Predictability is time and frequency dependent. We propose a new forecasting method - forecast combination in the frequency domain - that takes this fact into account. With this method we forecast the equity premium and real GDP growth rate. Combining forecasts in the frequency domain produces...

We generalize the Ferreira and Santa-Clara (2011) sum-of-the-parts method for forecasting stock market returns. Rather than summing the parts of stock returns, we suggest summing some of the frequency-decomposed parts. The proposed method signi cantly improves upon the original sum-of-the-parts...

We show that the out-of-sample forecast of the equity risk premium can be signi ficantly improved by taking into account the frequency-domain relationship between the equity risk premium and several potential predictors. We consider fi fteen predictors from the existing literature, for the...

We extract cycles in the term spread (TMS) and study their role for predicting the equity risk premium (ERP) using linear models. The low frequency component of the TMS is a strong and robust out-of-sample ERP predictor. It obtains out-of-sample R-squares (versus the historical mean benchmark)...

We assess the benefits of using frequency-domain information for active portfolio management. To do so, we forecast the bond risk premium and equity risk premium using a methodology that isolates frequencies (of the predictors) with the highest predictive power. The resulting forecasts are more...

Any time series can be decomposed into cyclical components fluctuating at different frequencies. Accordingly, in this paper we propose a method to forecast the stock market's equity premium which exploits the frequency relationship between the equity premium and several predictor variables. We...

This paper explores the out-of-sample forecasting performance of 25 equity premium predictors over a sample period from 1973 to 2023. While conventional time-series methods reveal that only one predictor demonstrates significant out-of-sample predictive power, frequency-domain analysis uncovers...

We introduce a frequency-domain forecast combination method that leverages time- and frequencydependent predictability to enhance forecast accuracy. By decomposing both the target variables (equity premium and real GDP growth) and predictor variables into distinct frequency components, this...

We study the optimal regulation of a monopolist when intrinsic efficiency (intrinsic cost) and empire building tendency (marginal utility of output) are private information, but actual cost (the difference between intrinsic cost and effort level) is observable. This is a problem of...