draws upon their research on the stock market over the past two dozen years. It contains their major research articles on the equity risk premium and new contributions on measuring, forecasting, and timing stock market returns, together with new interpretive essays that explore critical issues and new research on the topic of stock market investing. This book is aimed at all readers interested in understanding the empirical basis for the equity risk premium. Through the analysis and interpretation of two scholars whose research contributions have been key factors in the modern debate over stock market perfomance, this volume engages the reader in many of the key issues of importance to investors. How large is the premium? Is history a reliable guide to predict future equity returns? Does the equity and cash flows of the market? Are global equity markets different from those in the United States? Do emerging markets offer higher or lower equity risk premia? The authors use the historical performance of the world's stock markets to address these issues.
Download or read book Handbook of Computational Econometrics written by David A. Belsley and published by John Wiley & Sons. This book was released on 2009-08-18 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Computational Econometrics examines the state of the art of computational econometrics and provides exemplary studies dealing with computational issues arising from a wide spectrum of econometric fields including such topics as bootstrapping, the evaluation of econometric software, and algorithms for control, optimization, and estimation. Each topic is fully introduced before proceeding to a more in-depth examination of the relevant methodologies and valuable illustrations. This book: Provides self-contained treatments of issues in computational econometrics with illustrations and invaluable bibliographies. Brings together contributions from leading researchers. Develops the techniques needed to carry out computational econometrics. Features network studies, non-parametric estimation, optimization techniques, Bayesian estimation and inference, testing methods, time-series analysis, linear and nonlinear methods, VAR analysis, bootstrapping developments, signal extraction, software history and evaluation. This book will appeal to econometricians, financial statisticians, econometric researchers and students of econometrics at both graduate and advanced undergraduate levels.
Download or read book Two Out of sample Forecasting Models of the Equity Premium written by Thiago de Oliveira Souza and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
