An empirical behavioral order-driven model with price limit rules

Gao-Feng Gu (), Xiong Xiong (), Hai-Chuan Xu (), Wei Zhang (), Yongjie Zhang (), Wei Chen () and Wei-Xing Zhou
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Gao-Feng Gu: East China University of Science and Technology
Xiong Xiong: Tianjin University
Hai-Chuan Xu: East China University of Science and Technology
Wei Zhang: Tianjin University
Yongjie Zhang: Tianjin University
Wei Chen: Shenzhen Stock Exchange

Financial Innovation, 2021, vol. 7, issue 1, 1-24

Abstract: Abstract We propose an empirical behavioral order-driven (EBOD) model with price limit rules, which consists of an order placement process and an order cancellation process. All the ingredients of the model are determined based on the empirical microscopic regularities in the order flows of stocks traded on the Shenzhen Stock Exchange. The model can reproduce the main stylized facts in real markets. Computational experiments unveil that asymmetric setting of price limits will cause the stock price to diverge exponentially when the up price limit is higher than the down price limit and to vanish vice versa. We also find that asymmetric price limits have little influence on the correlation structure of the return series and the volatility series, but cause remarkable changes in the average returns and the tail exponents of returns. Our EBOD model provides a suitable computational experiment platform for academics, market participants, and policy makers.

Keywords: Econophysics; Order-driven model; Agent-based model; Asymmetric price limit; Stylized facts; Limit order book (search for similar items in EconPapers)
Date: 2021
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Working Paper: An empirical behavioural order-driven model with price limit rules (2017)
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DOI: 10.1186/s40854-021-00288-4

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