主管：中国科学院
主办：中国优选法统筹法与经济数学研究会
　　　中国科学院科技战略咨询研究院
Chinese Journal of Management Science

Chinese Journal of Management Science >

2023 , Vol. 31 >Issue 12: 11 - 22

DOI: https://doi.org/10.16381/j.cnki.issn1003-207x.2022.2771

Multi-Level Order Flow Imbalance and Price Impact

  • Zhi-dong LIU ,
  • Chao WANG
Expand
  • School of Management Science and Engineering，Central University of Finance and Economics，Beijing 100081，China

Received date: 2022-07-15

  Revised date: 2023-03-01

  Online published: 2023-12-20

Fold

Abstract

In order-driven financial market， order flow imbalance is the main driving force for price movement. To deeply explore the price impact of order flow imbalance， dynamic limit order book， and quantify time-varying characteristics of multi-level order flow imbalance are reconstructed， then the price impact and cross impact are discussed. The mechanism and trader's behavior characteristics behind the result are explored. Our empirical analysis results show that，first，multi-level order flow imbalance contains deeper levels information of limit order book. It can provide higher explanatory power for the contemporaneous price impact. Second， from the perspective of multi-asset trading， the information of other limit order book is also included in multi-level order flow imbalance， multi-asset models with cross-impact do not provide additional explanatory power for contemporaneous impact. Third， the post-double-selection granger causality testing can effectively identify the continuous guidance relationship between different sample stocks' multi-level order flow imbalance and realize the portrayal of cross impact. Multi-level order flow imbalance not only contains private information held by informed traders， but also implies behavioral characteristics of multi-asset traders.

Key words： limit order book; order imbalance; deeper levels; price impact; cross impact

Cite this article

Zhi-dong LIU , Chao WANG . Multi-Level Order Flow Imbalance and Price Impact[J]. Chinese Journal of Management Science, 2023 , 31(12) : 11 -22 . DOI: 10.16381/j.cnki.issn1003-207x.2022.2771

