Traders can adopt countless styles in their work, but one of the most controversial and fascinating ones is high-frequency trading, or HFT. You might have already heard about it in passing but want to learn more.
So, what is high-frequency trading? Could this style be right for you? Let’s take a look at what it entails and its various pros and cons.
What is high-frequency trading?
High-frequency trading is a type of automated trading that uses powerful computers to buy and sell financial assets incredibly quickly. The term “high frequency” refers to how quickly these trades are completed. They may take place in minutes, seconds or even milliseconds.
What Is High-Frequency Trading?
High-frequency trading is a type of automated trading that uses powerful computers to buy and sell financial assets incredibly quickly. The term “high frequency” refers to how quickly these trades are completed. They may take place in minutes, seconds or even milliseconds.
One of the core principles of high-frequency trading is to generate small profits on a very large number of trades. Unlike long-term investing, which aims to make substantial returns on a few carefully selected assets, HFT strategies focus on capturing minuscule price differences on thousands or even millions of trades per day. While the profit from each individual trade is minimal, the sheer volume and speed at which they are executed can add up to substantial overall gains.
How High-Frequency Trading Works
High-frequency trading uses powerful computers and advanced software to execute an enormous number of trades at extremely high speeds — often measured in microseconds, or even milliseconds. The goal is to capitalize on very small price changes that may vanish in the blink of an eye.
To achieve this, HFT firms rely on highly automated systems that integrate global market data, trading algorithms and ultra-low-latency infrastructure. Together, these systems continuously monitor multiple trading ecosystems, analyze price movements and place orders in real time. This level of automation allows high-frequency traders to process vast amounts of data and identify fleeting opportunities that humans would never notice on their own. For example, a price difference of just a fraction of a cent might exist between the same asset on two different exchanges. HFT algorithms can detect that discrepancy instantly — buying low on one exchange and selling high on another — thus capturing a small profit on each transaction. Repeated at a high volume and speed, these tiny margins add up to large sums of money.
The rapid rise of automated trading over the past several years has largely been driven by advances in computing power, the digitization of global financial markets and the regulatory changes that opened the door for electronic trading. As a result, HFT has become a dominant force in modern markets, accounting for a significant share of trading volume today — particularly in highly liquid asset classes like equities, futures and currency.
How to Get Started With High-Frequency Trading
When you’re a high-frequency trader, speed is the name of the game. You want to be able to get in and out of the market as quickly as possible so you can make your next move before anyone else even knows what happened. To get started, you will first need a HFT system.
An Overview of HFT Systems
When building an HFT system, consider how to make it fault-tolerant and scalable. A sophisticated system must handle many types of failure without disrupting its operations. Malicious agents in high-risk situations can cause DDOSes by disrupting market access for others.
In a microservice architecture, different components in the system should be able to run on different servers. This allows you to scale by adding more servers as needed.
When trading live, your system will encounter errors. Some might be related to third-party issues like broker DDOS attacks. Such an attack involves flooding a targeted network or server with internet traffic to the point that its normal operations are disrupting. When using a microservice design, schedulers aim to reboot a failing service quickly.
In highly volatile scenarios, malevolent agents may initiate DDOS attacks to obstruct others’ access to the market, causing your scrapper to fail. The microservice architecture is designed to be fault tolerant. If a single service fails, the system can keep functioning without it. This setup makes it easier for you to troubleshoot and fix issues as they arise.
For example, you can’t guarantee full market access in fluctuating market conditions (such as during high volatility and low liquidity periods).
The Components of HFT Systems
The components of an HFT system include the database, scrapper, quantitative model, order executor and quantitative analysis. These components work together to cull information and make informed purchase orders at lightning speeds:
- Database: The high-density time series database must handle hundreds of thousands of data insertions every day. It must also be scalable to execute high-speed resampling in an immutable and distributed manner.
- Scrapper: A scrapper is a crucial part of any HFT system. This software component is designed to collect real-time market and financial data from stock exchanges and API integrations. A scraper interacts with the database and must operate with low latency to provide the most up-to-date information to inform their orders.
- Quantitative Model: This is a custom algorithm that helps make fast trading decisions by analyzing market data like price, volume and trends to identify trading opportunities. When markets aren’t liquid, they can also help minimize slippage. Slippage, which occurs at any time in the market and affects all traders, is defined as the difference between expected and actual prices.
- Order Executor: You need a good microsystem to execute your positions well. Instead of market orders, you can execute limit orders, which take longer and may need to be modified depending on market liquidity. With limit orders, you can set a price that is the highest at which you want to buy shares. Your order may not be executed if the market trades above or below this level.
