Least Squares Inference on Integrated Volatility and the Relationship between Efficient Prices and Noise

30 Pages Posted: 28 Apr 2009 Last revised: 17 Mar 2011

See all articles by Ingmar Nolte

Ingmar Nolte

Lancaster University - Department of Accounting and Finance

Valeri Voev

Aarhus University - CREATES

Date Written: March 14, 2011

Abstract

The expected value of sums of squared intraday returns (realized variance) gives rise to a least squares regression which adapts itself to the assumptions of the noise process and allows for joint inference on integrated volatility (IV), noise moments and price-noise relations. In the iid noise case, we derive the asymptotic variance of the IV and noise variance estimators and show that they are consistent. The joint estimation approach is particularly attractive as it reveals important characteristics of the noise process which can be related to liquidity and market efficiency. The analysis of dependence between the price and noise processes provides an often missing link to market microstructure theory. We find substantial differences in the noise characteristics of trade and quote data arising from the effect of distinct market microstructure frictions.

Keywords: High frequency data, Subsampling, Realized volatility, Market microstructure

JEL Classification: G10, F31, C32

Suggested Citation

Nolte, Ingmar and Voev, Valeri, Least Squares Inference on Integrated Volatility and the Relationship between Efficient Prices and Noise (March 14, 2011). Available at SSRN: https://ssrn.com/abstract=1396185 or http://dx.doi.org/10.2139/ssrn.1396185

Ingmar Nolte

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Valeri Voev (Contact Author)

Aarhus University - CREATES ( email )

School of Economics and Management
Building 1322, Bartholins Alle 10
DK-8000 Aarhus C
Denmark

Register to save articles to
your library

Register

Paper statistics

Downloads
209
Abstract Views
819
rank
146,750
PlumX Metrics