TY - JOUR
T1 - Exchange rate return predictability in times of geopolitical risk
AU - Iyke, Bernard Njindan
AU - Phan, Dinh Hoang Bach
AU - Narayan, Paresh Kumar
N1 - Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/5
Y1 - 2022/5
N2 - We develop the hypothesis that geopolitical risk predicts exchange rate returns. Using data on 17 countries, we demonstrate that the information content embedded in geopolitical risk is economically useful and can improve the forecast accuracy of exchange rate returns. We show that geopolitical risk predicts 10 out of 17 (59%) exchange rate returns in in-sample tests while in out-of-sample tests predictability is found for 88% of currencies. Buy and sell signals generated from our model lead to higher returns compared to the historical average model. Our model delivers excess profits relative to the benchmark model in 11 out of 17 (65%) currencies.
AB - We develop the hypothesis that geopolitical risk predicts exchange rate returns. Using data on 17 countries, we demonstrate that the information content embedded in geopolitical risk is economically useful and can improve the forecast accuracy of exchange rate returns. We show that geopolitical risk predicts 10 out of 17 (59%) exchange rate returns in in-sample tests while in out-of-sample tests predictability is found for 88% of currencies. Buy and sell signals generated from our model lead to higher returns compared to the historical average model. Our model delivers excess profits relative to the benchmark model in 11 out of 17 (65%) currencies.
KW - Exchange rate returns
KW - Geopolitical risk
KW - Predictability
KW - Trading strategies
UR - http://www.scopus.com/inward/record.url?scp=85125729584&partnerID=8YFLogxK
U2 - 10.1016/j.irfa.2022.102099
DO - 10.1016/j.irfa.2022.102099
M3 - Article
AN - SCOPUS:85125729584
SN - 1057-5219
VL - 81
JO - International Review of Financial Analysis
JF - International Review of Financial Analysis
M1 - 102099
ER -