Abstract We establish an empirical link between the ex-ante uncertainty about macroeconomic fundamentals and the ex-post resolution of this uncertainty in financial markets. We measure macroeconomic uncertainty using prices of economic derivatives and relate this measure to changes in implied volatilities of stock and bond options when the economic data is released. Higher macroeconomic uncertainty is associated with greater reduction in implied volatilities following the news release. It is also associated with increased volume and decreased open interest in option markets after the release, consistent with market participants using financial options to hedge or speculate on macroeconomic news.

We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple and easily modified and extended to capture the effect of transaction costs, for example, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. We present an empirical implementation for the universe of all stocks in the CRSP–Compustat data set, exploiting the size, value, and momentum anomalies.

[We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple and easily modified and extended to capture the effect of transaction costs, for example, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. We present an empirical implementation for the universe of all stocks in the CRSP- Compustat data set, exploiting the size, value, and momentum anomalies.]

[Do bond investors demand credit quality or liquidity? The answer is both, but at different times and for different reasons. Using data on the Euro-area government bond market, which features a unique negative correlation between credit quality and liquidity across countries, we show that the bulk of sovereign yield spreads is explained by differences in credit quality, though liquidity plays a nontrivial role, especially for low credit risk countries and during times of heightened market uncertainty. In contrast, the destination of large flows into the bond market is determined almost exclusively by liquidity. We conclude that credit quality matters for bond valuation but that, in times of market stress, investors chase liquidity, not credit quality.]

Do bond investors demand credit quality or liquidity? The answer is both, but at different<br/>times and for different reasons. Using data on the Euro-area government bond market,<br/>which features a unique negative correlation between credit quality and liquidity across<br/>countries, we show that the bulk of sovereign yield spreads is explained by differences<br/>in credit quality, though liquidity plays a nontrivial role, especially for low credit risk<br/>countries and during times of heightened market uncertainty. In contrast, the destination of<br/>large flows into the bond market is determined almost exclusively by liquidity.We conclude<br/>that credit quality matters for bond valuation but that, in times of market stress, investors<br/>chase liquidity, not credit quality. (JEL G10, G12)