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...

In this paper we analyse the effect of model uncertainty on the wealth and utility outcomes of an investment decision. We compute optimal portfolio weights for domestic and foreign assets and using these weights we construct end investment horizon wealth and utility ratios. Model uncertainty is...

We emphasize using our solutions to the problems of omitted variables, measurement errors, and unknown functional forms to improve model specification, and to estimate the mean square error of an empirical best linear unbiased predictor of an individual drawing of the dependent variable of an...

This paper introduces model uncertainty into a simple Lucas-type monetary model. Inflation depends on agents' expectations and a vector of exogenous random variables. Following (Branch and Evans 2004) agents are assumed to underparameterize their forecasting models. A Misspecification...

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 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...

We develop an estimated time-series model of revisions of U.S. payroll employment in order to obtain more accurate filtered estimates of the "true" or underlying condition of U.S. employment. Our estimates of "true" employment are filtered, according to an estimated signal-plus-noise (S+N)...

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...