The present study investigates the factors that affect the forecasting performance of several models that have been used for exchange rate prediction. We provide a quantitative survey collecting 8,413 reported forecast errors and we investigate which forecasting characteristics tend to improve forecasting ability. According to our evidence, predictions can beat random walk when certain types of models and econometric methods are used. In particular, linear specifications based on PPP outperform random walk. Furthermore, higher data frequency and longer forecasting horizon also improve forecasting performance. In this way, we identify under which conditions it is feasible to solve the ‘Meese-Rogoff’ puzzle.

中文翻译：

---

汇率可预测性：事实还是虚构？

本研究调查了影响用于汇率预测的几种模型的预测性能的因素。我们提供了一项定量调查，收集了 8,413 个报告的预测错误，并调查了哪些预测特征有助于提高预测能力。根据我们的证据，当使用某些类型的模型和计量经济学方法时，预测可以击败随机游走。特别是，基于 PPP 的线性规范优于随机游走。此外，更高的数据频率和更长的预测范围也可以提高预测性能。通过这种方式，我们确定了在什么条件下可以解决“Meese-Rogoff”难题。