Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional Autoregressive Dynamics

SFB 649 Discussion Paper 2016-025

38 Pages Posted: 4 Aug 2016 Last revised: 22 Jun 2017

See all articles by Ying Chen

Ying Chen

National University of Singapore (NUS)

Wee Song Chua

National University of Singapore (NUS)

Wolfgang K. Härdle

Blockchain Research Center; Xiamen University - Wang Yanan Institute for Studies in Economics (WISE); Charles University; National Yang Ming Chiao Tung University; Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Date Written: June 2, 2017

Abstract

We develop a dynamic model to simultaneously characterize the liquidity demand and supply in limit order book. The joint dynamics is modelled in a unified Vector Functional AutoRegressive (VFAR) framework. We derive a closed-form maximum likelihood estimator under sieves and establish asymptotic consistency of the proposed method under mild conditions. We find the VFAR model presents strong interpretability and accurate out-of-sample forecast. In application to limit order book records of 12 stocks in NASDAQ traded from 2 Jan 2015 to 6 Mar 2015, the VFAR model yields R2 values as high as 98.5 percent for in-sample estimation and 98.2 percent in out-of-sample forecast experiments. It produces accurate 5-, 25- and 50-$minute forecasts, with RMSE as low as 0.09 to 0.58 and MAPE as low as 0.3 to 4.5 percent. The predictive power stably reduces trading cost in the order splitting strategies and achieves excess gains of 31 basis points on average.

Keywords: Liquidity demand and supply curves, Order splitting strategy, Vector functional autoregression

JEL Classification: C13, C32, C53

Suggested Citation

Chen, Ying and Chua, Wee Song and Härdle, Wolfgang K., Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional Autoregressive Dynamics (June 2, 2017). SFB 649 Discussion Paper 2016-025 , Available at SSRN: https://ssrn.com/abstract=2818409 or http://dx.doi.org/10.2139/ssrn.2818409

Ying Chen

National University of Singapore (NUS) ( email )

1E Kent Ridge Road
NUHS Tower Block Level 7
Singapore, 119228
Singapore

Wee Song Chua

National University of Singapore (NUS) ( email )

6 Science Drive 2
Singapore, 117546
Singapore

Wolfgang K. Härdle (Contact Author)

Blockchain Research Center ( email )

Unter den Linden 6
Berlin, D-10099
Germany

Xiamen University - Wang Yanan Institute for Studies in Economics (WISE) ( email )

A 307, Economics Building
Xiamen, Fujian 10246
China

Charles University ( email )

Celetná 13
Dept Math Physics
Praha 1, 116 36
Czech Republic

National Yang Ming Chiao Tung University ( email )

No. 1001, Daxue Rd. East Dist.
Hsinchu City 300093
Taiwan

Humboldt University of Berlin - Center for Applied Statistics and Economics (CASE)

Unter den Linden 6
Berlin, D-10099
Germany

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