Basics of Algorithmic Trading: Concepts, strategies and examples

Stock markets today operate at tremendous speeds, with thousands of trades executed every second. One way to participate in this trading is the use of automated systems known as algorithmic trading, or more commonly, "algo trading."

This article will explore what algorithmic trading is, explain how it functions, and outline both its benefits and disadvantages. This overview will allow investors, including those who prefer mutual funds, to gain insights into how algorithms influence modern-day investing.

• Table of contents

• What is algorithmic trading?
• Examples of simple trading algorithms
• How does algorithmic trading work?
• Strategies for algo trading
• Benefits of algo trading
• Disadvantages of algorithmic trading

What is algorithmic trading?

In simple terms, algorithmic trading involves computers automatically buying or selling stocks. Investors provide specific rules or instructions—known as algorithms—that tell computers exactly when, how, and at what price to buy or sell shares. This is the fundamental definition of algorithmic trading.

The main reasons investors prefer algo trading include:

• Faster trading speeds
• Removal of human emotions such as fear or greed
• Ability to trade 24/7
• Efficient execution of complex trading strategies

Examples of simple trading algorithms

To illustrate clearly how algorithmic trading works, here are some simple examples:

• Moving average algorithm:
  • Buys stocks when their price rises above the average price of the last 50 days.
  • Sells the stocks if their price falls below this 50-day average.
• Price level algorithm:
  • Automatically buys a stock if its price falls below a predetermined level, for example, Rs. 500.
  • Automatically sells when the stock reaches a specific higher price, say Rs. 600.

These examples of trading algorithms demonstrate typical ways computers help investors make trading decisions.

Read Also: Stock Market Trading: Meaning, Types, and Historical Context

How does algorithmic trading work?

Algorithmic trading follows these essential steps:

1. Defining rules: Investors create precise rules to govern buying and selling.
2. Continuous market monitoring: Algorithms track stock prices and market data without pause.
3. Executing automatic trades: Trades are placed immediately when conditions set by investors' rules are met, without human intervention.
4. Reviewing and optimising: Investors regularly evaluate performance and adjust their strategies to enhance results.

Algo trading essentially functions like a disciplined assistant, strictly following given instructions and acting promptly.

Strategies for algo trading

Common algorithmic trading strategies include:

• Trend-following strategy:
  • Buys stocks whose prices are consistently rising.
  • Sells these stocks when their upward price momentum weakens or reverses.
• Arbitrage strategy:
  • Finds price differences for the same stock listed on different stock exchanges.
  • Buys from an exchange offering a lower price and immediately sells on another exchange at a higher price to profit from the difference.
• Mean reversion strategy:
  • Assumes stock prices tend to revert to their historical average.
  • Buys stocks that are currently trading significantly below their average price, selling once prices recover.

These approaches enable investors to execute consistent, disciplined decisions, potentially improving profitability.

Read Also: What is Intraday Trading? Meaning, Types and Benefits

Benefits of algo trading

Some of the many benefits of algo trading include:

• Speed and efficiency: Algorithms execute trades within milliseconds, faster than any human trader.
• Enhanced accuracy: Computers significantly reduce errors such as entering wrong quantities or incorrect prices.
• Elimination of emotional bias: Trading occurs without emotional influences like fear or excitement, ensuring rational decisions.
• Consistent execution: Algorithms execute trades precisely, reducing missed opportunities

Disadvantages of algorithmic trading

Despite its many advantages, algo trading also presents certain disadvantages:

• Risk of system failures: Technical malfunctions or software glitches can result in unintended trades.
• Requirement for technical expertise: Developing and managing algorithms demands substantial technical knowledge and resources.
• Exposure to market risks: Sudden or unexpected market movements can cause algorithms to perform poorly, resulting in losses.
• Risks of excessive automation: Over-reliance on automated systems may reduce critical human judgement during unforeseen market situations.

Recognising these limitations can helps investors utilise algorithmic trading responsibly, balancing automation with careful oversight.

Conclusion

Now that we have an overview of what algorithmic trading is, how it operates, and its potential advantages and limitations, we know that it significantly influences modern investing, benefiting everyone from individual traders to large mutual fund companies. However, investors must remain aware of potential risks involved.

If this approach sounds complex, you can also consider investing in mutual funds, where investment decisions are made, and trades are executed by professional fund managers. This allows new investors to participate in the market and potentially benefit from its growth even if they don’t have the required time or expertise.

FAQs

How does algo trading work?

Algo trading executes trades automatically, following predefined rules and strategies.

Is algo trading profitable?

Algo trading can be profitable if properly designed, tested, and managed. However, like all trading methods, profitability is not guaranteed and depends on the judgements made by the investor and market conditions.

Is algo trading legal?

Yes, algorithmic trading is legal and adopted by institutional and individual investors in many countries.

Is algo trading allowed in India?

Algorithmic trading is regulated by the Securities and Exchange Board of India (SEBI), ensuring transparency and fairness. There are several rules designed to prevent market manipulation, ensure fair access, and maintain liquidity in the markets.