This paper proposes a new class of copula-based dynamic models for high dimension conditional distributions, facilitating the estimation of a wide variety of measures of systemic risk. Our proposed models draw on successful ideas from the literature on modeling high dimension covariance matrices...

One can consider the concept of market neutrality for hedge funds as having breadth and depth: breadth reflects the number of market risks to which a fund is neutral, while depth reflects the completeness of the neutrality of the fund to market risks. We focus on market neutrality depth, and...

Recent studies in the empirical finance literature have reported evidence of two types of asymmetries in the joint distribution of stock returns. The Þrst is skewness in the distribution of individual stock returns, while the second is an asymmetry in the dependence between stocks: stock...

The concept of common factors has in the econometrics literature been applied to conditional means or in some cases to conditional variances. In this paper we generalize this concept to bivariate distributions. This is done using the conditional bivariate copula as the statistical tool. The...

Recent advances in financial econometrics have led to the development of new estimators of asset price variability using frequently-sampled price data, known as "realised volatility estimators" or simply "realised measures". These estimators rely on a variety of different assumptions and take...

We test for asymmetry in a model of the dependence between the Deutsche mark and the yen, in the sense that a different degree of correlation is exhibited during joint appreciations against the U.S. dollar versus during joint depreciations. We consider an extension of the theory of copulas to...

We construct daily house price indices for ten major U.S. metropolitan areas. Our calculations are based on a comprehensive database of several million residential property transactions and a standard repeat-sales method that closely mimics the methodology of the popular monthly Case-Shiller...

We propose a new family of easy-to-implement realized volatility based forecasting models. The models exploit the asymptotic theory for high-frequency realized volatility estimation to improve the accuracy of the forecasts. By allowing the parameters of the models to vary explicitly with the...