Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy

被引:959
作者
Rapach, David E. [2 ]
Strauss, Jack K. [2 ]
Zhou, Guofu [1 ]
机构
[1] Washington Univ, John M Olin Sch Business, St Louis, MO 63130 USA
[2] St Louis Univ, St Louis, MO 63103 USA
关键词
BOOK-TO-MARKET; STOCK RETURN PREDICTABILITY; RISK-FACTORS; TESTS; INFLATION; YIELD; CONSUMPTION; ACCURACY; MODELS; RATIOS;
D O I
10.1093/rfs/hhp063
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
Welch and Goyal (2008) find that numerous economic variables with in-sample predictive ability for the equity premium fail to deliver consistent out-of-sample forecasting gains relative to the historical average. Arguing that model uncertainty and instability seriously impair the forecasting ability of individual predictive regression models, we recommend combining individual forecasts. Combining delivers statistically and economically significant out-of-sample gains relative to the historical average consistently over time. We provide two empirical explanations for the benefits of forecast combination: (i) combining forecasts incorporates information from numerous economic variables while substantially reducing forecast volatility; (ii) combination forecasts are linked to the real economy. (JEL C22, C53, G11, G12)
引用
收藏
页码:821 / 862
页数:42
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