We propose a methodology that can efficiently measure the Value-at-Risk (VaR) of large portfolios with time-varying volatility and correlations by bringing together the established historical simulation framework and recent contributions to the dynamic factor models literature. We find that the...

We evaluate the short horizon predictive ability of financial conditions indexes for stock returns and macroeconomic variables. We find reliable predictability only when the sample includes the 2008 financial crisis, and we argue that this result is driven by tailoring the indexes to the crisis...

Trading portfolios at Financial institutions are typically driven by a large number of financial variables. These variables are often correlated with each other and exhibit by time-varying volatilities. We propose a computationally efficient Value-at-Risk (VaR) methodology based on Dynamic...

We study whether stock market returns in oil-exporting countries can be predicted by oil price changes, and we investigate the link between predictability and the quality of each country's institutions. Returns are predictable for half the countries we consider, and predictability is stronger...

We measure the liquidity profile of open-end mutual funds using the sensitivity of their daily returns to aggregate liquidity. We study how this sensitivity changes around real-activity macroeconomic announcements that reveal large surprises about the state of the economy and after three...