SFB649DP2016 025
Forecasting Limit Order Book Liquidity Supply-Demand Curves with Functional
AutoRegressive Dynamics
Ying Chen
Wee Song Chua
Wolfgang K. Härdle
Abstract:
Limit order book contains comprehensive information of liquidity on bid and
ask sides. We propose a Vector Functional AutoRegressive (VFAR) model to
describe the dynamics of the limit order book and demand curves and utilize
the fitted model to predict the joint evolution of the liquidity demand and
supply curves. In the VFAR framework, we derive a closed-form maximum
likelihood estimator under sieves and provide the asymptotic consistency of the
estimator. In application to limit order book records of 12 stocks in NASDAQ
traded from 2 Jan 2015 to 6 Mar 2015, it shows the VAR model presents a strong
predictability in liquidity curves, with R2 values as high as 98.5 percent for
insample estimation and 98.2 percent in out-of-sample forecast experiments. It
produces accurate 5-; 25- and 50-minute forecasts, with root mean squared
error as low as 0.09 to 0.58 and mean absolute percentage error as low as 0.3
to 4.5 percent.
Keywords:
Limit order book, Liquidity risk, multiple functional time series
JEL Classification:
C13, C32, C53