The estimation of the volatility with high-frequency data is plagued by the presence of microstructure noise, which leads to biased measures. Alternative estimators have been developed and tested either on specific structures of the noise or by the speed of convergence to their asymptotic...

Corporate earnings announcements unpack large bundles of information that should, if markets are efficient, almost surely trigger jumps in stock prices immediately after the news release. Testing this implication is difficult in practice because most earnings announcements occur in the...

We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...

In this cross-sectional study, equity market performance is assessed in a multidimensional risk-adjusted return framework using a nonparametric procedure known as data envelopment analysis. Employing a censored regression procedure, the association between equity market performance and a set of...

Bid and ask sizes at the top of the order book provide information on short-term price moves. Drawing from classical descriptions of the order book in terms of queues and order-arrival rates (Smith et al (2003)), we consider a diffusion model for the evolution of the best bid/ask queues. We...

This study investigates the asset price dynamics of high-yield bonds. High-yield bonds are debt instruments issued by corporate borrowers with a credit rating below investment grade. The noninvestment grade rating is typically the result of greater reliance on debt in the firm's capital...

This investigation focuses on the volatility of stock returns in the Belgian Stock Exchange from the period of April 1991 to April 2008. Empirical results have shown that there is a mean and volatility spillover effect from the big European markets. There are also mean spillover effects from the...

Modern Algorithmic Trading ("Algo") allows institutional investors and traders to liquidate or establish big security positions in a fully automated or low-touch manner. Most existing academic or industrial Algos focus on how to "slice" a big parent order into smaller child orders over a given...

We present an adjusted method for calculating the eigenvalues of a time-dependent return correlation matrix that produces a more stationary distribution of eigenvalues. First, we compare the normalized maximum eigenvalue time series of the market-adjusted return correlation matrix to that of...

In this paper, we build estimation error in mean returns into the mean-variance (MV) portfolio theory under the assumption that returns on individual assets follow a joint normal distribution. We derive the conditional sampling distribution of the MV portfolio along with its mean and risk return...