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

By David E. Rapach, Jack Strauss, Guofu Zhou. 2010

1,487 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

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Citations in the corpus

Deep Learning for Predicting Asset Returns (2018, methodology): “Improved methodologies have been suggested by Campbell and Thompson (2007), Rapach et al. (2010) and Harvey et al. (2016) and, more recently, Feng et al. (2017) and Kozak et al. (2017).”
Predicting market returns using aggregate implied cost of capital (2013, neutral): “The reason for choosing the first forecast period is that existing studies such as Welch and Goyal (2008) and Rapach, Strauss, and Zhou (2010) have shown that many commonly used forecasting variables perform poorly starting in the late 1990s.”
Asset Pricing in Production Economies with Extrapolative Expectations (2015, background): “, Goyal and Welch, 2008 ), the trend of the literature favors such variables having power to predict returns (e.g., Ang and Bekaert, 2007; Campbell and Thompson, 2008; Cochrane, 2008; Rapach et al., 2010).”
Linear Hypothesis Testing in Dense High-Dimensional Linear Models (2016, methodology): “Rapach et al. (2010) use the model combination approach by taking the simple average of 14 univariate linear models.”
The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity (2010, background): “…drawn from our in-sample inferences, the out-of-sample R2 statistic, calculated both with expanding and rolling windows, is typically higher than those reported in Campbell and Thompson (2008), Goyal and Welch (2008), Rapach, Strauss, and Zhou (2010), and Henkel, Martin, and Nardari (2010).”
Short Interest and Aggregate Stock Returns (2016, background): “Specifically, as in Campbell and Thompson (2008), Rapach, Strauss, and Zhou (2010), and Ferreira and Santa-Clara (2011), we consider a mean-variance investor who 25The Harvey, Leybourne, and Taylor (2009) tl statistics are 2.12, 2.16, and 2.26 at the 10%, 5%, and 1% levels, respectively, none of…”
Forecasting commodity price indexes using macroeconomic and financial predictors (2014, background): “The evidence from stock markets presented by Henkel, Martin, and Nardari (2011) and Rapach, Strauss, and Zhou (2010) suggests that the predictability of stock returns is largely confined to economic recessions.”
Superforecasting: The Art and Science of Prediction (2015, background): “Such a modelling strategy is fairly common today (see for instance [3], for an application of this approach in the equity premium forecasting literature, or [4,5] in the context of exchange rate forecasting and equilibrium credit modelling).”
Does the choice of estimator matter when forecasting returns (2012, result): “Our approach is similar to the one of Rapach et al. (2010), Campbell and Thompson (2008), and Marquering and Verbeek (2004).”