In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric estimators of the aforementioned quantities,...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...

In recent years, numerous volatility-based derivative products have been engineered. This has led to interest in constructing conditional predictive densities and confidence intervals for integrated volatility. In this paper, we propose nonparametric kernel estimators of the aforementioned...

This paper proposes methods for testing the multivariate mixture of normals hypothesis. It uses multivariate measures of integrated variance to standardize (in a matrix sense) daily returns. Because replacing the unobserved integrated covariance by its estimator introduces a finite-sample...

We investigate how individual equity prices react to stock specific expected jump components. We find that a portfolio buying stocks with negative expected jump component and selling stocks with positive expected jump component earns significant returns, equal to 51 basis points per month.The...