Factor Model Forecasts of Exchange Rates
从汇率截面数据中提取共同因子，利用个体偏离因子的部分进行预测，发现即使单变量汇率序列无自相关，该方法仍有效，并在长期预测中优于无变化基准。
We construct factors from a cross-section of exchange rates and use the idiosyncratic deviations from the factors to forecast. In a stylized data generating process, we show that such forecasts can be effective even if there is essentially no serial correlation in the univariate exchange rate processes. We apply the technique to a panel of bilateral U.S. dollar rates against 17 Organisation for Economic Co-operation and Development countries. We forecast using factors, and using factors combined with any of fundamentals suggested by Taylor rule, monetary and purchasing power parity models. For long horizon (8 and 12 quarter) forecasts, we tend to improve on the forecast of a “no change” benchmark in the late (1999–2007) but not early (1987–1998) parts of our sample.