While high frequency trading is highly profitable for the companies developing the algorithms, few understand how they work in any detail. HFT shops are filled with mathematical and computer science Ph.D's writing sophisticated algorithms that no one outside the industry can comprehend. A report out of TABB Group in July 2009, a financial markets research and strategic advisory firm focused on capital markets, claimed that while HFT firms represent only 2% of the 20,000 trading firms in the US, these firms account for 73% of all US equity trading volume. HFT firms are a force to be reckoned with and a reality in today’s markets.
What is high frequency trading?
High frequency trading, also known as algorithmic or black-box trading, is the use of computer programs for the execution of trading strategies. The program is written such that all decisions for time of entry, price and quantity are pre-defined and executed without human intervention. Algorithmic trading has long been used by buy-side institutional investors to execute large orders effectively by minimizing the price impact of the order. Rebate algos have also been around for a while seeking to provide liquidity and capture the rebates paid by ECNs. Active traders see these algos constantly creating the bid and offer in high volume large cap stocks. More recently though, there has been a large explosion in predatory algorithm development. Predatory algos attempt to detect larger players in the market and front run those orders.
While HFT has increased liquidity and tightened spreads in large cap names, small cap companies have actually seen spreads increase according to NYSE Arca data. Investment Technology Group’s trading costs for small-cap stocks were 40% higher in Q2 2009 than Q1 2008, reflecting the inability to get trades processed and rising commission costs. Joseph Saluzzi of Themis Trading, a lone voice in bringing HFT to light, has argued that this is because of predatory algos.
With HFTs as dominant players in the market, active traders need to learn as much as they can about them. First, high frequency trading strategies are highly dependent on ultra-low latency. Many shops have their servers co-located on the exchanges to provide the fastest possible execution. Second, the coding is under constant evolution because of exceptionally high competition among participants and the micro precision of strategies that means they may only be effective for days at a time.
Clearly, any strategies that have an edge based on speed are out the window with the increase in high frequency trading. While the active trader used to front run the order of the institutional desk that was inefficient in execution, now even the small trader’s order is front run by the computer algorithm. Every human trader is now the inefficiency with their slower execution. Entering and exiting stocks will also be tougher. Any active trader is quite used to seeing his order front run immediately as he shows his bid or offer making it more difficult for him to get a fill. There is a high likelihood that active traders must become used to paying an added toll to HFTs for entering and exiting their positions.
The trading business is forever changing, that we know for sure. Level II strategies based on speed of execution are certainly on the decline. Active human traders must therefore become more sophisticated. First, minimize the impact of HFT by trading “in-play” stocks that have large volume from “real” players. Second, avoid non-volatile stocks trading below average volumes. Third, greater anticipation based on sound technical analysis is also needed. Most of us will need to fight hard for better prices and avoid the temptation to buy highs or short lows as algos are programmed to manipulate prices around these areas. Fourth, many of us will need to cut down our size and look for larger moves in stocks. Scalping very small moves is not nearly as profitable when a predatory algo scalps 3 cents from you on your buy and another 3 cents on your sell, just as a hypothetical. Also, levels in stocks are not as clear-cut because algos are programmed to push stocks through the level to shake out weak holders. But, if you can begin trading for dollar moves on less size, you’re less likely to notice the 6 cents you paid as a toll and you’ll be able to give the stock a little extra room around levels.
In order to successfully navigate through the choppiness that HFT has brought into equity markets, traders must spend an increasing amount of their after-hours time researching and learning levels. Spend more time analyzing charts on multiple time-frames. For traders who focus on very small timeframes, now might be the time to take a step back, decrease size, and look for setups and levels on higher timeframes. The higher the timeframe, the more powerful the setup and level and the harder it is for an algo to overtly cloud the area. Additionally, familiarity as to how particular stocks trade around levels helps provide the confidence necessary to follow-through on your ideas. Traders need to develop a universe of familiarity—a core group of “in-play” stocks and sectors—to follow each and every day. The more often you we trade a particular vehicle, the more familiar we become with how algos work in that particular stock.
These are not fail-safe rules but HFT is a reality and it is here to stay. Active traders must adjust and come to find a new edge beyond speed of execution. Where there’s movement, there’s opportunity and the survivors in our business will become more sophisticated in order to continue trading profitably.