Observed asset prices are known to deviate from their efficient values due to market microstructure frictions. This paper studies the effects of market microstructure noise on nonparametric estimates of the efficient price integrated variance. Specifically, we consider both asymptotic and finite sample effects of general market microstructure noise on realized variance estimates. The finite sam...

In this paper we design a test to detect the arrivals of jumps in asset prices contaminated by market microstructure noise. This test is defined by means of the truncated two-scales realized volatility estimator, recently introduced in Brownlees, Nualart, and Sun (2016), which is a robust estimator of the realized volatility in the presence of price jumps and market microstructure noise. We der...

The Hansen-Lunde (HL) research program is generally first-rate, displaying a rare blend of theoretical prowess and applied sense. The present paper is no exception. In a major theoretical advance, HL allow for correlation between microstructure (MS) noise and latent price. (I prefer “latent price” to terms such as “efficient price” or “true price,” which carry lots of excess baggage.) In a para...

We consider the best quadratic unbiased estimators of the integrated variance in the presence of independent market microstructure noise. We establish the asymptotic normality of a feasible best quadratic unbiased estimator under the assumption of constant volatility and show that it is asymptotically e cient when the market microstructure noise is normal. Since the class of quadratic estimator...

This paper is about how to estimate the integrated covariance 〈X,Y 〉T of two assets over a fixed time horizon [0, T ], when the observations of X and Y are “contaminated” and when such noisy observations are at discrete, but not synchronized, times. We show that the usual previous-tick covariance estimator is biased, and the size of the bias is more pronounced for less liquid assets. This is an...

If efficient asset prices follow a semi-martingale and are perfectly observed, their quadratic variation can be measured accurately from the sum of a large number of squared returns sampled over very finely spaced intervals, i.e., realized variance (Andersen et al., 2003, and Barndorff-Nielsen and Shephard, 2002). With the emergence of high-frequency data, it seems that we should be able to ide...

VOLATILITY AND JUMPS IN HIGH FREQUENCY FINANCIAL DATA: ESTIMATION AND TESTING Nan Zhou, PhD University of Pittsburgh, 2011 It has been widely accepted in financial econometrics that both the microstructure noise and jumps are significantly involved in high frequency data. In some empirical situations, the noise structure is more complex than independent and identically distributed (i.i.d.) assu...

Market microstructure noise is a challenge to high-frequency based estimation of the integrated variance, because the noise accumulates with the sampling frequency. This has lead to widespread use of constructing the realized variance, a sum of squared intraday returns, from sparsely sampled data, for example 5or 15minute returns. In this paper, we analyze the impact of microstructure noise on ...

We demonstrate, for the first time to our knowledge, the generation of squeezed light by means of soliton self-phase modulation in microstructure fiber. We observe and characterize the formation of solitons in the microstructure fiber at 1550 nm. A maximum squeezing of 2.7 dB is observed, corresponding to 4.0 dB after correcting for detection losses. The dependence of this quantum-noise reducti...