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Federal market information technology in the post flash crash era: roles for supercomputing

Published: 13 November 2011 Publication History

Abstract

This paper describes collaborative work between active traders, regulators, economists, and supercomputing researchers to replicate and extend investigations of the Flash Crash and other market anomalies in a National Laboratory HPC environment. Our work suggests that supercomputing tools and methods will be valuable to market regulators in achieving the goal of market safety, stability, and security.
Currently the key mechanism for preventing catastrophic market action are "circuit breakers." We believe a more graduated approach, similar to the "yellow light" approach in motorsports to slow down traffic, might be a better way to achieve the same goal. To enable this objective, we study a number of indicators that could foresee hazards in market conditions and explore options to confirm such predictions. Our tests confirm that Volume Synchronized Probability of Informed Trading (VPIN) and a version of volume Herfindahl-Hirschman Index (HHI) for measuring market fragmentation can indeed give strong signals ahead of the Flash Crash event on May 6 2010. This is a preliminary step toward a full-fledged early-warning system for unusual market conditions.

References

[1]
E. W. Bethel, S. Campbell, E. Dart, K. Stockinger, and K. Wu. Accelerating Network Traffic Analysis Using Query-Driven Visualization. In Proceedings of 2006 IEEE Symposium on Visual Analytics Science and Technology, pages 115--122. IEEE Computer Society Press. October 2006. LBNL-59891.
[2]
CFTC/SEC. Findings regarding the market events of may 6,2010, Sep 2010. http://www.sec.gov/news/studies/2010/marketevents-report.pdf.
[3]
CFTC/SEC. Preliminary findings regarding the market events of may 6,2010, May 2010. www.sec.gov/sec-cftc-prelimreport.pdf.
[4]
J. Chou, K. Wu, O. Rübel, M. Howison, J. Qiang, Prabhat, B. Austin, E. W. Bethel, R. D. Ryne, and A. Shoshani. Parallel index and query for large scale data analysis. In SC11, 2011.
[5]
B. Curry and K. D. George. Industrial concentration: A survey. The Journal of Industrial Economics, 31(3):203--255, 1983.
[6]
D. Easley, N. Kiefer, M. O'Hara, and J. Paperman. Liquidity, information, and infrequently traded stocks. Journal of Finance, 51:1405--1436, 1996.
[7]
D. Easley, M. M. Lopez de Prado, and M. O'Hara. Flow Toxicity and Liquidity in a High Frequency World. Technical Report 9--2011, The Johnson School at Cornell University. Feb 2011.
[8]
HDF Group. HDF5 user guide, 2011. http://hdf.ncsa.uiuc.edu/HDF5/doc/H5.user.html.
[9]
O. C. Herfindahl. Concentration in the US Steel Industry. PhD thesis, Columbia University, 1950.
[10]
T. Hey, S. Tansley, and K. Tolle, editors. The Fourth Paradigm: Data-Intensive Scientific Discovery. Microsoft, Oct 2009.
[11]
A. O. Hirschman. National Power and the Structure of Foreign Trade. University of California Press, 1980.
[12]
M. Howison, Q. Koziol, D. Knaak, J. Mainzer, and J. Shalf. Tuning HDF5 for Lustre File Systems. In Proceedings of 2010 Workshop on Interfaces and Abstractions for Scientific Data Storage (IASDS10), Heraklion, Crete, Greece, Sep 2010.
[13]
B. Lauterbach and U. Ben-Zion. Stock market crashes and the performance of circuit breakers. Empirical evidence. The Journal of Finance, 48(5):1909--1925, Dec 1993.
[14]
A. Madhavan. Exchange-traded funds, market structure and the flash crash. Technical Report in-preparation, BlackRock, 2011.
[15]
New York Stock Exchange, Inc. TAQ 3 User's Guide (V 1.1.9), Oct 2008.
[16]
M. O'Hara. Market microstructure theory. Blackwell, 2007.
[17]
O. Rübel, Prabhat, K. Wu, H. Childs, J. Meredith, C. G. R. Geddes. E. Cormier-Michel, S. Ahern, G. H. weber, P. Messmer, H. Hagen, B. Hamann, and E. W. Bethel. High Performance Multivariate Visual Data Exploration for Extemel Large Data. In SuperComputing 2008 (SC08), Austin, Texas, USA, November 2008. LBNL-716E.
[18]
SEC. SEC Proposes Consolidated Audit Trail System to Better Track Market Trades, SEC Press Release, May 26, 2010. http://www.sec.gov/news/press/2010/2010--86.htm.
[19]
K. Stockinger, E. W. Bethel, S. Campbell, E. Dart, and K. Wu. Detecting Distributed Scans Using High-Performance Query-Driven Visualization. In SC '06: Proceedings of the 2006 ACM/IEEE Conference on High Performance Computing, Networking, Storage and Analysis. IEEE Computer Society Press, November 2006. LBNL-60053.
[20]
C. Wang, D. Chen, and M. Huang. International technology diffusion in computers & communications field. In ICMIT, pages 5--10, 2010.

