Forecasting the equity risk premium with frequency-decomposed predictors
Gonçalo Faria () and
Fabio Verona ()
No 6, Working Papers de Economia (Economics Working Papers) from Católica Porto Business School, Universidade Católica Portuguesa
We show that the out-of-sample forecast of the equity risk premium can be significantly improved by taking into account the frequency-domain relationship between the equity risk premium and several potential predictors. We consider fifteen predictors from the existing literature, for the out-of-sample forecasting period from January 1990 to December 2014. The best result achieved for individual predictors is a monthly out-of-sample R2 of 2.98 % and utility gains of 549 basis points per year for a mean-variance investor. This performance is improved even further when the individual forecasts from the frequency- decomposed predictors are combined. These results are robust for different subsamples, including the Great Moderation period, the Great Financial Crisis period and, more generically, periods of bad, normal and good economic growth. The strong and robust performance of this method comes from its ability to disentangle the information aggregated in the original time series of each variable, which allows to isolate the frequencies of the predictors with the highest predictive power from the noisy parts.
Keywords: predictability; equity risk premium; frequency domain; discrete wavelets (search for similar items in EconPapers)
JEL-codes: C58 G11 G12 G17 (search for similar items in EconPapers)
Pages: 39 pages
New Economics Papers: this item is included in nep-ets, nep-for and nep-upt
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Working Paper: Forecasting the equity risk premium with frequency-decomposed predictors (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:cap:wpaper:062016
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