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Headlands Technologies LLC Blog Global quantitative trading firm Menu About Careers Blog Contact Posts Posted on May 1, 2024 May 3, 2024 Opinion: Rationalizing Latency Competition in High-Frequency Trading Introduction There is a common misunderstanding, even among practitioners, that low-latency trading is a waste of human talent and resources that could instead go to advancing physics or curing cancer. It’s been attacked by books like Flash Boys, governments trying to pass transaction taxes, and exchanges bending to pressure by implementing speed bumps or periodic batch auctions. This essay argues the positive case for HFT and latency competition based on four main reasons: (1) Low latency trading lowers spreads, (2) Economically significant things do happen on sub-millisecond time scales, (3) HFT is the optimization layer for capitalism, and (4) Markets are not a zero-sum game. Latency plays a significant role in how humans interact with the world. When we perceive and respond to stimuli, there is an inherent delay between the occurrence of an event and our reaction to it. This delay, or latency, is typically around 200 milliseconds, which is the time it takes for light to enter the eye, be converted into an electrical signal, traverse the brain’s neurons to decide on a response, and finally travel to the muscles to trigger an action. The implications of this latency extend beyond simple reactions. When we make decisions based on information from various sources, the age of that information can significantly impact the accuracy and effectiveness of our choices. For instance, reading news from a day-old newspaper means basing decisions on information that is 24 hours old. In the past, communication latency was even more pronounced. In 1776, Americans made decisions based on information about Europeans that was around 3 weeks old, due to the time it took for ships to cross the Atlantic. Latency also plays a role in more mundane interactions, such as negotiating the price of a used car. Both the buyer and seller enter the negotiation with pre-existing knowledge and expectations, but the actual negotiation process involves a rapid exchange of information through verbal and non-verbal cues. This high-frequency interaction helps both parties uncover additional information about the other’s willingness to pay or sell, ultimately leading to a mutually acceptable price. In essence, latency is present in all human interactions, from simple reactions to complex decision-making processes. Understanding the impact of latency on these interactions is crucial for developing effective strategies to manage and mitigate its effects, both in personal and professional contexts. The field of high-frequency trading has emerged as a means to address latency in financial markets, aiming to facilitate more efficient price discovery and reduce the potential for market distortions. Latency Increases Spreads One of the most important ways that HFT benefits markets is by reducing bid-ask spreads. The bid-ask spread is the difference between the highest price a buyer is willing to pay for an asset (the bid) and the lowest price a seller is willing to accept (the ask). Spreads represent the cost of transacting in a market – the wider the spread, the more expensive it is to trade. As a reminder, spreads matter so much because of the famous Coase Theorem from economics. Under the Coase Theorem, in a world with zero transaction costs the allocation of resources will be efficient regardless of the initial distribution of property rights, government tariffs, or organization of firms. But in the real world, transaction costs are never zero. And the biggest source of transaction costs in electronic markets is the bid-ask spread. The wider the spread, the more friction there is in the market, and the harder it is for prices to efficiently reflect all available information. Let’s see why spreads get tighter when latency is decreased. Market makers set the spread by posting bids and offers. Let’s take a bid for example. If the market maker is filled on the bid, they will want to hedge their risk on a similar security. Imagine you’re making markets on the S&P 500 futures in Chicago. If your bid is filled you are long S&P500. You need to hedge by selling short S&P 500 stocks in New York. If the latency to New York is high, then you may not be able to fill your hedge orders at a good price. In fact when market makers quote on S&P 500 futures they will use pricing logic to estimate their potential hedge prices, and only quote if there are reliable liquid hedges available in another market. High latency reduces the reliability of hedges. Let’s plug in some numbers. Say there’s a bid for the ETF SPY for $100 on Nasdaq in New York. Then market makers can bid CME ES futures for $99.99 in Chicago, since if they’re filled, they can hedge by selling to lock in a $0.01 profit in New York. However if latency is high, then by the time their sell order goes over the network from Chicago to NY, the Nasdaq bid might have dropped below $100, so the market maker either makes no profit or has a loss. Prices are volatile so the longer the order is in flight on the network, the more risk there is the price could drop. If latency is very long, market makers might only bid for ES for 99.98. Similarly the offer side will be wider so spreads will be wide. We can quantify this effect using some concepts from options pricing theory. A market maker’s quote is equivalent to writing an option that the market can execute against. The width of their quotes corresponds to the premium they charge for this option. And one of the key drivers of options premiums is time to expiry – the longer the option lasts, the more risk the option writer takes on, and thus the more expensive the option. In this context, latency is equivalent to time to expiry for a market maker. The longer it takes them to hedge an executed quote, the more risk they are exposed to, and the wider the spreads they will need to charge. Cutting latency is like reducing the lifespan of the options that market makers are implicitly short – it makes their job less risky and enables them to charge lower premiums, i.e., quote tighter spreads. If time to expiry is cut in half, then by Black-Scholes the option price goes down by 30% (sqrt(1) to sqrt(0.5)). Note there are other frictions that contribute to wider spreads, like monopolist exchanges charging high fees, so the 30% reduction would only apply to the liquidity-option-selling aspect of market making. Even bringing latency down from 100 microseconds to 10 microseconds significantly shrinks the option-selling cost of market making since volatility is spiky in short time intervals. In short time intervals rather than measuring time in wall clock time, volatility is proportional to market data packet time. A lot of market updates can happen in a few 10s of microseconds because market activity is bursty and discontinuous. Studies from around the world empirically confirm that HFT decreases spreads. The following summarize the conclusions of the SEC, a regulator from ESMA, and Bank of Canada- SEC: Algorithmic trading in general, and HFT specifically, increases the accuracy of prices and lowers transaction costs” European Securities and Markets Authority regulator: investments in high-frequency trading technology provide positive economic spillovers to the overall market since they reduce transaction costs not only for those who invest in this technology but for all market participants by enhancing the quality of securities markets.” Bank of Canada: Passive HFT entry leads to a tightening of the best incumbent bid-ask spread. … incumbents tighten spreads by approximately 0.8 basis points on average.” Sources: Gerig, Austin. High-Frequency Trading Synchonizes Prices in Financial Markets” (2012) https://www.sec.gov/files/dera-wp-hft-synchronizes.pdf In Clapham, B., Haferkorn, M. & Zimmermann, K. The Impact of...