In this paper I explore whether knowledge of the time-series properties of premia in the pricing of forward foreign exchange can be usefully exploited in forecasting future spot exchange rates. I use signal-extraction techniques, based on recursive application of the Kalman filter, to identify...

In this paper, we implement a methodology to identify and measure premia in the pricing of forward foreign exchange. The methodology involves application of signal-extraction techniques from the engineering literature. Diagnostic tests indicate that these methods are quite successful in...

This article presents a computationally efficient approach to sample from Gaussian state space models. The method is an instance of precision-based sampling methods that operate on the inverse variance-covariance matrix of the states (also known as precision). The novelty is to handle cases...

This paper studies the dynamics of Mexican inflation by using a wavelet multiresolution analysis on 16 indexes of the Mexican Consumer Price Index. This enables us to estimate the long-term trend, seasonality, and local shocks of the inflation series, even when the series are non-stationary. The...

Unobserved components time series models decompose a time series into a trend, a season, a cycle, an irregular disturbance, and possibly other components. These models have been successfully applied to many economic time series. The standard assumption of a linear model, often appropriate after...

The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...

We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and seasonal. Periodic time series models allow dynamic characteristics to depend on the period of the year, month, week or day. In the...