Up: 2:2

Modeling market impact and timing risk in volume time

Slava Mazur

Algorithmic Finance (2013), 2:2, 113-126
DOI: 10.3233/AF-13020

Published: Abstract, PDF.
Archived: SSRN.


Intraday volatility and market impact models in volume time are proposed. We build an intraday volatility profile to capture non-stationarity of intraday price returns and utilize a fractional Brownian motion process to measure deviations from square root scaling rule of volatility.

We propose a generalized, scalable market impact model that encompasses two mainstream approaches: an aggregated impact of a series of trades on a sufficiently long trading horizon and a transient impact of individual trades.

We give an intuitive interpretation of the model parameters and provide a generalized formulation of the optimal trading horizon and efficient trading frontier.

The self-similarity feature of an aggregated model allows for its application to smaller trading horizons and modeling of transient impact of sliced orders. We formulate conditions when the impact of sliced orders can be consistently aggregated to the total impact of the original order and deduce relationships between parameters of macro and micro level models to enforce such consistency.

We demonstrate that the parameters of aggregated and transient impact models are intimately related to the auto-covariance function of trade signs. We give an explicit formulation of such a relationship when the stated auto-covariance function has a power law form.

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University of Bridgeport

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Jayaram Muthuswamy

Kent State University

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Kenneth J. Arrow

Stanford University

Herman Chernoff

Harvard University

David S. Johnson

AT&T Labs Research

Leonid Levin

Boston University

Myron Scholes

Stanford University

Michael Sipser

Massachusetts Institute of Technology

Richard Thaler

University of Chicago

Stephen Wolfram

Wolfram Research

Editorial Board

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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

Affiliate Editors

Giovanni Barone-Adesi

University of Lugano

Bruce Lehmann

University of California, San Diego

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