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Globally, the Stock Exchanges are the largest and most liquid securities market.

Many companies trade their stocks, including individuals, hedge funds, and significant companies. It’s normal to imagine that the place is filled with high-sounding traders bidding on stocks.

However, the reality is the opposite. We’re living in the artificial intelligence world where most of our work is automated by computers.

In this article, we’ll understand high-frequency trading and why these algorithmic practices are gaining popularity.

What is High-Frequency Trading?

High-Frequency Trading (HFT) is a process wherein computers are programmed to trade hundreds and thousands of times a second to make little profits over time.

Despite the fact we believe that actions are performed by expert traders, these are automated trading machines. Almost 80% of trading transactions occur between HFT computers that are cleverly programmed to get profits consistently.

HFT is profitable for many trading firms that carefully employ the technology by experimenting with their algorithms in different market scenarios. These computers come in different sizes, but the controversial ones come with complex high-frequency trading algorithms.

Generally, traders with high-speed execution win over normal traders. HFTs provide an essential playground for trading high turnover orders that churn out many profits better than a human could.

Continuing our exploration of HFTs, let’s get a deeper understanding of what happens behind the scenes.

Note: The information written in this article is solely for educational purposes, and shall not be construed as, financial advice. The content should not be understood as a recommendation and we highly recommend consulting with a financial advisor/consultant before making any decisions.

How Does HFT Work?

Now that you know what high-frequency trading is, it’s simpler to understand how these algorithms work.

Going by the name, high frequency means a high number of trades, maybe hundreds, thousands, or millions of stocks executed in fractions of seconds.

For instance, if you’re an experienced intraday trader, how many trades would you make in an hour or an entire day? Even if you’re very fast, you won’t be confident to take more than a few trades, right?

Contrary, an HFT system can perform hundreds and thousands of trades per second. That is why institutions and hedge funds use Algo trading systems to make trades because it’s humanly not possible doing it manually.

This opens the room for a new topic we’ll check now – the strategies!

High-Frequency Trading Strategies

High-Frequency trading is all about speed and strategies. Some well-known HFT strategies include index arbitrage trading, volatility trading, news-based, global macro strategy, etc.

Index Arbitrage Trading

Arbitrage is a trading strategy that attempts to profit from the price differences between two or more market indexes.

Based on the price differences, arbitrage trading may occur between the same index traded on two exchanges or between market instruments like ETFs and options that track the index movements.

Global Macro Strategy

Global macro strategies are executed by hedge funds and investment institutes based on the overall economic conditions around the world. Based on the global financial scenarios, these institutions build long and short positions in equity, currencies, commodities, futures markets, and bonds.

Hedge funds build global macro strategies by analyzing and making predictions based on major political events.

As an example, a hedge fund might build short positions in its stock exchange and invest the money in countries with growing economies if it sees that the economies of a country are headed into recession.

News-Based Strategy

Here’s an example of a news-based high-frequency strategy that works well in weak sentiment markets.

HFTs are designed in such a way that they keep looking for negative keywords associated with stocks all over the internet.

For instance, if the algorithms suddenly start getting keywords like fraud, cheating, and allegations during or after market hours, it triggers short selling trades inferring that some bad news may come out.

Similarly, when HFTs find positive financial keywords like bank approval, hike, and increment, they initiate long position orders to capture the market movements before the news is out.

Now, we’ll check how these strategies affect the overall stock market.

How HFT Impacts the Stock Market?

Algorithmic trading is known as high-frequency trading (HFT).

In milliseconds, computers can determine market patterns and carry out automated, programmed instructions to buy and sell instruments. As trades get executed faster, and trade volumes are significantly higher, HFT increases competition in the market. With increased liquidity, bid-ask spreads decline, leading to more efficient markets.

In the financial markets, retail investors trade because they have confidence in the integrity of the institutions and the stock exchange boards.

However, events of algorithmic trading create unusual market volatility like the Flash Crash. A lack of confidence in the markets causes some conservative investors to abandon them.

Components of High-Frequency Trading

Performing high-frequency-based trades is the final part of the whole strategy. A challenging part is to incorporate the decided strategy into an integrated algorithm that will place the buy and sell orders on your behalf.

Here are some basic components for building an efficient Algo trading system:

#1. Programmers

You’ll need highly skilled programmers to build the trading system. They should have extensive knowledge of stock markets, buying and selling orders, and how stock exchanges work. A better strategy is to hire people who have worked extensively on creating trading software.

#2. Programming Language

C++ is the most preferred programming language choice for building a trading system. Since C and C++ are complex languages, engineers may transition to a simpler language like Python for writing code easier and evaluating Algo trading structures.

#3. Networking

Provision for network connectivity and permissions to access the trading account for placing orders.

#4. Market Data

Access to stock market feeds to analyze the data and grab opportunities for placing high-frequency orders.

#5. Backtesting

A way to test a system before it is launched on a real market once it’s built, as well as the infrastructure required.

