Fundamentals and Exchange Rate Prediction Revisited
用多种货币汇率的独立成分构造潜在基本面汇率，发现其与泰勒规则、购买力平价结合的模型在预测上优于随机游走，且汇率变化的第三矩信息有助于解释汇率波动。
This paper measures latent fundamental exchange rates with independent component‐based rates constructed from a cross‐section of exchange rates and then uses their deviations from exchange rates to forecast. Empirical results indicate that the independent component‐based model and its Taylor rule and purchasing power parity augmented models are superior to the random walk in predicting exchange rates. These results are robust to several scenarios and are likely to be observed if the U.S. sources and the recursive scheme are applied. Our results reveal that information regarding the third moment of exchange rate changes is helpful to explain exchange rate movements.