Using extracted forward rate term structure information to forecast foreign exchange rates

Abstract

The diculty of beating the random walk in forecasting spot foreign exchange rates is well documented, with the restricted VECM still providing the leading challenge. In this paper, we propose a functional principal component-based scalar response model. Our approach leads to near systematic outperformance in terms of a comparison of performance measures and to multiple instances of statistically signicant improvements in forecast accuracy. Overall, our results provide evidence that the forward rate term structure contains substantial information about the evolution of the spot exchange rate. Finally, a stylised trading strategy is employed to demonstrate possible economic benets of our approach.

Exchange Rate Forecasting Based on Combined Fuzzification Strategy and Advanced Optimization Algorithm

“…The process of changes in exchange rates is complicated and is closely related to a country's economic level, price level, inflation rate, interest rate, and government intervention. A country's exchange rate not only has a huge impact on the international economy and financial markets but also has an important impact on socioeconomic parameters and everyday life [2]. Therefore, in order to maintain sustained and stable economic growth, the correct prediction of exchange rates is imperative, as this can not only help the state and foreign trade enterprises strengthen management and avoid foreign exchange risks, but it is also a powerful supplement to the foreign exchange market theory [3].…”