Algorithmic (Algo) Trading

Algorithmic trading is an automated method of placing trades based on pre-defined instructions that consider factors like time, price, and volume.
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Algorithmic (Algo) Trading
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3 mins
18-June-2025

Algorithmic trading refers to the use of computer programmes with predefined rules to execute trades automatically in financial markets. These rules factor in elements like timing, price, and volume to streamline the trading process. It leverages machine speed and precision over human capabilities. By 2019, over 92% of Forex trades were algorithm-driven, highlighting its growing appeal among both institutional and retail investors.

What is algorithmic trading?

Algorithmic trading leverages computer programs executing pre-defined instructions (algorithms) to automate trade execution. This approach enables trading at speeds and frequencies surpassing human capabilities, potentially maximizing profit generation. These algorithms incorporate factors such as timing, price, quantity, and mathematical models to guide trading decisions. Beyond profit enhancement, algorithmic trading contributes to increased market liquidity and promotes a more systematic and objective trading environment by minimising the influence of human emotions on trading activities.

Examples of simple trading algorithms

Initiate a short position of 20 lots in GBP/USD if the rate exceeds 1.2012. For every 5-pip increase beyond this level, reduce the short by 2 lots. Conversely, for every 5-pip decline, expand the short position by 1 lot.
Buy 100,000 XYZ shares if the price dips below Rs. 200. For each 0.1% rise above Rs. 200, purchase an additional 1,000 shares. For every 0.1% drop below Rs. 200, sell 1,000 shares.

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How algorithmic trading works?

Algorithmic trading involves creating a set of instructions or code that enables a computer to automatically buy or sell securities like stocks, futures, or options. These trades are executed based on predefined parameters such as price, volume, timing, or complex mathematical models.

1. Trade criteria

The trading strategy employed involves the following criteria:

  • Buy signal: Initiate a long position (purchase 50 shares) when the 50-day moving average of the stock price surpasses the 200-day moving average.
  • Sell signal: Liquidate the existing position (sell all shares) when the 50-day moving average falls below the 200-day moving average.

2. System implementation

This trading strategy is executed through an automated system. The system continuously monitors the stock price and calculates the 50-day and 200-day moving averages in real-time. Upon detection of the specified buy or sell signal, the system automatically places the corresponding order.

3. Benefits

This automated approach eliminates the need for manual price monitoring, chart analysis, and order placement. By identifying and capitalizing on trading opportunities algorithmically, the system enhances efficiency and reduces the potential for human error.

Strategies for algo trading

If you are a seasoned trader, you may already be familiar with various manual trading strategies. Many of these techniques can also be used in algo trading. Let’s take a closer look at how to do algo trading using some popular trading strategies.

Trend following
This strategy focuses on identifying and capitalising on existing market trends using historical data to predict future price movement. You’d assume that the current trend will persist and position yourself in the same direction as the trend to benefit from its continuation.

Arbitrage
Arbitrage exploits price differences for the same asset across markets. It involves buying and selling simultaneously to benefit from discrepancies. This often demands sophisticated algorithms for rapid execution to secure profits before the price gap closes.

Mean reversion
Mean reversion strategies assume asset prices tend to return to their long-term average. You would look for substantial deviations from historical norms, trading on the expectation that the price will revert to its mean over time.

Index fund rebalancing
This involves anticipating changes index funds make to align with their benchmarks. Traders aim to act ahead of these adjustments, forecasting how large-scale fund activity might impact stock prices during the rebalancing period.

Market timing
Market timing strategies aim to pinpoint ideal moments to enter or exit trades by analysing indicators and market signals. The goal is to maximise returns by accurately predicting short-term price movements, requiring sharp analysis and swift execution.

Benefits of algo trading

Now that you know what algo trading is and how to do algo trading using common trading strategies, let’s take a closer look at the benefits of algo trading. These benefits include the following:

  • Traders receive optimal pricing on trades.

  • Trade orders are placed instantly and accurately.

  • Orders are executed quickly to minimise adverse price movement.

  • Emotional and psychological trading errors are significantly reduced.

  • Transaction costs are lower.

  • Multiple market conditions can be evaluated simultaneously.

  • Manual entry errors are greatly minimised.

  • Strategies can be tested using historical and real-time data.

  • Ideal for time-sensitive trading operations.

Disadvantages of algorithmic trading

Drawbacks of algorithmic trading are as follows:

  • Latency: Algorithmic trading necessitates rapid execution speeds and minimal latency to prevent missed opportunities or financial losses due to delayed trade execution.
  • Black swan events: Algorithmic trading relies on historical data and mathematical models to predict market trends. However, unforeseen market disruptions, commonly referred to as "black swan events," can lead to significant losses for algorithmic traders.
  • Technological dependence: Algorithmic trading heavily relies on technology, including computer programs and high-speed internet connections. Technical issues or failures can disrupt trading processes and result in financial losses.
  • Market impact: Large algorithmic trades can significantly impact market prices, potentially leading to losses for traders who cannot adjust their positions accordingly. Moreover, algorithmic trading has been implicated in increased market volatility, including instances of "flash crashes."
  • Regulatory compliance: Algorithmic trading is subject to various regulatory requirements and oversight, which can be complex and time-consuming to adhere to.
  • High capital costs: The development and implementation of algorithmic trading systems can be expensive. Traders may also incur ongoing fees for software and data feeds.
  • Limited customisation: Algorithmic trading systems operate based on predefined rules and instructions, potentially limiting traders' ability to tailor their trades to specific needs or preferences.
  • Lack of human judgment: Algorithmic trading relies on mathematical models and historical data, neglecting subjective and qualitative factors that can influence market movements. This absence of human judgment can be a disadvantage for traders who prefer a more intuitive or instinctive trading approach.

Conclusion

You need the right platforms and tools to fully leverage the many algo trading benefits. Today, many leading stockbrokers offer algo trading apps to help retail traders automate their trading strategies. However, before you use these tools, you must become well-acquainted with how to do algo trading in different market conditions.

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Frequently asked questions on algo trading

Do algorithmic trading really work?

Yes, algorithmic trading can be highly effective when used correctly. It automates trading decisions, executes orders faster than humans, and removes emotional biases. However, its success relies on the strength of the algorithm, market conditions, and solid risk management. Proper backtesting and ongoing monitoring are essential for consistent results.    

Is algo trading available in India?

Algo trading in India has witnessed substantial growth, with its contribution to total turnover exceeding 50% from a modest 9% in 2010.

Does algo trading work?

Yes, algorithmic trading can work well when built and managed properly. It uses rule-based systems to make fast, emotion-free trades, taking advantage of market inefficiencies. However, performance depends on the strategy's quality, changing market dynamics, and effective risk control. Backtesting and constant monitoring are key to long-term success.

Is algo trading profitable?

Yes, algorithmic trading is legal and regulated in India. The Securities and Exchange Board of India (SEBI) oversees its use in the markets. Traders must follow specific compliance norms and technical guidelines when deploying automated strategies on recognised exchanges.

Is algo trading legal?

Algorithmic trading is generally permissible within the legal frameworks of most developed economies, including the United States, the United Kingdom, and India. Regulatory oversight, as exercised by bodies like the SEC and SEBI, is crucial to maintain market integrity. Adherence to the specific regulations and guidelines established by these authorities is paramount to prevent market manipulation and ensure transparency in algorithmic trading practices.

Is algo trading allowed in India?

Yes, algorithmic trading is permitted in India. The Securities and Exchange Board of India (SEBI) regulates algorithmic trading in the Indian markets. However, there are specific guidelines and regulations that need to be adhered to by market participants engaging in algo trading.

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