Stock Market ‘Flash’ Crashes Now Can be Predicted, Thanks to Cornell Metric

The new “Volume-synchronized Probability of INformed trading” – or VPIN – metric looks at the imbalance of trade relative to the total volume of the market.

The developers: David Easley, Cornell professor of social sciences and chair of the Department of Economics, and Maureen O’Hara, professor of finance at Cornell’s Johnson Graduate School of Management, in collaboration with Marcos Lopes de Prado of Tudor Investments.

The metric identifies flow toxicity, which Easley and O’Hara have been researching for about 20 years.

“Flow toxicity refers to the risk that liquidity providers face when trading with traders who have better information than they do,” says Easley. The flow of orders “is considered toxic when traders are selling when they’d rather be buying, and buying when they’d rather be selling.”

Flash events occur when market makers suddenly stop trading in response to a high level of flow toxicity, resulting in a sudden drop of prices.

“All morning long on May 6 order flows were becoming increasingly unbalanced, and volumes were huge,” says O’Hara. “An hour or more before the flash crash our measure hit historic levels.”

The VPIN could prevent future flash crashes by giving market regulators warning of flow toxicity early enough that they could slowly adjust the market, says Easley. The metric could also give traders a way to hedge the risk of flash crashes, so traders don’t have to be as concerned with the value of their inventory plummeting.

O’Hara serves on the Joint Commodity Futures Trading Commission-Securities and Exchange Commission (CFTC-SEC) Advisory Committee on Emerging Regulatory Issues established after May 6.

“One of the problems that regulators face now is that markets are so fast, that regulating after the fact is really too late,” she says.

Both the CFTC and the Financial Industry Regulatory Authority economic advising board have expressed interest in the VPIN. Private firms, such as Tudor Investments, have also used O’Hara and Easley’s research to develop trading algorithms for high-frequency markets.

Easley, who is also a member of the Department of Information Science, recently co-authored “Networks, Crowds and Markets: Reasoning About a Highly Connected World” with Jon Kleinberg, Cornell professor of computer science.

“Measuring Flow Toxicity In A High Frequency World” appears online in the Social Science Research Network. (Originally published Oct. 21, 2010.) The complete paper can be found at: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1695596