Self‐Fundamentals, Cross‐Fundamentals, and Exchange Rate Predictions
将自身基本面（货币对两国经济基本面）和交叉基本面（其他主要经济体基本面）结合，用Mallows模型平均法预测汇率，发现该方法显著优于随机游走，并可用于货币和债券投资获利。
Abstract In this paper, we propose incorporating both self‐fundamentals, defined as the fundamentals of two economies in one currency pair, and cross‐fundamentals, defined as the fundamentals of other major economies, to forecast exchange rates in line with the theory of “third‐country effects” of Berg and Mark (2015). We utilize the Mallows model averaging method proposed in Hansen (2007) to optimally combine the predictions provided by fundamental submodels. We find that our approach significantly outperforms the random walk and the alternatives for one‐month‐ahead predictions and that both the self‐ and cross‐fundamentals play important roles in prediction. Furthermore, according to our prediction, we obtain meaningful investment profit trading on currencies and bonds.