- Quantitative Analysis: Analysts can customize the tools they use to their needs: many types of graphs help reveal data, but histograms that show ranges are also ideal for this purpose. Linear regressions, which help determine whether a correlation exists between sets, can provide another way to see relationships. Thanks to Python-based tools like Streamlit, analysts can now easily generate their own models. With such convenient techniques and advanced technology, it has never been easier for researchers to conduct quantitative analysis.
What Are the Benefits of High-Frequency Trading?
HFT has become so prevalent that it’s frequently cited as a major contributor to the stock market’s volatility. But generally speaking, HFT has two noteworthy benefits:
Reduced Bid-Ask Spreads
The bid-ask spread refers to the difference between what buyers are willing to pay for an asset and what others are asking for. HFT firms can act as market makers, placing orders at high speed and improving pricing for traders.
For example, a study on HFT fee implementation in Canada found that when HFT activity decreased with higher fees, bid-ask spreads widened 9 percent among retail investors, while charges to institutional traders rose 13 percent. This suggests that HFT activity helps keep spreads low.
Improved Market Liquidity
Higher HFT fees result in greater disparities between the bid and ask prices. Increased liquidity tends to reduce the gap between prices of bid and ask orders, making markets more efficient.
What Are the Drawbacks of High-Frequency Trading?
In the past decade, high-frequency trading has become a major force in financial markets. The increased use of HFT has attracted considerable criticism for its efforts on the capital markets and unfair advantage for institutions.
Market Instability
The method relies on mathematical models and computers rather than human judgment and interaction, replacing a number of broker-dealers. This means decisions in HFT happen in split seconds, which can result in surprisingly big market fluctuations. For example, on May 6, 2010, the DJIA dropped 1,000 points, or 10 percent, in just 20 minutes — the largest intraday point decrease in DJIA history. Following their own investigation, government authorities found that a massive order triggered a selling frenzy and caused the crash.
Unfair Institutional Advantages
Another concern about HFT is that it gives an unfair advantage to large financial institutions over individual investors. Individual, small investors are at a disadvantage because they lack the resources and speed to process information as efficiently as high-frequency trading computers.
Phantom Liquidity
Critics also object to HFT’s “phantom liquidity,” which refers to its ability to appear and disappear quickly, arguing that it makes markets less stable. Phantom liquidity is one of the outcomes of low-latency activities in high-speed friendly exchange structures. It emerges when a single trader — an HFT specifically — places duplicate orders in multiple venues.
How Has High-Frequency Trading Affected the Market?
The world of trading has undergone a profound transformation in recent years, largely driven by the rise of high-frequency trading. These ultra-fast, algorithm-driven strategies have reshaped how markets operate across asset classes — including foreign exchanges, exchange trade funds (ETFs) and commodities.
HFT has contributed to the overall growth in trading volume and market activity, affecting investors at all levels. While large, established firms like Virtu Financial and Citadel Services have come to dominate the market, smaller trading firms and fintech startups are now active competitors as well, enabled by lower barriers to entry and technological advancements.
Meanwhile, the scope of high-frequency trading is expanding. What began purely as algorithmic trading is now being enhanced by emerging technologies like cloud computing, artificial intelligence and machine learning. These tools can help firms analyze market patterns and optimize strategies and process data even faster.
Try High-Frequency Trading for Yourself
High-frequency trading is a growing phenomenon in the financial world, but it’s been around for several years. It involves using computer algorithms to place trades at a very high rate of speed, often within a fraction of a second. This enables larger profits when done correctly, but it also comes with many risks that can result in massive losses.
Investors must be careful not to succumb to the temptation of taking these risks without fully understanding them and their potential outcomes. This is why it’s important for investors to learn more about high-frequency trading before deciding if they want to participate in it.
Frequently Asked Questions
How does high-frequency trading work?
High-frequency trading uses powerful hardware and specialized algorithms to place and execute trades in milliseconds. This method enables traders to profit from small price fluctuations at a high volume.
What are the disadvantages of high-frequency trading?
High-frequency trading has several upsides and can benefit institutional investors and savvy traders, but it also has its disadvantages to know about:
- Steep learning curve: Creating an HFT system requires high-performance computers and coding knowledge to create a robust system that can cull data and execute trades while fending internal bugs and possible malicious agents.
- Institutional advantages: The technical and data requirements for high-frequency trading gives institutions an unfair advantage compared to individual traders.
- Phantom liquidity: Critics of HFT techniques claim that methods create unstable markets and increase volatility.
What is the difference between high-frequency trading and day trading?
High-frequency trading and day trading both involve trading financial assets, but differ on their speed, technology and strategy.
- HFT uses algorithms and specialized computers to analyze data and execute orders in milliseconds. Institutional investors use this technique to profit on small price fluctuations on financial assets.
- Day trading is popular among individual investors and does not use advanced algorithms, making the process more manual. Traders using the strategy often seek to leverage momentum in trending stocks or assets.
