High Frequency Trading (HFT) is a very powerful segment of modern financial markets. HFT essentially involves the use of advanced algorithms along with high-speed computing systems to execute millions of trades in a fraction of a second. HFT is not new, and top hedge funds and institutional traders create HFT strategies that dominate a large portion of daily trading volumes in equities, futures, options, and even crypto markets. Whether it is Wall Street hedge funds or Indian Indian proprietary trading firms, each of them is trying to capitalize on tiny price inefficiencies, and make a profit from arbitrage opportunities across different exchanges or asset classes at lightning speed.

What is High-Frequency Trading (HFT)?

High Frequency Trading (HFT) is a specialised type of algorithmic trading that focuses on powerful computers, ultra-fast data feeds, and complex algorithms to execute a large number of orders at extremely high speeds. These data capture, logic building and order placement can sometimes be completed within microseconds. The main goal of HFT is to exploit short-lived market inefficiencies or arbitrage opportunities to capture small profits on each trade, multiplied across thousands or millions of trades.

Some of the key characteristics of HFT are the following:

• Speed: HFTs thrive on speed, and a minor difference of 1 millisecond can mean the difference between profit and loss.

• Automation: Since the trades are taken at such high speeds, all trades are strictly executed by algorithms without human intervention.

• High order volume: The profit per trade is very small, hence HFT systems may place thousands of orders per second.

• Short holding periods: Since HFT strategies are mostly arbitrage strategies, positions are often held for only a few seconds or milliseconds.

• Co-location & low latency networks: Speed is very important for HFT firms, and they pay to place their servers near exchange infrastructure to reduce delay.

How High-Frequency Trading Works

High Frequency Trading is highly complex and is achieved through a perfect combination of technology, data and algorithms. Here is the step-by-step process of how HFT works:

Market Data Ingestion
HFT systems get a stream of real-time data from the exchange. The data contains different levels of detail and is classified as L1 and L2. Some of the information contained in the data is current open orders (limit), order books and executed prices.

Microsecond-Level Analysis
Once the data is received, the algorithms instantly start detecting arbitrage opportunities, pricing errors, or order imbalances.

Decision-Making Engine 

Based on pre-set logic, strategies and machine learning models, the algo system is able to determine if and when to place a trade.

Trade Execution
Once the decision is reached, the live orders are executed within microseconds using ultra-low latency infrastructure. The HFT traders are able to achieve such speeds because their servers are located near exchange data centres, called co-location servers.

Order Modification or Cancellation
Many times, the orders are not executed because other HFT players might be able to take the orders quickly. Hence, the orders may be updated or cancelled just as quickly, depending on market conditions. In fact, over 90% of HFT orders are cancelled before execution.

Post-Trade Risk Monitoring
The risk management is super strong in HFT systems. Real-time systems monitor trades for compliance, exposure limits, and profitability. This is also a mandate from SEBI so that there are no market manipulations.

Here is the infrastructure summary of how HFT systems achieve low latency:

How Fast Is a High-Frequency Trade?

HFT systems are extremely fast. The orders are placed and cancelled in microseconds (μs) or nanoseconds (ns). That's a million times faster than a human blink. Here are just some numbers to give an idea of the frequency:

HFT systems can only work because of the speed. Even if there is a delay of even 1 millisecond, it can cause a missed opportunity or slippage. Most top HFT firms spend millions to shave off microseconds using custom hardware, optimised code, and faster-than-light communication lines. The end goal is to ensure that the orders are fastest to reach the exchange because that would mean higher odds of capturing the best price before the market moves.

Key Features of HFT

HFT is a complete ecosystem of automation, precision, and scale. Here are the key features of HFT systems: 

1. Ultra-Low Latency

The name “High Frequency Trading” means that these systems need high frequency to be profitable. HFT firms must ensure that they keep reducing delays in data processing and order execution. As a retail trader, we might look at charts at a 1-minute time frame, but for HFT systems, the latency is measured in microseconds.

2. Algorithmic Execution

Trades are fully automated using pre-programmed algorithms designed to analyse market conditions and react instantly.

3. High Order Volume

HFT systems only make small profits. So they send thousands of orders per second, often cancelling most of them. If some HFT firm abuses this feature, it's known as “order stuffing”.

4. Market Making

HFT firms provide liquidity to the exchanges and act as market makers. They provide depth to both the bid and ask side of the book by simultaneously placing buy and sell orders. One of their strategies is to profit from the bid-ask spread.

