A typical at-home retail trader gives little thought to what happens in those few seconds between the time he clicks that buy order to when those shares get credited into his account. He remains unaware of the fact that out there, situated in close vicinity to the massive servers of his traded stock exchange, are fast predatory supercomputers capable of executing the same buy order tens of thousands of times in that duration. The financial markets have seen a transition into a more computerized domain with the advent of High-frequency Trading (HFT). This up-and-coming field has seen a new symbiotic relationship between professional traders and software experts trying to breach new speed barriers. A typical high frequency trader is capable of executing an order in about 64 microseconds. For perspective, the average human eye blinks in roughly 150 milliseconds, more than a thousand times slower!
If you have ever traded a share or invested in a mutual fund, it is almost certain that you have been affected by the tactics and strategies of high frequency traders. The supporters of HFT often glorify their contributions to the markets which are grossly overestimated. It is true that HFTs have significantly increased the liquidity in the markets and have allowed for tighter bid-ask spreads, but this hardly gives the true picture. HFT firms are known to provide liquidity to the thicker side of the order book and completely withdraw their funds in situations of crisis. What we are left with are a group of efficient vulture-like algorithms pecking a sum off every trade that takes place. While the exact nature of their role in the markets is under constant debate, they play an important role in an ever more technology-oriented market.
But how do these firms actually make money and why is there a cut-throat competition to become the fastest. High frequency trading firms engage in a variety of trading strategies that are well beyond the potential of any other market participant due to their mind-boggling speed. Such digital agility allows them to move past traditional technical and fundamental analysis for devising more creative methods to capitalize on opportunities.
Some of these tech facilitated, speed reliant gameplans are discussed here:
Market Making and Liquidity Rebates
The most precious element in the stock market is the presence of liquidity. Especially for short-term traders, the ability to buy and sell a given number of shares at any moment is of utmost importance. This need is both understood and exploited by high frequency traders.
The stock market not only contains exchanges where stocks are listed but also include electronic marketplaces called ECNs (Electronic Network Communications). ECNs are nothing but automated markets that directly match buyers and sellers without middlemen. These markets provide something known as rebates, i.e., traders are essentially paid to add liquidity and charged to take it out. While the monetary incentives for liquidity providers is miniscule, only a few fractions of a cent per share, HFT firms are capable of practically churning out a risk-free income by simply sending out large volumes of buy and sell limit orders.
In lines with the necessity of liquidity, many HFT firms also engage in the strategy of market making. This involves the consistent maintenance of demand and supply by the trader, generally an HFT firm or a large financial institution. These ‘big players’ trade from both sides in the market, and always stand ready to buy or sell securities. As a compensation for the risk and service offered, they receive the spread- which is the difference between the highest buying price (bid) and the lowest selling price (ask).
Latency Arbitrage
The most infamous strategy of modern-day HFT firms is latency arbitrage which has been criticized for being unethical and disadvantageous to other participants. In simple words, latency arbitrage is a method through which HFT firms front-run institutional and retail traders.
This strategy can be explained through a simple example. Let us consider a wholesale electronics buyer, Max looking to buy 3000 mobiles. To meet his demand, he goes to the store that is the closest to him, Store A. However, he is only successful in purchasing 1000 mobiles due to a shortage in the stock. He then progresses to the second closest option, Store B. Here, he purchases an additional 1000 mobiles and faces the same issue. Meanwhile, a nearby vendor, Chris, becomes aware of the wholesale buyer’s demand and rushes over to Store C to purchase all the mobiles at market price. Thus, when Max reaches the final store, he is forced to buy the mobiles at a higher than usual price from the only available seller- Chris. This was only possible due to Chris’s superiority in speed and information.
A similar structure is seen in the stock market as well. Large market exchanges like NASDAQ and NYSE often send their bids and offers to subsidiary networks known as ECNs (analogous to the stores in the above example). When institutional traders and private investors place large buy orders, these are evenly split up and sent to the ECN servers. As a result of differing distances, the closest ECN is bound to receive the order a few hundred microseconds prior! This gives our HFT firms enough time to race over to the more distant ECNs (like Store B and C) and purchase large volumes of the desired stock. This same stock is sold back to the institutions at a higher price, allowing the firm to profit.
Momentum ignition
As the name suggests, this strategy is based on a false ignition or spark in the price of a stock caused by the high frequency trader. At critical levels of support and resistance, these firms use their speed and volume to breach important technical levels. Under this false pretense, a large number of traders join the price spurt and create a momentum in the respective direction. This causes a further surge or decline in price. At this moment the firm exits the position allowing it to profit off the false move that it had induced.
Since these situations are artificially created, the momentum slowly fizzles out and the price quickly adjusts back to a state of equilibrium. Thus, traders who joined at the tail-end of this impulsive move would bear losses.
These complex strategies definitely allow HFT firms to extract maximum compensation from the markets they trade in. These firms are capable of churning out a positive income for almost every single day in a year. The principal reason that allows them to beat the market consistently is not the complexity of their strategies but the statistical edge behind them.
The Role of Statistics : A case Study on Virtu Financial
The true mechanics of their profitability were witnessed in the initial public offering of a prominent HFT firm by the name of Virtu Financial which was brought to the market in mid-2015. According to its prospectus, out of the 1278 total trading days, Virtu was profitable in 1277. Virtu had a win rate (percentage of successful trades) of just 51%. This meant that, even assuming a 51%-win rate, 24% loss rate and 25% break-even, Virtu typically made $0.0027 per share. Despite this, it was successful in making roughly $10 million every single day. The secret to this lies in the volume of transactions. Virtu executed between 2.5-3.5 million trades every single day across all its asset classes.
But that still doesn’t explain how they are able to make money every single day without fail.
This can be explained by the above table. Here, the daily edge refers to the probability of the firm to be profitable by the end of the day. Now assume that the firm takes part in only a single trade in the entire day. This means that it has a 51% chance of making money and 49% chance of not making money, based on the previously mentioned win-rate. As its trades increase to 100, the probability of making income more than half of the time becomes more defined. The point being, if a trial is repeated for a significant number of times, its expected probability becomes more and more defined. Thus, even with a win-rate slightly above half, Virtu is assured a profitable day due to the high volume of trades.
While HFT firms deserve the frequency bashing they receive for promoting an unfair market with extremely high barriers to entry, they also teach us a new way of thinking about and going around conventional systems. Instead of being contained within the box or thinking outside the box, they challenge the very notion of the metaphorical box.
Samarth Khanduri
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