Abstract

We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000 news articles relevant to the six most-traded foreign exchange currency pairs for the period of 1979–2016. We employ a dynamic model averaging approach to reduce model selection uncertainty and to identify time-varying probability to include regressors in our models. Our results show that smaller sizes models accounting for the presence of selective attention offer improved fitting and forecasting results. Specifically, we document a growing impact of foreign trade and monetary policy news on the euro/dollar exchange rate following the global financial crisis. Overall, our results point to the existence of selective attention in the case of most currency pairs.

摘要

我们分析了选择性注意假设下的汇率预测表现。尽管货币市场对各种不同的信息做出反应，但我们假设市场参与者只处理有限数量的信息。我们的分析包括 100,000 多篇与 1979-2016 年期间交易量最大的六种外汇货币对相关的新闻文章。我们采用动态模型平均方法来减少模型选择的不确定性，并确定随时间变化的概率以在我们的模型中包含回归变量。我们的结果表明，考虑到选择性注意存在的较小尺寸模型提供了改进的拟合和预测结果。具体来说，我们记录了全球金融危机后外贸和货币政策新闻对欧元/美元汇率的影响越来越大。总的来说，我们的结果表明在大多数货币对的情况下都存在选择性关注。