#6. Historical Data

Depending on the algorithm’s complexity, historical data may be available for backtesting.


  • Improved Liquidity: HFT improves the bid-asks spreads, thereby improving the overall liquidity in the market.
  • Making Use of Inefficiencies: With HFTs, you have a high chance of churning profits in just fractions of seconds; that’s not possible with the manual process.
  • Arbitrage Trading: HFTs keep finding stocks trading on different exchanges and execute long/short positions to pull profits from such scripts.
  • News-Based Trading Algorithms: HFTs provide the freedom to take trades based on news and capture aggressive market movements without emotions. On the other hand, humans are skeptical and refrain from taking trades when in doubt.

Just like the pros, HFTs come with many drawbacks, and here are a few of them.


  • High Infrastructure Cost: Since HFTs use advanced algorithms, IT infrastructure costs are also high. It means only giant financial institutions like investment banks, institutional investors, and hedge funds can afford these technologies, not the retailer investors.
  • Misleading Strategies: HFTs flood the market with fake orders without any intention of actually executing the placed orders. As soon as the price reaches a certain level, these orders get canceled, resulting in crashes, fake breakouts or breakdowns, etc.
  • Zero Sum Game: If only big institutions can practice HFTs, then who’ll they make money out of? The answer is small and retail investors. It means that giant institutions usually take money out of our pockets.

Now, we will explore some of the best resources for learning high-frequency trading.

Learning Resources

A common concern you may come up with is – How to Understand High-Frequency Trading? or How to learn more about HFTs?

Well, a simple approach is to build a solid foundation for the subject. After covering and understanding the basics, it’s easier to avoid jargoned numerical discussion. 

The essential books we found for High-Frequency Trading are:

Developing High-Frequency Trading Systems

If you’re a software developer with good programming skills, the Developing High-Frequency Trading Systems book is an ideal choice. It helps you create and optimize high-frequency trading systems using Java, C++, and Python.

The book steadily takes you from an HFT introduction to creating your trading system with the help of traditional HFT programming languages like C++ and Java. Next, you’ll learn how to use Python to achieve a higher performance accuracy with confidence.

Overall, it’s a book for software engineers who want to learn the technical side of HFTs and wants to create ultra-low latency systems.

Algorithmic and High-Frequency Trading (Mathematics, Finance, and Risk) 

The Algorithmic and High-Frequency Trading book is written for advanced-level mathematics users who understand calculus and dynamic programming problems.

You’ll get plenty of examples in every chapter, and most chapters conclude by showcasing a realistic application of trading data. Since it’s an advanced derivations book, you’ll need some mathematical maturity to understand the examples.

All About High-Frequency Trading 

All About High-Frequency Trading talks about deploying computer algorithms to understand market activities, perform trades and generate profits in a matter of seconds. 

Preview Product Rating Price
All About High-Frequency Trading (All About Series) All About High-Frequency Trading (All About Series) No ratings yet $16.90

The book will help you understand which markets are suitable for HFT, algorithmic strategies high-frequency traders use, risks, and upcoming technology advancements in High-Frequency Trading.

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems 

With an average rating of 3.2 stars out of 5, High-Frequency Trading by Irene Aldridge is the first edition to learn high-frequency algorithmic trading.

This book covers the essential aspects of HFTs and their importance from a business point of view that sets the foundation for developing trading systems. You’ll also get a brief idea about the post-trade analysis processes, such as important performance metrics and trading evaluations. 

High-Frequency Trading by Irene Aldridge – 2nd Edition

High-Frequency Trading book by Irene Aldridge is a revised edition of the book mentioned above. It helps you create a solid foundation for learning HFT in the first edition.

Preview Product Rating Price
High-Frequency Trading High-Frequency Trading $63.12

The second edition describes recent technological developments that enable HFTs to develop better efficiency in handling risk management strategies and safeguard information in uncertain markets.

It also includes various high-frequency trading strategies and tools for building an efficient HFT system.

High-Frequency Trading and Probability Theory (East China Normal University Scientific Reports)

The book on High-Frequency Trading and Probability Theory is all about treating HFT and technical chart analysis as science. It’s a good read for investors who wish to verify their technical analysis efficiency by the theory of stationary stochastic processes.

The authors of this book also reveal how to build IT infrastructure for creating high-frequency trading algorithms and obtaining arbitrage from financial markets.

Final Words

High-Frequency Trading is gaining more popularity, and more trading giants are developing advanced software to help themselves. Although it’s a fascinating process, it involves a certain level of risk.

Now, if you hear about High-Frequency Trading next time, you’ll know what it is and how different market participants use HFT for their benefits.

Next, you can check out the best stock market APIs.

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  • Rahul
    Rahul is a digital marketer and web developer. He keeps learning about new web development trends and helps people do online business. In his free time, he enjoys watching YouTube videos and reading psychology books.

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