Common shocks, similarities in central bank reaction functions, and international trade potentially produce common components in international inflation rates. This paper characterizes such links in international inflation rates with a dynamic latent factor model that decomposes 64 national...

We use boosted decision trees to generate daily out-of-sample forecasts of excess returns for Bitcoin and Ethereum, the two best-known and largest cryptocurrencies. The decision trees incorporate information from 39 predictors, including variables relating to cryptocurrency fundamentals,...

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...