Little is known about the reactions of daily returns on portfolios with different characteristics to unexpected changes in macroeconomic conditions. This paper fills this void by analyzing the reactions of daily returns on portfolios formed on size and book-to-market ratio to news about a wide...

One fundamental issue in the study of market microstructures is that of price discovery. While most existing studies focus on the trading period, little is known whether and how much the non-trading period contributes to the price discovery. This paper offers a new perspective on the price...

We explore how the demand for a risky asset can be separated into an investment effect and a hedging effect by all risk-averse investors. This question has been shown to be complex when considered outside of the mean-variance framework. We restrict dependence among returns on the risky assets to...

We consider the original Arrow-Lind framework in which a government undertakes a risky project to be shared among many taxpayers. In our model, the taxpayers decide the level of participation in the risky project. Moreover, the amount of taxes collected by the government fully finances the...

We study the effect of an asymmetric environment on risk sharing. In our model, entrepreneurs consider undertaking risky projects in the real sector as well as selling part of their projects to investors. To capture the idea of an asymmetric environment, the returns on the alternative risk-free...

We assess the predictive accuracy of a large number of multivariate volatility models in terms of pricing options on the Dow Jones Industrial Average. We measure the value of model sophistication in terms of dollar losses by considering a set 248 multivariate models that differ in their...

This paper addresses the question of the selection of multivariate GARCH models in terms of variance matrix forecasting accuracy with a particular focus on relatively large scale problems. We consider 10 assets from NYSE and NASDAQ and compare 125 model based one-step-ahead conditional variance...

A large number of parameterizations have been proposed to model conditional variance dynamics in a multivariate framework. However, little is known about the ranking of multivariate volatility models in terms of their forecasting ability. The ranking of multivariate volatility models is...

This paper uses estimation techniques related to those of Galbraith and Zinde-Walsh (2000) for ARCH and GARCH models, based on realized volatility (Andersen and Bollerslev 1998, and others), to estimate the conditional quantiles of daily volatility in samples of equity index and foreign exchange...

We propose different extensions of the continuous record asymptotic analysis for rolling sample variance estimators developed by Foster and Nelson (1996). First, despite the difference in information sets we are able to compare the asymptotic distribution of volatility estimators involving data...