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...

In this paper we present Aino 3.0, the latest vintage of the dynamic stochastic general equilibrium (DSGE) model used at the Bank of Finland for policy analysis. Aino 3.0 is a small-open economy DSGE model at the intersection of the recent literatures on so-called TANK (“Two-Agent New...

Policymakers and researchers see inflation characterized by cyclical fluctuations driven by changes in resource utilization and temporary shocks, around a trend influenced by inflation expectations. We study the in-sample inflation dynamics and forecast inflation out-of-sample by analyzing a New...

We show that the New Keynesian Phillips Curve (NKPC) outperforms standard benchmarks in forecasting U.S. inflation once frequency-domain information is taken into account. We do so by decomposing the time series (of inflation and its predictors) into several frequency bands and forecasting...

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...

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)...

In this paper we present Aino 3.0, the latest vintage of the dynamic stochastic general equilibrium (DSGE) model used at the Bank of Finland for policy analysis. Aino 3.0 is a small-open economy DSGE model at the intersection of the recent literatures on so-called TANK (“Two-Agent New...