An efficient and accurate approach is proposed for forecasting the Value at Risk (VaR) and Expected Shortfall (ES) measures in a Bayesian framework. This consists of a new adaptive importance sampling method for the Quick Evaluation of Risk using Mixture of t approximations (QERMit). As a first...

Investors' searches for successful forecasting models cause the data generating process for financial returns to change over time, which means that individual return forecasting models can, at best, hope to uncover evidence of 'local' predictability. We illustrate this point on a suite of...

Using a long sample of commodity spot price indexes over the period 1947–2010, we examine the out-of-sample predictability of commodity prices by means of macroeconomic and financial variables. Commodity currencies are found to have some predictive power at short (monthly and quarterly)...