Model Uncertainty And Exchange Rate Volatility

This article proposes an explanation for shifts in the volatility of exchange‐rate returns. Agents are uncertain about the true data generating model and deal with this uncertainty by making inference on the models and their parameters' approach, I call model learning. Model learning may lead agents to focus excessively on a subset of fundamental variables. Consequently, exchange‐rate volatility is determined by the dynamics of these fundamentals and changes as agents alter models. I investigate the empirical relevance of model learning and find that the change in volatility of GBP/USD in 1993 was triggered by a shift between models.