Do Return Prediction Models Add Economic Value

We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.

[1]  Wayne E. Ferson,et al.  Are the Latent Variables in Time‐Varying Expected Returns Compensation for Consumption Risk? , 1990 .

[2]  Allan Timmermann,et al.  Instability of Return Prediction Models , 2005 .

[3]  Joseph P. Romano,et al.  The stationary bootstrap , 1994 .

[4]  F. Peracchi,et al.  The Conditional Distribution of Excess Returns: An Empirical Analysis , 1994 .

[5]  R. Engle,et al.  On the Economic Sources of Stock Market Volatility , 2008 .

[6]  A. Deaton.  Consumption , Aggregate Wealth , and Expected Stock Returns , 2008 .

[7]  Guofu Zhou,et al.  Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy , 2009 .

[8]  Stijn Van Nieuwerburgh,et al.  Reconciling the Return Predictability Evidence , 2006 .

[9]  René Garcia,et al.  Empirical Likelihood Estimators for Stochastic Discount Factors , 2008 .

[10]  Luis M. Viceira,et al.  Spreading the Wealth Around: Reflections Inspired by Joe the Plumber , 1998 .

[11]  I. Welch,et al.  A Comprehensive Look at the Empirical Performance of Equity Premium Prediction II , 2004, SSRN Electronic Journal.

[12]  J. Campbell.  Stock Returns and the Term Structure , 1985 .

[13]  M. Lettau,et al.  Reconciling the Return Predictability EvidenceThe Review of Financial Studies: Reconciling the Return Predictability Evidence , 2008 .

[14]  E. Fama,et al.  BUSINESS CONDITIONS AND EXPECTED RETURNS ON STOCKS AND BONDS , 1989 .

[15]  E. Ghysels,et al.  Série Scientifique Scientific Series Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies , 2022 .

[16]  M. Halling,et al.  Predictive Regressions with Time-Varying Coefficients , 2008 .

[17]  John Geweke,et al.  A note on some limitations of CRRA utility , 2001 .

[18]  P. Bossaerts,et al.  Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn? , 1999 .

[19]  R. C. Merton,et al.  On Estimating the Expected Return on the Market: An Exploratory Investigation , 1980 .

[20]  Guofu Zhou,et al.  Forecasting Stock Returns , 2013 .

[21]  S. B. Thompson,et al.  Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average? , 2008 .

[22]  G. Schwert.  Why Does Stock Market Volatility Change Over Time? , 1988 .

[23]  Andrew Ang,et al.  Stock Return Predictability: Is it There? , 2001 .

[24]  Peter F. Christoffersen.  Evaluating Interval Forecasts , 1998 .

[25]  R. Stambaugh,et al.  On the Predictability of Stock Returns: An Asset-Allocation Perspective , 1995 .

[26]  Nicholas G. Polson,et al.  Sequential learning , predictive regressions , and optimal p ortfolio returns PRELIMINARY , 2009 .

[27]  Campbell R. Harvey,et al.  The Risk and Predictability of International Equity Returns , 1993 .

[28]  Turan G. Bali,et al.  World Market Risk, Country-Specific Risk and Expected Returns in International Stock Markets , 2009 .

[29]  Gianni Amisano,et al.  Comparing Density Forecasts via Weighted Likelihood Ratio Tests , 2007 .

[30]  L. Glosten,et al.  On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks , 1993 .

[31]  E. Fama,et al.  Dividend yields and expected stock returns , 1988 .

[32]  Peter Christoffersen,et al.  Série Scientifique Scientific Series the Importance of the Loss Function in Option Valuation the Importance of the Loss Function in Option Valuation , 2022 .

[33]  A. Timmermann,et al.  Predictability of Stock Returns: Robustness and Economic Significance , 1995 .

[34]  Turan G. Bali,et al.  The role of autoregressive conditional skewness and kurtosis in the estimation of conditional VaR , 2008 .

[35]  R. Shiller,et al.  The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors , 1986 .

[36]  R. Engle,et al.  CAViaR , 1999 .

[37]  Ivana Komunjer,et al.  Quasi-maximum likelihood estimation for conditional quantiles , 2005 .