We establish the out-of-sample predictability of monthly exchange rate changes via machine learning techniques based on 70 predictors capturing country characteristics, global variables, and their interactions. To guard against overfitting, we use the elastic net to estimate a high-dimensional...

Using a measure of global political risk, relative to the U.S., that captures unexpected political conditions, we show that political risk is priced in the cross section of currency momentum and contains information beyond other risk factors. Our results are robust after controlling for...

We develop a novel measure of U.S. populist rhetoric. Aggregate Populist Rhetoric (APR) Index spikes around populist events. We decompose the APR Index into sub-indices. We show that APR Index and International Relations sub-index are negatively priced in the cross-section of currency excess...

Analyzing around 1.2 million FX-related news articles, we examine the cross-sectional predictive ability of FX news sentiment building an investment strategy that buys (sells) currencies with low (high) media sentiment. We find that this strategy offers positive and statistically significant...

In this paper, we examine the economic value of a text-based measure of financial integration. Our attention measure of financial integration is a strong positive predictor of currency excess returns. Specifically, the financial integration measure is positively priced in the cross-section of...