References

1 邴涛，刘善存，张强，等. 指令驱动市场中非知情交易者的最优交易策略［J］. 管理科学学报， 2017， 20（3）： 24-45.
1 Bing Tao， Liu Shancun， Zhang Qiang， et al. The optimal trading strategy of uninformed traders in an order driven market［J］. Journal of Management Sciences in China， 2017， 20（3）： 24-45.
2 郭梁， 周炜星. 基于高频数据的中国股市量价关系研究［J］. 管理学报， 2010， 7（8）： 1242-1247.
2 Guo Liang， Zhou Weixing. An empirical analysis of the volume-price relation using high-frequency data in the chinese stock market［J］. Chinese Journal of Management， 2010， 7（8）： 1242-1247.
3 Gould M D， Porter M A， Williams S， et al. Limit order books［J］. Quantitative Finance， 2013， 13（11）： 1709-42.
4 O'Hara M. High frequency market microstructure［J］. Journal of Financial Economics， 2015， 116（2）： 257-270.
5 Bouchaud J P， Bonart J， Donier J， et al. Trades， quotes and prices： financial markets under the microscope［M］. Cambridge University Press， 2018.
6 Capponi F， Cont R. Multi-asset market impact and order flow commonality［R］. Working Paper， Imperial College London，2020.
7 谢文杰， 李牧遥， 周炜星. 噪声交易者、交易行为多样性与即时价格冲击［J］. 管理科学学报， 2020， 23（4）： 98-109.
7 Xie Wenjie， Li Muyao， Zhou Weixing. Noise traders，diversity of trading behavior，and immediate price impact of a stock and its warrant［J］. Journal of Management Sciences in China， 2020， 23（4）： 98-109.
8 Cont R. Statistical modeling of high-frequency financial data［J］. IEEE Signal Processing Magazine， 2011， 28（5）： 16-25.
9 Hautsch N， Huang R. The market impact of a limit order［J］. Journal of Economic Dynamics and Control， 2012， 36（4）： 501-522.
10 刘志东， 赵致远， 王超. 指令流不平衡、指令爆发与价格冲击［J］. 系统工程理论与实践， 2022， 42（9）： 2367-2390.
10 Liu Zhidong， Zhao Zhiyuan， Wang Chao. Order flow imbalance， quote burst and price impact［J］. Systems engineering-Theory & Practice， 2022， 42（9）： 2367-2390.
11 龚玉婷， 徐信喆， 杨朝军. 证券市场指令流与收益的非线性依赖性研究：混合连接函数（Mixed Copula）在流动性及流动性黑洞问题上的应用［J］. 管理工程学报， 2016， 30（3）： 151-160.
11 Gong Yuting， Xu Xinzhe， Yang Chaojun. Nonlinear dependence of order flow and return on stock market： applying mixed copula in the problem of liquidity and liquidity black hole［J］. Journal of Industrial Engineering/Engineering Management，2016， 30（3）： 151-160.
12 Eisler Z， Bouchaud J P， Kockelkoren J. The price impact of order book events： market orders， limit orders and cancellations［J］. Quantitative Finance， 2012， 12（9）： 1395-419.
13 Bouchaud J P， Gefen Y， Potters M， et al. Fluctuations and response in financial markets： the subtle nature of ‘random’ price changes［J］. Quantitative finance， 2004， 4（2）： 176-90.
14 陈收， 李双飞， 黎传国. 订单差、交易量变化对股票价格的冲击［J］. 管理科学学报， 2010， 13（9）： 68-75+97.
14 Chen Shou， Li Shuangfei， Li Chuanguo. Stock price response to order imbalance and change of volume［J］. Journal of Management Sciences in China， 2010，13（9）： 68-75+97.
15 Frazzini A， Israel R， Moskowitz T J. Trading costs of asset pricing anomalies［R］. Working Paper，AQR Capital Management， 2012.
16 Cont R， Kukanov A， Stoikov S. The price impact of order book events［J］. Journal of financial econometrics， 2014， 12（1）： 47-88.
17 Xu Ke， Gould M D， Howison S D. Multi-level order-flow imbalance in a limit order book［J］. Market Microstructure and Liquidity， 2018， 4（03n04）： 1950011.
18 Chan K， Fong W M. Trade size， order imbalance， and the volatility-volume relation［J］. Journal of Financial Economics， 2000， 57（2）： 247-273.
19 Bouchaud J P. Price impact［R］. Working Paper， Capital Fund Management， 2009.
20 Wang Shanshan， Sch?fer R， Guhr T. Cross-response in correlated financial markets： individual stocks［J］. The European Physical Journal B， 2016， 89（4）： 1-16.
21 Brown P， Walsh D， Yuen A. The interaction between order imbalance and stock price［J］. Pacific-Basin Finance Journal， 1997， 5（5）： 539-557.
22 Kyle A S. Continuous auctions and insider trading［J］. Econometrica： Journal of the Econometric Society， 1985： 1315-1335.
23 Andrade S C， Chang C， Seasholes M S. Trading imbalances， predictable reversals， and cross-stock price pressure［J］. Journal of Financial Economics， 2008， 88（2）： 406-423.
24 Benzaquen M， Mastromatteo I， Eisler Z， et al. Dissecting cross-impact on stock markets： an empirical analysis［J］. Journal of Statistical Mechanics： Theory and Experiment， 2017， 2017（2）： 023406.
25 Pasquariello P， Vega C. Strategic cross-trading in the US stock market［J］. Review of Finance， 2015， 19（1）： 229-282.
26 Cont R， Cucuringu M， Zhang Chao. Price impact of order flow imbalance： multi-level， cross-sectional and forecasting［J］. arXiv preprint arXiv： ， 2021.
27 Ahn H J， Bae K H， Chan K. Limit orders， depth， and volatility： evidence from the stock exchange of Hong Kong［J］. The Journal of finance， 2001， 56（2）： 767-788.
28 赵秀娟， 魏卓，汪寿阳.基于日内效应的沪深300股指期货套利的分析［J］.管理科学学报， 2015，18（1）：73-86.
28 Zhao Xiujuan， Wei Zhuo， Wang Shouyang. Study on CS1300 index futures' arbitrage based on intraday effect［J］. Journal of Management Sciences in China， 2015， 18（1）： 73-86.
29 刘志东， 赵致远. 基于状态依赖Hawkes过程的我国股市限价指令簿事件激励效应研究［J］. 中国管理科学， 2022， 30（2）： 1-13.
29 Liu Zhidong， Zhao Zhiyuan. Research on excitation effect among limit order book events in chinese stock market based on state-dependent hawkes processes［J］. Chinese Journal of Management Science， 2022， 30（2）： 1-13.
30 Harris L E， Panchapagesan V. The information content of the limit order book： evidence from NYSE specialist trading decisions［J］. Journal of Financial Markets， 2005， 8（1）： 25-67.
31 Madhavan A， Richardson M， Roomans M. Why do security prices change？ A transaction-level analysis of NYSE stocks［J］. The Review of Financial Studies， 1997， 10（4）： 1035-1064.
32 Giot P. Market risk models for intraday data［J］. The European Journal of Finance， 2005， 11（4）： 309-324.
33 Hecq A， Margaritella L， Smeekes S. Granger causality testing in high-dimensional VARs： a post-double-selection procedure［J］. Journal of Financial Econometrics， 2023，21（3）：915-958.
34 Brunnermeier M K. Information leakage and market efficiency［J］. The Review of Financial Studies， 2005， 18（2）： 417-457.
35 Schneider M， Lillo F. Cross-impact and no-dynamic-arbitrage［J］. Quantitative Finance， 2019， 19（1）： 137-154.
36 Harford J， Kaul A. Correlated order flow： pervasiveness， sources， and pricing effects［J］. Journal of Financial and Quantitative Analysis， 2005， 40（1）： 29-55.
Options
Outlines

/

〈 〉