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.
Original language | English |
---|---|
Journal | International Journal of Managerial Finance |
Publication status | Published - 2005 |
Keywords
- foreign exchange
- stochastic processes
- time-series analysis