For the class of distortion risk measures, a natural estimator has the form of L-statistics. In this article, we investigate the large sample properties of general L-statistics based on weakly dependent data and apply them to our estimator. Under certain regularity conditions, which are somewhat...

A technique for online estimation of spot volatility for high-frequency data is developed. The algorithm works directly on the transaction data and updates the volatility estimate immediately after the occurrence of a new transaction. Furthermore, a nonlinear market microstructure noise model is...

We study the price impact of order book events--limit orders, market orders, and cancellations--using the NYSE Trades and Quotes data for fifty U.S. stocks. We show that, over short time intervals, price changes are mainly driven by the order flow imbalance (OFI), defined as the imbalance...

Working in a single-factor Markovian setting, this article derives a new, static spanning relation between a given option and a continuum of shorter-term options written on the same asset. Compared to dynamic delta hedge, which breaks down in the presence of large random jumps, the static hedge...

We propose a novel approach to model serially dependent positive-valued variables which realize a non-trivial proportion of zero outcomes. This is a typical phenomenon in financial time series observed at high frequencies, such as cumulated trading volumes. We introduce a flexible point-mass...

A new asymptotic framework is used to provide finite sample approximations for various statistics in the spurious return predictive regression analyzed by Ferson, Sarkissian, and Simin (2003a). Our theory explains all the findings of Ferson, Sarkissian, and Simin (2003a) and confirms the...