Inference from the Order Book with Applications to Volatility Estimation

26 Pages Posted: 26 Nov 2010

See all articles by Petr Novotny

Petr Novotny

Columbia University - Department of Statistics

Jan Vecer

Charles University in Prague - Faculty of Mathematics and Physics

Date Written: January 28, 2010

Abstract

The state of the exchange is characterized by an order book- number of lots that are asked or offered for each given price. Modeling the entire order book is too complex since there are too many variables to match, and the resulting model may not be realistic. Our approach is to model the state of the exchange using only a small number of parameters, where one parameter represents a price of the asset, and another parameter represents liquidity of the market. This is a compromise between modeling the entire order book, and modeling only one dimensional process that represents the price. The estimator of the price can be used to estimate other implied parameters of financial models, such as the volatility of an asset. The volatility estimator overcomes microstructure noise that is present in the high frequency data and thus one can obtain good volatility estimators even on very short time scales.

Keywords: volatility, high frequency data

JEL Classification: C00

Suggested Citation

Novotny, Petr and Vecer, Jan, Inference from the Order Book with Applications to Volatility Estimation (January 28, 2010). Available at SSRN: https://ssrn.com/abstract=1714078 or http://dx.doi.org/10.2139/ssrn.1714078

Petr Novotny (Contact Author)

Columbia University - Department of Statistics ( email )

Mail Code 4403
New York, NY 10027
United States

Jan Vecer

Charles University in Prague - Faculty of Mathematics and Physics ( email )

Sokolovska 83
Prague, 186 75
Czech Republic

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