29 August 2012

How machines rule the financial markets

Excerpts from what is, to my mind, a scary story at Salon:
In today’s stock market, humans have largely been reduced to interested observers. The algorithms own the market now. Dow Jones and Bloomberg offer news services that are written specifically for the trading bots. These stories would be incomprehensible to a human, but make perfect sense to an algorithm...

The competition between warring Wall Street algorithms has become so bizarre that there are days when 40 percent of the trades on all U.S. exchanges, from the Nasdaq to the NYSE, are made by just two midwestern companies that most people, even those who work in finance, have never heard of. One of them, Getco, is located in Chicago; the other, Tradebot, is in Kansas City. Both firms employ world-class hackers and engineers who are focused on clearing profits of often less than one cent per share. Getco and Tradebot deploy thousands of algorithms to scour the markets for the tiniest of opportunities...

When a mutual fund company, be it Fidelity, Vanguard, or T. Rowe Price, makes a trade to add to a position or subtract from one, it’s inevitably a very large order. Trading a million shares of a stock, even a heavily traded one such as Apple or ExxonMobil, can move the market against the large seller or buyer. If other traders know that an order to buy a million shares is coming through the pipe, they will do whatever they can to get in front of it and buy up available shares. That way, they can repost their newly acquired shares for sale at a higher price knowing that they’ll get sucked into the mutual fund order. When a mutual fund has to pay more for its shares, it costs the owners of that fund—normal people saving for retirement—money...

Wall Street leaders have acknowledged that a rogue series of algorithms could spark a string of colossal losses that their owners can’t cover. Because some high-speed trading algorithms are able to trade on margin with leverage, it’s conceivable that a series of bad trades, all conducted in seconds, could lead to a liquidity crisis, bankrupting a trader’s broker and the clients he trades for. Such incidents have nearly happened before. In late 2009, Chicago’s Infinium Capital Management, one of the more secretive and powerful trading houses in the United States, twice lost control of an algorithm that began selling S&P 500 futures as fast as it could, dropping the market... 
The Salon story is in turn excerpted from a book that will be published later this week.

5 comments:

  1. For an example of an algorithm causing losses, see http://www.nanex.net/aqck2/3525.html and http://www.nanex.net/aqck2/3522.html for more details.

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  2. I am a free-market, small-government conservative, but I will admit that stories like these make me open up a bit regarding government regulation.

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  3. Another very good article on this subject:
    Trading at the speed of light:
    http://spectrum.ieee.org/computing/it/financial-trading-at-the-speed-of-light

    hat's why Spread Networks, of Ridgeland, Miss., invested what probably amounts to a few hundred million dollars last year to install a new fiber-optic cable along the shortest route it could find between New York and Chicago and then began marketing the connection to high-frequency trading firms. The round-trip travel time of a signal along its new cable, 13.3 milliseconds, is 3 ms faster than competitors can offer. With electronic trades now taking less than a millisecond to execute, firms with access to this fast connection can profit handsomely.

    And: When The Speed Of Light Is Too Slow: Trading at the Edge
    http://www.kurzweilai.net/when-the-speed-of-light-is-too-slow
    Dr. Alex Wissner-Gross, a Research Affiliate at the MIT Media Laboratory, and Dr. Cameron Freer, a Junior Researcher at the University of Hawaii, have developed an econophysical mathematical model called “relativistic statistical arbitrage” that provides a strategy for dealing with this new class of light-speed-limited, long-distance trading, in a paper published in Physical Review E. They advise market traders to locate their computers at certain points in between the two markets, with the locations of these points determined by how fast each market can send pricing information to the trading computers.

    And a (perhaps subjective) documentary on subject:
    Quants: The Alchemists of Wall Street http://topdocumentaryfilms.com/quants-alchemists-wall-street/

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  4. Another article on high-speed trading:
    http://m.cnbc.com/us_news/49333454
    The ultimate goal of many of these programs is to gum up the system so it slows down the quote feed to others and allows the computer traders (with their co-located servers at the exchanges) to gain a money-making arbitrage opportunity.

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