Realised kernels use high frequency data to estimate daily volatility of individual stock prices. They can be applied to either trade or quote data. Here we provide the details of how we suggest implementing them in practice. We compare the estimates based on trade and quote data for the same...

This paper shows how to use realised kernels to carry out efficient feasible inference on the ex-post variation of underlying equity prices in the presence of simple models of market frictions. The issue is subtle with only estimators which have symmetric weights delivering consistent estimators...

We examine moving average (MA) filters for estimating the integrated variance of a financial asset price in a framework where high frequency price data are contaminated with marketmicrostructure noise. We show that the sum of squared MA residuals needs to be scaled for it to be a suitable...

This rejoinder clarifies issues related to the features of market microstructure noise. Specifically, we show that pre-processing of high-frequency data is very useful for the estimation of quadratic variation. We also document a strong relationship between quadratic variation and the number of...

In this paper, we provide an intraday analysis of the impact of monetary policy on the equity markets. Specifically, we study changes in prices and changes in volatility for the Samp;P 500 associated with Federal Open Market Committee announcements as well as real-time changes in market...

We consider the problem of deriving an empirical measure of daily integrated variance (IV) in the situation where high-frequency price data are unavailable for part of the day. We study three estimators in this context and characterize the assumptions that justify their use. We show that the...

We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of marketmicrostructure noise and that a simple...

The realized variance (RV) is known to be biased because intraday returns are contaminated with market microstructure noise, in particular if intraday returns are sampled at high frequencies. In this paper, we characterize the bias under a general specification for the market microstructure...