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 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 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 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 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:
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 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 On the Out of sample Predictability of Stock Market Returns written by Hui Guo and published by . This book was released on 2002 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Reconciling the Return Predictability Evidence In Sample Forecasts Out of Sample Forecasts and Parameter Instability written by Stijn Van Nieuwerburgh and published by . This book was released on 2008 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence of stock return predictability by financial ratios is still controversial, as documented by inconsistent results for in-sample and out-of-sample regressions and by substantial parameter instability. This paper shows that these seemingly incompatible results can be reconciled if the assumption of a fixed steady-state mean of the economy is relaxed. We find strong empirical evidence in support of shifts in the steady-state and propose simple methods to adjust financial ratios for such shifts. The forecasting relationships of adjusted price ratios and future returns is statistically significant, stable over time, and present in out-of-sample tests. We also show that shifts in the steady-state are responsible for the parameter instability and poor out-of sample performance of unadjusted price ratios that are found in the data. Our conclusions hold for a variety of financial ratios and are robust to changes in the econometric technique used to estimate shifts in the steady-state.
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 The ARCH in Mean Dose Work written by Haibin Xie and published by . This book was released on 2015 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: The predictability of stock market is of great interest to both reseachers and investors. Despite voluminous evidence of in-sample predictability, the out-of-sample predictability of stock returns remains an ongoing debate. In this paper, motivated by both the financial theories and the well documented facts in financial empirical literature, we employ the ARCH-in-Mean model as a benchmark to scrutinize the out-of-sample predictability of the US stock market returns. Empirical studies performed on the S&P500 stock index demonstrate that the ARCH-in-Mean model does report significant out-of-sample forecasts in both statistical and economic sense. The main conclusions of this paper are that 1) the US stock returns is predictable both in-sample and out-of-sample; 2) the predictability of US stock returns can be traced back to both time-varying risk premia and investors' underraction to bad news and overreaction to extremely bad news.
Download or read book Reconciling the Return Predictability Evidence In Sample Forecasts Out of Sample Forecasts and Parameter Instability written by Martin Lettau and published by . This book was released on 2013 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence of stock return predictability by financial ratios is still controversial, as documented by inconsistent results for in-sample and out-of-sample regressions and by substantial parameter instability. This paper shows that these seemingly incompatible results can be reconciled if the assumption of a fixed steady-state mean of the economy is relaxed. We find strong empirical evidence in support of shifts in the steady-state and propose simple methods to adjust financial ratios for such shifts. The forecasting relationships of adjusted price ratios and future returns is statistically significant, stable over time, and present in out-of-sample tests. We also show that shifts in the steady-state are responsible for the parameter instability and poor out-of sample performance of unadjusted price ratios that are found in the data. Our conclusions hold for a variety of financial ratios and are robust to changes in the econometric technique used to estimate shifts in the steady-state.
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 Essays on Return Predictability and Volatility Estimation written by Yuzhao Zhang and published by . This book was released on 2008 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Should We Expect Significant Out of sample Results when Predicting Stock Returns written by Erik Hjalmarsson and published by . This book was released on 2006 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Quantile Regression Approach to Equity Premium Prediction written by Loukia Meligkotsidou and published by . This book was released on 2014 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a quantile regression approach to equity premium forecasting. Robust point forecasts are generated by both fixed and time-varying weighting schemes, thus exploiting the entire distributional information associated with each predictor. Further gains are achieved by incorporating the forecast combination methodology in our quantile regression setting. Our approach using a time-varying weighting scheme delivers statistically and economically significant out-of-sample forecasts relative to the historical average benchmark and the combined mean predictive regression modeling approach.
