Imperial College London

ProfessorHarryZheng

Faculty of Natural SciencesDepartment of Mathematics

Professor of Mathematics
 
 
 
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Contact

 

+44 (0)20 7594 8539h.zheng Website

 
 
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Location

 

6M16Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Choi:2021:10.1016/j.jedc.2021.104098,
author = {Choi, SE and Jang, HJ and Lee, K and Zheng, H},
doi = {10.1016/j.jedc.2021.104098},
journal = {Journal of Economic Dynamics and Control},
pages = {1--25},
title = {Optimal market-Making strategies under synchronised order arrivals with deep neural networks},
url = {http://dx.doi.org/10.1016/j.jedc.2021.104098},
volume = {125},
year = {2021}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - This study investigates the optimal execution strategy of market-making for market and limit order arrival dynamics under a novel framework that includes a synchronised factor between buy and sell order arrivals. Using statistical tests, we empirically confirm that a synchrony propensity appears in the market, where a buy order arrival tends to follow the sell order’s long-term mean level and vice versa. This is presumably closely related to the drastic increase in the influence of high-frequency trading activities in markets. To solve the high-dimensional Hamilton–Jacobi–Bellman equation, we propose a deep neural network approximation and theoretically verify the existence of a network structure that guarantees a sufficiently small loss function. Finally, we implement the terminal profit and loss profile of market-making using the estimated optimal strategy and compare its performance distribution with that of other feasible strategies. We find that our estimation of the optimal market-making placement allows significantly stable and steady profit accumulation over time through the implementation of strict inventory management.
AU - Choi,SE
AU - Jang,HJ
AU - Lee,K
AU - Zheng,H
DO - 10.1016/j.jedc.2021.104098
EP - 25
PY - 2021///
SN - 0165-1889
SP - 1
TI - Optimal market-Making strategies under synchronised order arrivals with deep neural networks
T2 - Journal of Economic Dynamics and Control
UR - http://dx.doi.org/10.1016/j.jedc.2021.104098
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000702446100010&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - https://www.sciencedirect.com/science/article/pii/S0165188921000336?via%3Dihub
UR - http://hdl.handle.net/10044/1/92102
VL - 125
ER -