Can currency-based risk factors help forecast exchange rates?

Abstract

The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract This paper examines time-series predictability of bilateral exchange rates from linear factor models that utilize unconditional and conditional expectations of three currency-based risk factors. Exploiting a comprehensive set of statistical criteria, we find that all versions of the linear factor models largely fail to outperform the benchmark of random walk with drift model in the out-of-sample forecasting of monthly exchange rate returns. This holds true for individual currencies and currency portfolios formed on forward discounts. We also show that the information embedded in the currency-based risk factors does not generate systematic economic value to investors. JEL Classification: F31, F37, G11, and G17.

Impact of the Main Currencies Exchange Rates on the Romanian Economic Policy Transformation

“…Such studies as Chinn and Meese (1995) and Mark (1995) argue that the evolution of the exchange rate can be predicted and somehow managed for long periods of time, while other views (Della Corte and Tsiakas, 2012;Verdelhan, 2013) highlight the randomness of the exchange rate evolution and the impossibility of predicting it. Ahmed, Liu and Valente (2016) analyzing the predictability of the exchange rates using linear factor models in the case of three currency-based risk factors reach the same conclusions expressed in previous studies (Meese and Rogoff, 1983), according to largely fail to outperform the benchmark random walk. On the other hand, Ahmed and Straetmans (2015) try to predict the cyclical behavior of exchange rates by using five risk factors, namely violations of uncovered interest rate parity (UIP), relative purchasing power parity (RPPP), pseudo-parity for equity returns, relative (cross-country) TED spreads and relative term spreads.…”

Modelling return and volatility spillovers in global foreign exchange markets

“…Further, the forecasting of exchange rate has been largely conducted on the basis of the structural "models of the 1970s;" Frenkel-Bilson (Frenkel, 1976;Bilson, 1978), Dornbusch-Frankel (Dornbusch, 1976;Frankel, 1979) and Hooper-Morton (Hooper 8 and Morton, 1982) asset models (see Meese and Rogoff, 1983 for more expositions of the models). These theoretical models capture the predictive power of such variables as relative money supplies, relative incomes, short-term interest rate differentials and relative prices among others for exchange rate forecasting (see Moosa and Burns, 2014a;Moosa and Burns, 2014b;Moosa and Burns, 2014c;Burns and Moosa, 2015;Ahmed, et al 2016 for empirical literatures).…”

“…In support of the Meese andRogoff (1983) submission, Cheung, et al (2005) examines the out-of-sample performance of the interest rate parity, monetary, productivity-based and behavioural exchange rate models and concludes that none of the models consistently outperforms the random walk at any horizon. Also, Ahmed, et al (2016) examines the predictability of bilateral exchange rates from asset pricing models and find that all versions of the factor models largely fail to outperform the benchmark random walk model for the out-of-sample forecasting of exchange rate. Further, Ince, et al (2016) also find weaker evidence of predictability for the traditional interest rate differential, purchasing power parity, and monetary models against the random walk model.…”

Predicting Exchange Rates in Asia: New Insights on the Accuracy of Survey Forecasts

“…Recently, Ahmed, Liu, and Valente (2016) as well as Byrne, Korobilis, and Ribeiro (2016) utilize the Theil's U measure in the context of evaluating FX forecasts. The Theil's U can easily be calculated as the fraction of the root mean squared error (RMSE) 7 of the forecast and the naïve prediction.…”