Cited By

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  • (2016)Volume-Synchronised Probability of Informed Trading on Chinese Index Futures: A Comparative Approach1China Accounting and Finance Review10.7603/s40570-016-0005-618:2Online publication date: 28-Jun-2016
  • (2015)Effects of limit order book information level on market stability metricsJournal of Economic Interaction and Coordination10.1007/s11403-015-0164-612:2(221-247)Online publication date: 31-Jul-2015
  • (2012)The Application of High Performance Computing to Solvency and Profitability Calculations for Life Assurance ContractsProceedings of the 2012 SC Companion: High Performance Computing, Networking Storage and Analysis10.1109/SC.Companion.2012.140(1163-1170)Online publication date: 10-Nov-2012
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  1. Federal market information technology in the post flash crash era: roles for supercomputing

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    cover image ACM Conferences
    WHPCF '11: Proceedings of the fourth workshop on High performance computational finance
    November 2011
    54 pages
    ISBN:9781450311083
    DOI:10.1145/2088256
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 13 November 2011

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    Author Tags

    1. JEL codes: c02
    2. VPIN
    3. circuit breakers
    4. d52
    5. d53
    6. flash crash
    7. flow toxicity
    8. g14
    9. liquidity
    10. market fragmentation
    11. market microstructure
    12. probability of informed trading

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    Cited By

    View all
    • (2016)Volume-Synchronised Probability of Informed Trading on Chinese Index Futures: A Comparative Approach1China Accounting and Finance Review10.7603/s40570-016-0005-618:2Online publication date: 28-Jun-2016
    • (2015)Effects of limit order book information level on market stability metricsJournal of Economic Interaction and Coordination10.1007/s11403-015-0164-612:2(221-247)Online publication date: 31-Jul-2015
    • (2012)The Application of High Performance Computing to Solvency and Profitability Calculations for Life Assurance ContractsProceedings of the 2012 SC Companion: High Performance Computing, Networking Storage and Analysis10.1109/SC.Companion.2012.140(1163-1170)Online publication date: 10-Nov-2012
    • (undefined)Comments on 'Testing VPIN on Big Data - Response to Reflecting on the VPIN Dispute'SSRN Electronic Journal10.2139/ssrn.2331106
    • (undefined)Reflecting on the VPIN DisputeSSRN Electronic Journal10.2139/ssrn.2305905
    • (undefined)Assessing VPIN Measurement of Order Flow Toxicity via Perfect Trade ClassificationSSRN Electronic Journal10.2139/ssrn.2292602
    • (undefined)Trade Classification Algorithms: A Horse Race between the Bulk-Based and the Tick-Based RulesSSRN Electronic Journal10.2139/ssrn.2182819
    • (undefined)VPIN and the Flash Crash: A CommentSSRN Electronic Journal10.2139/ssrn.2062450
    • (undefined)Flow Toxicity and Liquidity in a High Frequency WorldSSRN Electronic Journal10.2139/ssrn.1695596
    • (undefined)The Flash Crash: Trading Aggressiveness, Liquidity Supply, and the Impact of Intermarket Sweep OrdersSSRN Electronic Journal10.2139/ssrn.1629402

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