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...

The study is aimed at determining the oscillators of crisis manifestations when the Russian economy tries to make transition to the path for accelerating technological development and forming an innovative economy. Short-term cycles were determined in the development of the Russian economy from...

How long is the long run in the relationship between money growth and inflation? How important are high inflation episodes for the unit slope finding in the quantity theory of money? To answer these questions we study the relationship between excess money growth and inflation over time and...

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...

We revisit the empirical performance of the Q theory of investment, explicitly taking into account the frequency dependence of investment, Tobin's Q, and cash flow. The time series are decomposed into orthogonal components of different frequencies using wavelet multiresolution analysis. We find...

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...

This paper begins by re-examining the spectral properties of several cyclically sensitive variables such as hours worked, unemployment and capacity utilization. For each of these series, we document the presence of an important peak in the spectral density at a periodicity of approximately 36-40...

This paper first applies the MODWT (Maximal Overlap Discrete Wavelet Transform) to Euro Area quarterly GDP data from 1995 – 2014 to obtain the underlying cyclical structure of the GDP components. We then design optimal fiscal and monetary policy within a large state-space LQ-tracking wavelet...

In this paper discrete wavelet filtering techniques are applied to decompose macroeconomic data so that they can be simultaneously analyzed in both the time and frequency domains. The MODWT (Maximal Overlap Discrete Wavelet Transform) is applied to U.S. quarterly GDP data from 1947–2012 to...

This paper uses wavelet-based optimal control to simulate fiscal and monetary strategies under different levels of policy restrictions. The model applies the Maximal Overlap Discrete Wavelet Transform (MODWT) to United States quarterly GDP data, and then uses the decomposed variables to build a...

This paper begins by re-examining the spectral properties of several cyclically sensitive variables such as hours worked, unemployment and capacity utilization. For each of these series, we document the presence of an important peak in the spectral density at a periodicity of approximately 36-40...

We make two complementary contributions to efficiently estimate dynamic factor models: a frequency domain EM algorithm and a swift iterated indirect inference procedure for ARMA models with no asymptotic efficiency loss for any finite number of iterations. Although our procedures can estimate...

The traditional approach to obtain valid confidence intervals for nonparametric quantities is to select a smoothing parameter such that the bias of the estimator is negligible relative to its standard deviation. While this approach is apparently simple, it has two drawbacks: First, the question...

We generalise the spectral EM algorithm for dynamic factor models in Fiorentini, Galesi and Sentana (2014) to bifactor models with pervasive global factors complemented by regional ones. We exploit the sparsity of the loading matrices so that researchers can estimate those models by maximum...

​This paper first applies the MODWT (Maximal Overlap Discrete Wavelet Transform) to Euro Area quarterly GDP data from 1995-2014 to obtain the underlying cyclical structure of the GDP components. We then design optimal fiscal and monetary policy within a large state-space LQ-tracking wavelet...

​In this paper discrete wavelet filtering techniques are applied to decompose macroeconomic data so that they can be simultaneously analyzed in both the time and frequency domains. The MODWT (Maximal Overlap Discrete Wavelet Transform) is applied to U.S. quarterly GDP data from 1947-2012 to...