This paper develops a new approach for variance trading. We show that the discretely-sampled realized variance can be robustly replicated under very general conditions, including when the price can jump. The replication strategy specifies the exact timing for rebalancing in the underlying. The...

This paper introduces a new method for estimating variance matrices. Starting from the orthogonal decomposition of the sample variance matrix, we exploit the fact that orthogonal matrices are never ill-conditioned and therefore focus on improving the estimation of the eigenvalues. We estimate...

Time changed Brownian motions are extensively applied as decision models for asset returns in Finance. On the other hand infinite divisible normal mixtures generate time changed Brownian motions. The standard generalization leading to the multivariate setting of normal mean variance mixtures...

Volatility swaps and variance options are financial products written on discretely sampled realized variance. Actively traded in over-the-counter markets, these products are priced often by a continuously sampled approximation to simplify the computations. This paper presents an analytical...

We examine the prediction of Merton's intertemporal CAPM that time varying risk premiums arise from the conditional covariances of returns on assets with the return on the market and other state variables. We find a positive and significant price of risk for the covariance with the market return...

We derive the limiting distribution of the Oaxaca estimator of average treatment effects studied by Kline (2011). A consistent estimator of the asymptotic variance is proposed that makes use of standard regression routines. It is shown that ignoring uncertainty in group means will tend to lead...

This paper examines general variance-covariance structures for the specific effects and the overall error term in a two- way random effects (RE) model. So far panel data literature has only considered these general structures in a one-way model and followed the approach of a Cholesky-type...

This paper proposes a data-based measure of model performance to discriminate among competing asset pricing models of return predictability. I form a set of variance bounds on pricing kernels based on different systems for predicting asset returns. For a given asset pricing model, I define the...

A modification of the self-perturbed Kalman filter of Park and Jun (1992) is proposed for the on-line estimation of models subject to parameter in stability. The perturbation term in the updating equation of the state covariance matrix is weighted by the measurement error variance, thus avoiding...