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.