A stochastic approach to modelling the USD/AUD exchange rate: Implications for managing foreign exchange exposure

Abstract

Purpose

To develop an integrated approach to forecasting spot foreign exchange rates by incorporating some principles underlying long‐term dependence.

Design/methodology/approach

The paper utilises the random‐walk framework to develop a stochastic forecast model wherein the sign (positive or negative) and magnitude (strong or weak) of dependence can be separately controlled. The integrated model demonstrates superior forecast performance over a conventional random walk.

Findings

Using spot log prices and log price changes (returns) for the USD/AUD exchange rate, the initial outcomes of the study suggest that a priori knowledge of the underlying sign and magnitude of long‐term dependence yields out‐of‐sample forecasts superior to those of a random walk model.

Research limitations/implications

Independent assessment of the contribution to forecast accuracy of controlling for the sign of dependence between successive price changes only shows little additional improvement in out‐of‐sample forecast performance over the random walk null.

Practical implications

The findings of the study have important ramifications for managerial finance as they provide important insights on expected future currency returns with potential advantages in currency hedging and/or timing of international capital flows.

Originality/value

The contribution of this paper is to develop an original forecast model explicitly incorporating the conceptual and theoretical characteristics of long‐term dependent time series. By separating the key characteristics and modelling each individually, the contribution of each to forecast accuracy can be evaluated.

Citation

Ellis, C. and Wilson, P. (2005), "A stochastic approach to modelling the USD/AUD exchange rate: Implications for managing foreign exchange exposure", International Journal of Managerial Finance, Vol. 1 No. 1, pp. 36-48. https://doi.org/10.1108/17439130510584874