5. Arbitrage Strategies

HFT algorithms are created to exploit tiny price differences across exchanges. These are called latency arbitrage strategies. HFT systems also trade related instruments such as cash and futures, which is called statistical arbitrage.

6. Short Holding Periods

HFT trades are usually held for very short times, ranging from milliseconds to seconds. The orders are either executed or, if they are not executed at the price that the HFT wants, the orders are cancelled immediately. 

7. Co-location & Direct Market Access

HFT firms pay a lot of money to have the best infrastructure. Since getting the live feed and placing an order needs to be quick, HFT place their servers physically close to exchange infrastructure, giving them a speed advantage through Direct Market Access (DMA).

How is High-Frequency Trading Different from Algorithmic Trading?

Here is the difference between HFT and algo trading:

High-Frequency Trading vs. Traditional Trading

Here is the difference between HFT and traditional trading. 

Advantages of High-Frequency Trading

HFT offers a lot of advantages to both the owners and the trading markets. Here are some of these advantages:

1. Increased Market Liquidity

HFT firms usually act as market makers, where they place a massive number of buy and sell orders on both sides of the book. This ensures tight bid-ask spreads and higher trade availability. This benefits all market participants.

2. Efficient Price Discovery

Price discovery means getting the fair price based on the market forces and current market information. HFT systems are able to react to market information within microseconds, which helps prices adjust quickly to new data, improving overall market efficiency.

3. Arbitrage and Mispricing Correction

Sometimes the pricing of the assets can be mispriced. HFT algorithms exploit such mispricing across markets, which helps to eliminate inefficiencies.

4. Reduced Trading Costs

One of the biggest costs of trading as a retail trader is the slippage cost. HFT systems help to provide liquidity to the market, which narrows spreads and thereby reduces the execution costs for retail traders.

Risks and Criticism of HFT

While High-Frequency Trading (HFT) brings speed and liquidity to markets, there are also some risks associated with HFT. 

1. Market Volatility

A lot of the time, we notice that there is sudden volatility in the market. Sudden issues with algorithms can lead to sharp, unexplained price swings, as seen during events like the 2010 Flash Crash.

2. Lack of Transparency

Most of the HFT strategies are proprietary by nature, and hence, the rules of the strategies are not shared by the firms. It is also hard to track how HFT affects price formation. This lack of transparency can lead to informational asymmetry between the HFT traders and retail traders.

3. Unfair Speed Advantage

There have been some concerns that since HFT firms have an unfair advantage in getting faster prices, they have an edge over retail and slower institutional traders. This has raised concerns about unequal market access.

4. Systemic Risk

There can be issues such as “fat finger”, which can lead to systemic risk in the market. Also, since the HFT firms compete against each other, automated trading systems can try to better the price, which can create feedback loops, which can invariably lead to escalating errors or triggering cascading sell-offs in milliseconds.

Regulatory Framework for HFT

HFT is one of the highly regulated businesses, and SEBI has robust regulations around algorithmic and high-frequency trading. The aim is to ensure fairness, transparency, and market stability while fostering innovation in trading technology.

As per the new regulations and working paper by SEBI, algo trading and HFT are defined as any order generated using automated execution logic. This includes order placement without manual intervention and use of automated strategies like arbitrage, market making and even  options strategies. There are more regulations for HFT, such as which strategies should be approved by the exchange, and the definition of HFT also includes if there are more than 10 trades per second. 

Some of the key regulations on HFT in India are:

1. Colocation and Fair Access

There are co-location services offered by Indian exchanges, such as NSE, which allow the HFT firms to place their servers close to the exchange for faster access. SEBI is considering whether there should be extra rules imposed on such HFT firms to curb the unfair latency advantage.

2. Algo Approval & Testing

SEBI, in its new working paper, has suggested that the algorithms must be submitted by the algo trading firms for exchange approval before deployment. It is also required to maintain logs of each algorithm version and parameter changes. This will help in doing an audit in case there are some issues or errors in the algorithm.

3. Risk Controls & Order Throttling

Since HFT is completely automated, there can be some errors that trigger massive systemic risk in the market. HFT firms must thus implement pre-trade risk checks such as quantity and price validation, fat finger error controls and maximum order-to-trade ratios. Also, one of the major issues in HFT is a lot of order cancellations, and SEBI monitors very carefully to curb quote stuffing.

4. Penalties for Misuse

SEBI is very strict in imposing monetary fines on HFT firms in case of mistakes made by their algorithms. SEBI has also previously launched investigations under the SEBI Prohibition of Fraudulent and Unfair Trade Practices (PFUTP) Regulations to ensure that all HFT firms are working with ethics.