Abstract
This article 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 high-performance computing (HPC) environment.
Our work suggests that supercomputing tools and methods will be valuable to market regulators in achieving the goals of market safety, stability, and security. Research results using high-frequency data and analytics are described, and directions for future development are discussed.
Currently, the key mechanism for preventing catastrophic market action is “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 the volume Herfindahl–Hirschman index (HHI) for measuring market fragmentation could have indeed given strong signals ahead of the Flash Crash event on May 6, 2010. This is a preliminary step toward a full-fledged earlywarning system for unusual market conditions.
Footnotes
The authors would like to thank Horst Simon for his visionary leadership in establishing the Center for Innovative Financial Technology and initiating this project; Jerry Chou, David H. Bailey, Arie Shoshani, and Orianna DeMasi for helpful discussions in planning for this work; Harrison Dekker and Masou Nikravesh for helping with obtaining some of the data for this project; Jeff Donovan for the Nanex data used in this work; Marcos Lopez de Prado for providing sample code and data for computing VPIN; Maureen O’Hara and David Easley for valuable discussions on VPIN; Ananth Madhavan for instructive suggestions on computing HHI in a progressive manner; Quincey Koziol for helping out organizing HDF files; and Dan Weisberg for useful discussions about Panopticon. We are grateful for the insightful discussions with Gregg Berman, SEC’s lead Flash Crash investigator, whose suggestions kick-started the current work.
This work is supported by the Director, Office of Laboratory Policy and Infrastructure Management of the U.S. Department of Energy, under Contract No. AC02-05CH11231, and used resources of the National Energy Research Scientific Computing Center (NERSC).
Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor the Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or the Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof or the Regents of the University of California.
- Copyright © 2012 Lawrence Berkeley National Laboratory. All rights reserved. Not to be reproduced or redistributed without permission.
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Crash Era: Roles for Supercomputing
