Mathematics Seminar: Deep LOB Trading: Half a second please! | Wong Hoi Ying
Online Mathematics Seminar by Professor Wong Hoi Ying (The Chinese University of Hong Kong
), held on 22 March 2022.
Abstract: We introduce an expert deep-learning system for limit order book (LOB) trading for markets in which the stock tick frequency is longer than or close to 0.5 seconds, such as the Chinese A-share market. This half a second enables our system, which is trained with a deep-learning architecture, to integrate price prediction, trading signal generation, and optimization for capital allocation on trading signals altogether. It also leaves sufficient time to submit and execute orders before the next tick-report. Besides, we find that the number of signals generated from the system can be used to rank stocks for the preference of LOB trading. We test the system with simulation experiments and real data from the Chinese A-share market. The simulation demonstrates the characteristics of the trading system in different market sentiments, while the empirical study with real data confirms significant profits after factoring in transaction costs and risk requirements.
This is a joint work with Jie YIN.
Bio: Hoi Ying Wong is a Professor at Department of Statistics, the Chinese University of Hong Kong (CUHK). He is also a CUHK Outstanding Fellow of Faculty of Science and Associate Dean of Science (Student Affairs). His research interest includes quantitative finance, stochastic control, numerical methods and machine learning (recently). He has published over 90 journal articles and is serving as Associate Editor of SIAM Journal on Financial Mathematics, and International Journal of Theoretical and Applied Finance. He has consulting experience with banks, Hong Kong Monetary Authority and FinTech companies.