A Comparison of the Forecasting Ability of Immediate Price Impact Models

37 Pages Posted: 28 Oct 2014 Last revised: 22 Sep 2015

See all articles by Manh Cuong Pham

Manh Cuong Pham

Lancaster University - Department of Accounting and Finance

Huu Nhan Duong

Monash University - Department of Banking and Finance; Financial Research Network (FIRN)

Paul Lajbcygier

Monash University - Department of Banking & Finance

Date Written: September 18, 2015

Abstract

As a consequence of recent technological advances and the proliferation of algorithmic and high frequency trading, the cost of trading in financial markets has irrevocably changed. One important change relates to how trading affects prices; known as price impact. Price impact represents the largest cost associated with trading. Forecasting price impact is very important as it can provide estimates of trading profits after costs and also suggest optimal execution strategies. Although several models have recently been developed which may forecast the immediate price impact of individual trades, limited work has been done to compare their relative performance. We provide a comprehensive performance evaluation of these models and test for statistically significant outperformance amongst candidate models using out-of-sample forecasts. We find that normalizing price impact by its average value significantly enhances the performance of traditional non-normalized models as the normalization factor captures some of the dynamics of price impact.

Keywords: Market Impact, Trading Costs, Out-of-sample forecasting

JEL Classification: G10, G12

Suggested Citation

Pham, Manh Cuong and Duong, Huu Nhan and Lajbcygier, Paul, A Comparison of the Forecasting Ability of Immediate Price Impact Models (September 18, 2015). Available at SSRN: https://ssrn.com/abstract=2515667 or http://dx.doi.org/10.2139/ssrn.2515667

Manh Cuong Pham

Lancaster University - Department of Accounting and Finance ( email )

Lancaster, Lancashire LA1 4YX
United Kingdom

Huu Nhan Duong

Monash University - Department of Banking and Finance ( email )

Melbourne
Australia

Financial Research Network (FIRN)

C/- University of Queensland Business School
St Lucia, 4071 Brisbane
Queensland
Australia

HOME PAGE: http://www.firn.org.au

Paul Lajbcygier (Contact Author)

Monash University - Department of Banking & Finance ( email )

23 Innovation Walk
Wellington Road
Clayton, Victoria 3800
Australia

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