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Least Squares inference on integrated volatility and the relationship between efficient Prices and noise

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Least Squares inference on integrated volatility and the relationship between efficient Prices and noise. / Nolte, Ingmar; Voev, Valeri.
In: Journal of Business and Economic Statistics, Vol. 30, No. 1, 2012, p. 94-108.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Nolte, I & Voev, V 2012, 'Least Squares inference on integrated volatility and the relationship between efficient Prices and noise', Journal of Business and Economic Statistics, vol. 30, no. 1, pp. 94-108. https://doi.org/10.1080/10473289.2011.637876

APA

Nolte, I., & Voev, V. (2012). Least Squares inference on integrated volatility and the relationship between efficient Prices and noise. Journal of Business and Economic Statistics, 30(1), 94-108. https://doi.org/10.1080/10473289.2011.637876

Vancouver

Nolte I, Voev V. Least Squares inference on integrated volatility and the relationship between efficient Prices and noise. Journal of Business and Economic Statistics. 2012;30(1):94-108. doi: 10.1080/10473289.2011.637876

Author

Nolte, Ingmar ; Voev, Valeri. / Least Squares inference on integrated volatility and the relationship between efficient Prices and noise. In: Journal of Business and Economic Statistics. 2012 ; Vol. 30, No. 1. pp. 94-108.

Bibtex

@article{2b473889cf7d468bac2119b31f06f0f1,
title = "Least Squares inference on integrated volatility and the relationship between efficient Prices and noise",
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 variance (), noise moments, and price-noise relations. In the iid noise case, we derive the asymptotic variance of the 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. This article has supplementary material online.",
keywords = "High-frequency data, jumps, market microstructure, realized volatility, subsampling",
author = "Ingmar Nolte and Valeri Voev",
year = "2012",
doi = "10.1080/10473289.2011.637876",
language = "English",
volume = "30",
pages = "94--108",
journal = "Journal of Business and Economic Statistics",
issn = "0735-0015",
publisher = "American Statistical Association",
number = "1",

}

RIS

TY - JOUR

T1 - Least Squares inference on integrated volatility and the relationship between efficient Prices and noise

AU - Nolte, Ingmar

AU - Voev, Valeri

PY - 2012

Y1 - 2012

N2 - 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 variance (), noise moments, and price-noise relations. In the iid noise case, we derive the asymptotic variance of the 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. This article has supplementary material online.

AB - 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 variance (), noise moments, and price-noise relations. In the iid noise case, we derive the asymptotic variance of the 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. This article has supplementary material online.

KW - High-frequency data

KW - jumps

KW - market microstructure

KW - realized volatility

KW - subsampling

U2 - 10.1080/10473289.2011.637876

DO - 10.1080/10473289.2011.637876

M3 - Journal article

VL - 30

SP - 94

EP - 108

JO - Journal of Business and Economic Statistics

JF - Journal of Business and Economic Statistics

SN - 0735-0015

IS - 1

ER -