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  • Corey Voorman

High Frequency Trading Strategies


There are a few different types of actors in the world’s security exchanges. Some wear suits, others trade foreign currency from their parents’ homes and dorm rooms, and others furiously press buy on their Robinhood apps over their lunch breaks. Another class of trader is tucked safely in a glass cabinet in a basement, this trader is covered in flashing lights and has fiber optic cables protruding out at all angles. High frequency trading is the sort of Wall Street phrase that makes the average pension holders’ hands get a bit damp and the high school math aficionado’s dreams a bit brighter at night. What if making money in the stock market was as simple as using the computing power in that old PC you own to make money while you spend it? Unfortunately, the market is a bit more complex and competitive than most folks realize at first glance.


High frequency trading (HFT) is characterized, not surprisingly, by speed. Arguably the usage of telegraph lines in the 1930’s to quickly disseminate information to ready traders at the exchanges was a primitive form of high frequency trading. HFT is characterized by reactive trading which was given a boost in the 1980’s when the NASDAQ and other exchanges allowed for electronic trading. One of the early beneficiaries of high speed trading strategies were those who owned property near major exchanges. The theory and practice was that the shorter your fiber optic cable was, the quicker you could trade. With powerful computing algorithms and trades that occur within a billionth of a second, the only latency would be caused by cable length. Imagine being concerned about the delay of information traveling at the speed of light from two blocks away versus one block. Currently, many exchanges allow their computer market makers and traders to live in cabinets in the basement, leveling the playing field for speed.


Now the defining factor of success for high frequency trading is simply the trading system or algorithm that the computers are tasked to implement. There are trading strategies that immediately comb news articles or tweets searching for key words such as “earnings”, “shares drop” or “Wall Street Bets”. That move aggressively to trade according to the strategy their program dictates. There are even algorithms designed to prey on other algorithms, spoofing or quote stuffing to make small sums off of their slower or more poorly written computational competitors. The code for these HFT programs are closely guarded by their owners. Those who employ HFT strategies know that as soon as their strategy is analyzed, replicated or understood, the tiny informational edge they hold will be destroyed, making them less profitable.

Many restrictions exist for algorithmic HFT programs on exchanges. Certain market exchanges have limits to the HFT strategies that can be employed. However there are certain exchanges such as dark pools, or brokerages with internal trading operations who are happy to let HFT strategies plug into their capital pools, of course, for a fee. Some who oppose HFT strategies state that the presence of robotic traders can create unintended consequences such as recursion loops which could drive individual security prices down or up aggressively. Many of the HFT programs are designed to combat these events from happening, or even dampen volatility by taking the opposite side of trades in billionths of a second. Many HFT programs often provide liquidity and a smaller bid ask spread for securities that are purchased passing a better price onto the person buying the security. HFT strategies are pure speculation and traders who press buy or sell from their mobile devices 3 times a week should always account for the veracity, speed and resources of the competition they face. Investors who own profitable companies with strong management purchased at a good price have no quarrel to pick with HFT algorithms as short term price fluctuations do not impede their long term strategy.

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