Forecasting Stock Returns

By David E. Rapach, Guofu Zhou. 2013

269 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/6e31843948401ee673635ee93731eb0e3c6fe208

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Citations in the corpus

Short Interest and Aggregate Stock Returns (2016, background): “…during the Global Financial Crisis is consistent with the recent findings of Rapach, Strauss, and Zhou (2010), Henkel, Martin, and Nardari (2011), Rapach and Zhou (2013), and Neely, Rapach, Tu, and Zhou (2014), who show that aggregate stock return predictability and the associated utility gains…”
Complete subset regressions (2013, methodology): “For example, Rapach et al. (2010) consider equal-weighted combinations of all possible univariate equity premium models and find that they produce better forecasts of stock returns than a simple no-predictability model.”
Modelling the volatility of the Dow Jones Islamic Market World Index using a fractionally integrated time-varying GARCH (FITVGARCH) model (2014, result): “Given that better in-sample fit does not necessarily translate into superior out-of-sample forecasts (Rapach and Zhou, 2013), an immediate extension of the current study would be to compare the forecasting ability of the FIGARCH and FITVGARCH, and possibly other set of standard models describing…”
Optimal robust reinsurance-investment strategies for insurers with mean reversion and mispricing (2018, methodology): “…processes are described by mean-reverting (MR) models, which are given in the empirical literature on real market, see Chapter 20 in Cochrane (2001) and Rapach and Zhou (2013); they play an important role in the portfolio by providing for the possibility of time-varying investment opportunities.”
Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach (2017, unknown): “In addition, it would be interesting to explore whether the results hold over an out-of-sample period, since in-sample predictability does not necessarily guarantee forecasting gains (Rapach and Zhou 2013).”
Has oil price predicted stock returns for over a century (2015, background): “Further, our primary focus in this paper is the out-ofsample predictive ability of oil price and its component for stock returns, given the widely held view that predictive models require out-of-sample validation (Rapach and Zhou, 2013).”