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How to Survive in the Age of High-Frequency Trading

By Igor Zhitnitsky and Victor German

NEW YORK ( TheStreet) -- The flash crash of 2010, which sent the Dow Jones Industrial Average briefly plunging nearly 1,000 points, brought to public attention the growing influence that algorithmic trading can wield over the market.

In the years following, mini flash crashes of individual stocks became commonplace, even if not always as loud. Beside the occasional flash crash, high-frequency trading, or HFT, is believed to have had a hand in other harrowing market events in recent years. The technical difficulties at Nasdaq on the debut of the Facebook (FB - Get Report) initial public offering, for example, was believed by many to have been at least in part the result of aggressive high-frequency trading. That event caused shares of Apple (AAPL - Get Report), Netflix (NFLX - Get Report) and at least two dozen other stocks to behave erratically for half an hour, culminating in a 17-second shutdown of the entire exchange.

Even the very firms whose sole business is related to trading are not immune to the unpredictability of these algorithms. In March 2012 we saw the BATS Global Markets (BATS) IPO crash 99.8% in less than 10 seconds, temporarily taking Apple down 9% as collateral damage. Later that year, Knight Capital Group (KCG) lost $440 million -- four times its net income for the previous year -- in half an hour to a poorly tested trading algorithm.

[Read: <a target="blank" data-add-tracking="true" href=""><em> Google Becomes a Hardware Company </em></a>]

On the face of it, high speed algorithmic trading is not without casualties. While some proponents contend that the net impact of HFT on the liquidity and efficiency of the market is generally positive notwithstanding exceptional events, we see strong evidence to the contrary.

One stark case study is an event that briefly shook the market on May 23, taking the entire utilities subsector of the S&P 500 down 8% when American Electric Power (AEP) and NextEra Energy (NEE) fell 54% and 62%, respectively. The cause of the fall was precisely the sudden lack of liquidity, and the culprits responsible were HFT algorithms. If the value of HFT is to provide liquidity, they failed spectacularly.

So who is happy about the impact of HFT on market conditions over the last few years? According to a 2012 survey by the TABB Group, it isn't the institutional community. When asked to rate their level of confidence in U.S. equity market structure, only 2% of 260 respondents rated their confidence as very high, down from 12% two years earlier, while 26% rated their confidence level as weak, up from 12% in 2010.
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