ARFIMA Tests for Random Walks in Exchange Rates in Asian, Latin American and African-Middle Eastern Markets

Abstract

This article examines fractional processes as alternatives to random walks in emerging foreign exchange rate markets. Sowell's (1992) joint maximum likelihood is used to estimate the ARFIMA parameters and test for random walks. The results show that, in most cases, the emerging market exchange rates follow fractionally integrated processes. Forecasts of exchange rates based on the fractionally integrated autoregressive moving average models are compared to those from the benchmark random walk models. A Harvey, Leybourne and Newbold (1997) test of equality of forecast performance indicates that the ARFIMA forecasts are more efficient in the multi-step-ahead forecasts than the random walk model forecasts. The presence of fractional integration is seen to be associated with market inefficiency in the exchange markets examined. The evidence suggests that fractional integrated processes are viable alternatives to random walks for describing and forecasting exchange rates in the emerging markets.

Long Memory, Spurious Memory: Persistence in Range-Based Volatility of Exchange Rates

“…Spurious memory was examined in the exchange rate volatility of Czech Kouna and Hungarian Forint while other four series were contaminated with level shifts and presented persistent behaviour of true long memory as well (Walther et al 2017). Long memory trends in Latin American countries have been explored by (Holmes 2008;Karemera and Cole 2010;Gil-Alana and Sauci 2018).…”