High-Frequency Trading Comprehensive Analysis: Strategies, Risks, and Market Adaptation

What is High-Frequency Trading?

High-Frequency Trading (abbreviated as HFT) is a trading strategy that utilizes computers to enter and exit the market within milliseconds or even microseconds. Compared to traditional investing, the core features of HFT are extremely fast transaction speeds and very short holding periods. Traders profit by capturing tiny price fluctuations in the market.

In the era before widespread computer technology, a few highly responsive traders could manually perform “manual high-frequency” operations. However, with technological advancements, human reaction speeds can no longer compete with algorithms. Today, market makers and other institutions use high-speed computers to execute large volumes of orders in extremely short timeframes, dynamically adjust quotes, manage risks, and maintain market liquidity.

The history of high-frequency trading is closely linked to the evolution of electronic trading systems. From the initial need to trade in person at exchanges, to telephone orders, and now to automated computer programs, each step has dramatically increased trading speed and scale. Early HFT traders used complex mathematical models and statistical analysis to identify price discrepancies between different markets or exchanges, exploiting the principle that “price differences will eventually converge” to perform arbitrage and generate profits.

For example, if Bitcoin prices on the US exchange are higher than on the Japanese exchange, arbitrageurs can sell in the US and buy in Japan, waiting for the price gap to close before closing the position for profit. This riskless arbitrage was once a primary source of profit for HFT.

Advanced Techniques in High-Frequency Trading

Beyond traditional arbitrage, HFT has developed more complex strategies. Some participants establish positions first, then place large virtual buy or sell orders to create the illusion of “big players’ optimism/pessimism,” attracting other investors to follow and buy or sell, thereby pushing prices up or down. Once the price moves in the anticipated direction, these traders quickly cancel their virtual orders and close their positions to realize the spread. In other words, HFT doesn’t necessarily require actual trades; it cleverly uses market psychology and information asymmetry to steer prices favorably.

As HFT’s share in global markets continues to grow, ordinary investors may not need to engage in HFT directly but should understand its operational logic to better grasp market dynamics.

The Double-Edged Impact of High-Frequency Trading on Markets

Positive Effect: Increased Liquidity

HFT indeed brings benefits to the market. Although it involves virtual orders, a significant proportion of transactions still occur, promoting market circulation. The high volume of trading activity makes assets easier to buy and sell, attracting more retail investors into the market.

Negative Risks: Amplified Volatility

HFT can also intensify market volatility. Since traders profit from market fluctuations, their strategies tend to magnify upward and downward swings—regardless of the market direction, they can profit. When these trades are automated, market shocks can lead to profits and losses being amplified infinitely, creating a “rising and falling together” effect.

Cost Consideration: Government Tax Revenue

HFT involves a large number of transactions, generating substantial transaction fees and taxes. While these costs are negligible for well-funded institutions, they represent significant revenue for governments. Therefore, governments have not banned HFT; instead, they have used taxation to achieve a kind of win-win situation.

Pioneers in Quantitative Investing: The Legendary Story of Jim Simons

When discussing HFT and quantitative investing, one cannot ignore mathematician Jim Simons. Born in 1938, Simons earned his Ph.D. in mathematics at the age of 23. During his career, he worked in intelligence as a code-breaking expert and later became a master of geometry in academia, but ultimately chose to apply his mathematical talents to investing.

In 1982, Simons founded Renaissance Technologies and established the Medallion Fund. From 1989 to 2006, this fund achieved an astonishing average annual return of 38.5%, far surpassing traditional hedge funds. Simons is thus hailed as the “King of Quantitative Investing.”

Simons’ secret to success lies in using complex mathematical and statistical models to detect tiny market price movements. As the company grew, he assembled hundreds of top experts to develop automated trading systems—driven by over 10 million lines of code—enabling highly efficient operations with minimal human intervention.

By the end of 2019, Renaissance managed assets worth approximately $130.1 billion. Notably, during the intense market volatility of 2020, the fund still achieved a 39% growth, with a net profit of 24% after fees. Simons’ case demonstrates the powerful potential of quantitative HFT but also highlights the high demands for mathematics, computing, and capital in this field.

The Three Main Strategies of High-Frequency Trading

1. Market Making Strategy

Market making is the most common HFT method. Traders continuously place and cancel orders to create the illusion of active trading in an asset, attracting other market participants and pushing prices up or down. They then quickly close their positions for profit. This approach is similar to market making for newly listed stocks but executed at much higher speed and frequency.

2. Arbitrage Strategy

Arbitrage exploits price differences of the same asset across different exchanges, different time periods of similar assets, or between futures and spot markets. Traders predict that these price gaps will eventually close and buy low/sell high or sell high/buy low to earn riskless or low-risk profits.

3. Trend Following

Trend trading follows market directions, aiming to profit from the middle of a trend. Traders often seize opportunities when companies release major news—such as large purchases after earnings reports or shorting during negative news—amplifying the movement. Unlike market making, trend following is based on real events or market sentiment rather than creating false signals.

Core Risks of High-Frequency Trading

Risk 1: Psychological and Discipline Challenges

HFT demands excellent mental resilience and strict discipline. Since decisions must be made in extremely short timeframes, hesitation or emotional reactions can lead to significant losses. Many traders fall into the “adding to losing positions” mentality—continuously increasing their positions to recover losses, ultimately deepening their trouble.

Risk 2: Hardware and Network Requirements

HFT essentially involves competing for “mispricings” caused by time delays. Multiple parties race to exploit the same opportunity, making advanced equipment and stable, low-latency networks crucial. Even milliseconds or microseconds of lag or disconnection can prevent order execution or cause slippage losses. In this competitive arena, outdated equipment can cause you to lose outright to rivals.

Risk 3: Transaction Costs Erosion

Due to the extremely high trading frequency, transaction fees and taxes can eat up most profits. Many retail investors attempting HFT find that their annual gains are less than the fees charged by brokers and exchanges. This underscores the importance of choosing low-cost trading environments.

Which Markets Are Most Suitable for High-Frequency Trading?

Markets suitable for HFT should have two core features:

Feature 1: Sufficient Market Size and Liquidity

HFT requires entering and exiting large positions within short periods. If the market is too small or lacks liquidity, traders face difficulties executing trades, increased slippage, or even inability to trade. Additionally, sufficient volatility is necessary to provide profit opportunities. Generally, larger markets with higher liquidity and volatility are more suitable for HFT.

Feature 2: Low Tax and Fee Environment

Since HFT involves massive trading volume, transaction costs and taxes constitute a significant portion of expenses. If costs are too high, capturing tiny spreads becomes unprofitable, possibly leading to losses. Therefore, markets with low taxes and fees give HFT traders a decisive advantage.

Based on these criteria, the U.S. stock market is one of the most suitable venues globally for HFT. It has a vast participant base—not only domestic investors but also global capital. Its market size far exceeds other countries’ entire markets, with enormous trading volumes. For example, a single day’s Tesla trading volume (around $17.636 billion) is comparable to Taiwan’s entire daily trading volume (~NT$200 billion).

Moreover, U.S. stock trading fees and taxes are much lower than Taiwan’s: the U.S. stock transaction tax is 0.00051%, with zero commission fees; in contrast, Taiwan’s transaction tax is 0.3% (0.15% for day trading), and the fee is 0.1425%. This huge difference is a decisive competitive advantage for HFT.

Additionally, the U.S. market offers ample trading hours. Taiwan’s market opens from 08:45 to 13:45, while the U.S. includes pre-market, regular, and after-hours trading, allowing participants across different time zones to engage, further increasing trading opportunities.