I thought so: http://www.nytimes.com/2009/07/24/business/24trading.html?scp=3&sq=high%20frequency&st=cse From the article: It was July 15, and Intel, the computer chip giant, had reporting robust earnings the night before. Some investors, smelling opportunity, set out to buy shares in the semiconductor company Broadcom. (Their activities were described by an investor at a major Wall Street firm who spoke on the condition of anonymity to protect his job.) The slower traders faced a quandary: If they sought to buy a large number of shares at once, they would tip their hand and risk driving up Broadcom’s price. So, as is often the case on Wall Street, they divided their orders into dozens of small batches, hoping to cover their tracks. One second after the market opened, shares of Broadcom started changing hands at $26.20. The slower traders began issuing buy orders. But rather than being shown to all potential sellers at the same time, some of those orders were most likely routed to a collection of high-frequency traders for just 30 milliseconds — 0.03 seconds — in what are known as flash orders. While markets are supposed to ensure transparency by showing orders to everyone simultaneously, a loophole in regulations allows marketplaces like Nasdaq to show traders some orders ahead of everyone else in exchange for a fee. In less than half a second, high-frequency traders gained a valuable insight: the hunger for Broadcom was growing. Their computers began buying up Broadcom shares and then reselling them to the slower investors at higher prices. The overall price of Broadcom began to rise. Soon, thousands of orders began flooding the markets as high-frequency software went into high gear. Automatic programs began issuing and canceling tiny orders within milliseconds to determine how much the slower traders were willing to pay. The high-frequency computers quickly determined that some investors’ upper limit was $26.40. The price shot to $26.39, and high-frequency programs began offering to sell hundreds of thousands of shares. The result is that the slower-moving investors paid $1.4 million for about 56,000 shares, or $7,800 more than if they had been able to move as quickly as the high-frequency traders.
looks like market manipulation rather than front running. high freq traders gaming the system. front running would involve the broker/investment advisor trading ahead of his clients to get favorable prices.
Without analyzing the rest of the article (which I suspect contains some errors (some of them serious)), I’d like to note that $7,800 is less that 0.6% of $1.4 million.
This week’s Economist explores the answer: http://www.economist.com/businessfinance/displaystory.cfm?story_id=14133802 Algorithmic trading causes concern among investors and regulators THE arrest of a former Goldman Sachs employee in July for allegedly stealing the firm’s proprietary computer codes thrust the arcane world of high-frequency trading (HFT) into the spotlight. The glare of attention is intensifying. High-frequency traders are essential providers of liquidity—accounting for roughly 50% of trading volume on the New York Stock Exchange—and can claim to have squashed bid-ask spreads. But many claim HFT comes at the price of gouging other investors. The basic idea of HFT is to use clever algorithms and super-fast computers to detect and exploit market movements. To avoid signalling their intentions to the market, institutional investors trade large orders in small blocks—often in lots of 100 to 500 shares—and within specified price ranges. High-frequency traders attempt to uncover how much an investor is willing to pay (or sell for) by sending out a stream of probing quotes that are swiftly cancelled until they elicit a response. The traders then buy or short the targeted stock ahead of the investor, offering it to them a fraction of a second later for a tiny profit. Another popular HFT strategy is to collect rebates that exchanges offer to liquidity providers. High-frequency traders will quickly outbid investors before immediately selling the shares to the investor at the slightly higher purchase price, collecting a rebate of one-quarter of a cent on both trades. Other tactics include piggybacking on sharp price movements to increase volatility, which increases the value of options held by traders. The speeds are mind-boggling. High-frequency traders may execute 1,000 trades per second; exchanges can process trades in less than 500 microseconds (or millionths of a second). Asymmetric information is nothing new. Even its critics concede that most HFT is perfectly legal. But some of the advantages that accrue to high-frequency traders look unfair. Flash orders, a type of order displayed on certain exchanges for less than 500 microseconds, expose information that is only valuable to those with the fastest computers. By locating their servers at exchanges or in adjacent data centres traders can maximise speed. “It appears exchanges are conspiring with a privileged group of high-frequency traders in a massive fraud,” says Whitney Tilson, a fund manager. Requiring orders to be posted for at least a second would nullify the value of flash orders and of probing the market. A group that accounts for nearly 50% of a market also introduces systemic risk. Lime Brokerage, a technology provider, has raised the prospect of a rogue algorithm going awry. Many believe that last year’s extreme market volatility was heightened by high-frequency traders. According to Nassim Nicholas Taleb, an author and investor, HFT “magnifies changes and ultimately makes the system weaker”. The market can correct some of these problems. Institutions are developing their own algorithms to confuse high-frequency traders. Bigger investors are moving to “dark pools”, electronic trading venues that conceal an order’s size and origin. The London Stock Exchange announced in July that it was abolishing liquidity rebates. Regulators are also rolling up their sleeves. On July 24th Charles Schumer, a Democratic senator, urged the Securities and Exchange Commission to ban flash orders. As trading moves from milliseconds to microseconds to nanoseconds, everyone is learning to act more quickly.