Up: 2:1

A multiscale model of high-frequency trading

Andrei Kirilenko; Richard B. Sowers; Xiangqian Meng

Algorithmic Finance (2013), 2:1, 59-98
DOI: 10.3233/AF-13017

Published: Abstract, PDF.
Archived: SSRN.

Abstract

We propose and study a stylization of high frequency trading (HFT). Our interest is an order book which consists of orders from slow liquidity traders and orders from high-frequency traders. We would like to frame a model which is amenable to the (seemingly natural) mathematical toolkit of separation of scales and which can be used to address some of the larger issues involved in HFT.

The main issue to which we address our model is volatility. An important question is how volatility is affected by HFT. In our stylized model, we show how HFT increases volatility, and can quantify this effect as a function of the parameters in our model and the separation of scales.

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University of Bridgeport

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Kent State University

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Stanford University

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Harvard University

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AT&T Labs Research

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Boston University

Myron Scholes

Stanford University

Michael Sipser

Massachusetts Institute of Technology

Richard Thaler

University of Chicago

Stephen Wolfram

Wolfram Research

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Peter Bossaerts

California Institute of Technology

Emanuel Derman

Columbia University

Ming-Yang Kao

Northwestern University

Pete Kyle

University of Maryland

David Leinweber

Lawrence Berkeley National Laboratory

Richard J. Lipton

Georgia Tech

Avi Silberschatz

Yale University

Robert Webb

University of Virginia

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Giovanni Barone-Adesi

University of Lugano

Bruce Lehmann

University of California, San Diego

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