Exchange Rate Narratives

Abstract

Leveraging Wall Street Journal news, recent developments in textual analysis, and generative AI, we estimate a narrative decomposition of the dollar exchange rate. Our findings shed light on the connection between economic fundamentals and the exchange rate, as well as on its absence. From the late 1970s onwards, we identify six distinct narratives that explain changes in the exchange rate, each largely non-overlapping. U.S. fiscal and monetary policies play a significant role in the early part of the sample, while financial market news becomes more dominant in the second half. Notably, news on technological change predicts the exchange rate throughout the entire sample period. Finally, using text-augmented regressions, we find evidence that media coverage explains the unstable relationship between exchange rates and macroeconomic indicators.

Keywords: Exchange rates, big data, textual analysis, macroeconomic news, Wall Street Journal, narrative retrieval, scapegoat