As it appeared on TSCI Street Pulse - January 11, 2010
Algorithmic trading techniques and (HFT) high frequency trading have dramatically altered the behavior of U.S. equity markets. If you are an active, short term trader, you have probably noticed that the markets have radically changed, and have become increasingly more difficult to trade. The development of AT was initially intended to be a solution for the reduced liquidity in the markets (as a result of decimalization), and then as a tool to more effectively arbitrage disparities in the markets. However, people often find alternative ways to profit from technological solutions, by bending the rules and exploiting the system, and algorithmic trading is no exception to the rule.
Before traders can begin to adapt to the new trading environment, traders need to understand how algorithmic trading techniques work, and the effects they have on the markets. While algorithmic trading was not developed originally for the purpose of implementing the toxic or predatory strategies described below, these techniques dramatically affect the way the market trades in the short term, and if not recognized will place the individual trader at a substantial disadvantage.
Liquidity-rebate traders take advantage of volume rebates of about 0.25 cents per share offered by exchanges to brokers who post orders, providing liquidity to the market. When they spot a large order, they fill parts of it, then re-offer the shares at the same price, collecting the exchange fee for providing liquidity to the market. This strategy doesn't require the trader to make a profit on the trade. If the trader breaks even, or even loses a small amount on the trade, the rebates he receives for providing liquidity, will generate a profit.
Predatory algorithmic traders take advantage of the institutional computers that chop up large orders into many small ones. By placing small buy orders that are quickly canceled, the predatory algo trader, fools the institutional computer into bidding up the price of the stock. After the price of the stock, is forced up to an artificially inflated level, the "predatory algo" shorts the stock.
Automated market makers "ping" stocks to identify large reserve book orders by issuing an order very quickly, then withdrawing it. By doing this, they obtain information on a large buyer's limits. They use this information to "front -run" orders by buying shares elsewhere and selling them to the institution they traded in front of.
Program traders buy large numbers of stocks at the same time to fool institutional computers into triggering large orders, creating volatile market moves. The program traders race the large orders, taking profits against, the very orders they triggered to move higher.
Finally, flash traders expose an order to only one exchange. They execute the order only if it can be carried out on that exchange without going through the "best price" procedure intended to give sellers on all exchanges a chance at best price execution. The SEC has now promised to ban this technique.
My personal trading strategy includes, looking for technical setups, interpreting price action, analyzing capital flows, and utilizing a disciplined money management methodology. The previously mentioned practices have led to the following changes in the market's behavior, and forced me to adapt accordingly.
Buying new highs, and selling new lows, rarely works now. Chasing momentum can be like chasing your own tail, as the market rarely follows through. Passive algorithms designed to sell-the-new-high, or buy-the-new low, dictate that traders need to take into account this phenomena, and make adjustments.
As a result of HFT, stocks touch more price points and may cause you to be stopped out of more positions. Algorithms are configured to "hunt stops", forcing the market to reach prices, that would not be reached under normal conditions, and elect stops. In addition, false buy and sell signals are more prevalent now, as competing algos battle one another.
Large institutional buy or sell orders, that used to move the market dramatically, are now executed more efficiently, and have less impact on the market. This makes momentum trading less profitable, and more difficult.
Limit orders may be difficult or impossible to get filled as HFT programs "step in front" of your orders, and slippage is greater, as programs drop the bids for lower prices, when they sense a sell order, or raise their offers, when they sense a buy order.
Traders' percentage of winning trades is likely to drop, and their risk-reward ratio may be less favorable now, so it is important, that money management remains the most important part of their trading strategy. In the "new" market dominated by HFT , setups that might have previously worked extremely well, either no longer work, or work marginally. However, variations on these setups might work extremely well, if adapted properly to the HFT environment. In other words, if you know what the HFTs are doing, and the effect they are having on the market, you can wait for the algos to do their thing, and react accordingly.
If traders want to remain successful, they must periodically remake themselves and their trading, by learning to adapt to changing market conditions. They first need to recognize why and how the markets have changed, and then they need to adjust their trading style so they can successfully adapt to how the markets currently trade. Loopholes in market rules give high-speed traders an unfair advantage, by allowing them to see what others are doing, or intending to do. Their computers can essentially trick or fool slower traders' computers, into giving up profits, and can do so in milliseconds. The repercussions of these actions have irrevocably changed the way the market trades, and has forced successful traders to adapt to a new market dynamic.
