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...

Introduction -- ARMA models -- Forecasting stationary processes -- Estimation of Mean and Autocovariance Function -- Estimation of ARMA Models -- Spectral Analysis and Linear Filters -- Integrated Processes -- Models of Volatility -- Multivariate Time series -- Estimation of Covariance Function...

We propose a wavelet-based approach for construction of a financial cycle proxy. Specifically, we decompose three key macro-financial variables – private credit, house prices, and stock prices – on a frequency-scale basis using wavelet multiresolution analysis. The resulting...

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...

This paper examines the relationship between BSE Sensex and three other developed markets in the frequency domain. Cross-spectral methods, which are important in discovering and interpreting the relationships between economic variables, are used to analyze the relationships between different...

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...

The empirical performance of the Q theory of investment can be significantly improved by simultaneously considering the time- and the frequency-varying features of the investment-Q relationship. Using continuous wavelet tools, I assess the investment-Q sensitivity at different frequencies and...

Econometric analysis requires filtering techniques that are adapted to cater to data sequences that are short and that have strong trends. Whereas the economists have tended to conduct their analyses in the time domain, the engineers have emphasised the frequency domain. This paper places its...

We study the cross-country dimension of financial cycles for six euro area countries using three different methodologies: principal component analysis, synchronicity and similarity measures and wavelet analysis. We find that equity prices and interest rates display synchronization across...

In this chapter, we first explain what we mean by a signal, and then we describe some characteristics such as energy, frequency, phase, power spectrum, etc. We show how to analyse it by the means of spectral analysis and Fourier transform. Moreover, as the Fourier transform does not provide any...

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...

Despite an increase in research – motivated by the global financial crisis of 2007-08 – empirical studies on the financial cycle are rare compared to those on the business cycle. This paper adds some new evidence to this scarce literature by using a different empirical methodology –...

In recent times, a large number of studies has investigated the empirical properties of financial cycles within countries, mainly based on band-pass filter techniques. The contribution of this paper to the literature is twofold. First, in contrast to most existing studies in the financial cycle...

This paper develops a wavelet-based control system model that can be used to simulate fiscal and monetary strategies in an open economy context in the time-frequency domain. As the emphasis on real exchange rate stability is increased, the model simulates the effects on both the aggregate and...

We propose to date and analyze the financial cycle using the Maximum Overlap Discrete Wavelet Transform (MODWT). Our presentation points out limitations of the methods derived from the classical business cycle literature, while stressing their connection with wavelet analysis. The fundamental...

In this paper we use a New Keynesian model to explain why volatility transfer from high frequency to low frequency cycles can and did occur during the period commonly referred to as the "great moderation". The model suggests that an increase in inflation aversion and/or a reduction to a...

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...

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...

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...