This paper focuses on the time series’ decomposition and economic representation of its constituent parts. Wavelet transforms are used for adaptive analysis of local behaviour of heterogeneous agents. Unlike fully revealing equilibrium of homogeneous beliefs, in the environment with...

We explore whether forecasting an aggregate variable using information on its disaggregate components can improve the prediction mean squared error over forecasting the disaggregates and aggregating those forecasts, or using only aggregate information in forecasting the aggregate. An implication...

This paper presents a forecast tracker that can help bridge the wide gap between formal econometric forecasting methods and the common practice of judgmental forecasting. Traditionally, out-of-sample forecast errors have been widely used to improve the accuracy of econometric models, but track...

This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatility of high frequency asset returns into components that may be easily interpreted and estimated. The conditional variance is expressed as a product of daily, diurnal and stochastic intraday...

This article faces the problem of stock price forecasting based on an integrated approach in which the modeling of high frequency financial data (duration, volume and bid-ask spread) uses a contemporaneous ordered probit model – the price changes (measured in numbers of ticks) are the...

Monetary policy conducted in real time has to take into account the preliminary nature of recent national accounts data. Not only recent data, but also figures dating many years back are potentially subject to revisions. This means that there is a danger that an important part of the central...

In this paper, we investigate the out-of-sample forecasting ability of a genetic program to approach the dynamic evolution of the Yen/US$ and Pound Sterling/US$ exchange rates, and verify whether the method can beat the random walk model. Later on, we use the predicted values to generate a...

Recent work has found that, without the benefit of hindsight, it can prove difficult for policy-makers to pin down accurately the current position of the output gap; real-time estimates are unreliable. However, attention primarily has focused on output gap point estimates alone. But point...

Data in which each observation is a curve occur in many applied problems. This paper explores prediction in time series in which the data is generated by a curve-valued autoregression process. It develops a novel technique, the predictive factor decomposition, for estimation of the...

This paper documents that inflation forecasts of the Federal Reserve systematically under-predicted inflation before Volker's appointment as Chairman and systematically over-predicted it afterward. It also documents that, under quadratic loss, commercial forecasts have information not contained...