Difference Between High-Frequency Trading and Algorithmic Trading

With the evolution of technology in financial markets, terms like algorithmic trading and high-frequency trading have become common. Although both involve computer-driven execution of trades, they differ significantly in their objectives, speed, and trading volume. This article explains the difference between these two advanced trading strategies and their roles in the Indian and global stock markets.

Algorithmic trading, or algo trading, is the use of computer-coded instructions (algorithms) to automate trading decisions and execution. These algorithms follow predefined criteria such as price, volume, timing, or other mathematical models.

Key Features of Algorithmic Trading

• Executes trades automatically
  

• Reduces human intervention and errors
  

• Strategies can include arbitrage, trend following, mean reversion, etc.
  

• Common among institutional and retail traders
  

High-frequency trading (HFT) is a specialized form of algorithmic trading that executes a vast number of orders within extremely short time frames, typically in microseconds or even nanoseconds.

Key Features of HFT

High-Frequency Trading (HFT) is characterised by several key features, including:

• Uses ultra-low latency infrastructure
  

• Relies on colocation services close to exchange servers
  

• Executes thousands of trades per second
  

• Seeks small profits per trade but scales through volume
  

Algorithmic trading and high-frequency trading differ across several important dimensions, as shown below:

Both algorithmic and high-frequency trading employ distinct strategies to capitalise on market opportunities:

In Algorithmic Trading

• Trend Following: Based on moving averages or momentum
  

• Arbitrage: Exploiting price differences between markets
  

• VWAP (Volume Weighted Average Price): Large orders split over time
  

• Mean Reversion: Betting on prices reverting to historical averages
  

In High-Frequency Trading

• Latency Arbitrage: Capitalising on speed differences across platforms
  

• Market Making: Placing simultaneous buy/sell orders to earn the spread
  

• Statistical Arbitrage: Using large datasets to find short-lived opportunities
  

• Liquidity Detection: Detecting large orders to front-run or shadow them
  

SEBI regulates algorithmic and high-frequency trading with stringent measures to promote fairness and transparency:

SEBI on Algorithmic Trading

• Mandates pre-approval of algo strategies
  

• Brokers must maintain audit trails of all algo orders
  

• Retail access to algos is subject to broker risk frameworks
  

SEBI on High-Frequency Trading

• Tight regulations on colocation access
  

• Exchanges must ensure fair latency architecture
  

• Proposal for randomisation of order queues to level the playing field
  

Algorithmic trading and high-frequency trading demand different levels of technological infrastructure, as outlined below:

Algorithmic trading and high-frequency trading each have distinct advantages and drawbacks to consider:

Pros of Algorithmic Trading

• Efficient execution
  

• Emotion-free decision making
  

• Reduces transaction costs over time
  

Cons

• Technical glitches can result in large losses
  

• Requires continuous monitoring and backtesting
  

Pros of HFT

• Provides market liquidity
  

• Enables tight bid-ask spreads
  

• Fastest reaction to market events
  

Cons

• May cause flash crashes
  

• Difficult to regulate due to speed
  

• Accessible mostly to large institutions
  

Different types of market participants adopt algorithmic and high-frequency trading strategies based on their objectives and resources:

Real-World Example

• A retail investor might use an algo to execute buy orders at 5-minute intervals to average out prices.
  

• An HFT firm might execute 1,000 trades in a second to capture a ₹0.10 spread repeatedly.
  

While both algorithmic trading and high-frequency trading leverage automation and data, their speed, intent, and complexity differ vastly. Algorithmic trading is more accessible and broadly applied, while HFT is an advanced, capital-intensive strategy often reserved for large institutions. Understanding the difference helps traders choose the right tools and strategies suited to their trading goals and risk appetite.

This content is for informational purposes only and the same should not be construed as investment advice. Bajaj Finserv Direct Limited shall not be liable or responsible for any investment decision that you may take based on this content.