What are Algorithmic Trading Strategies and How Do They Work?
- 5th February 2026
- 01:00 PM
- 10 min read
Algorithmic trading means the usage of computer programmes with predefined rules that help in automatic trade execution. The predefined rules are designed in a way so that the computer program can efficiently time the market, analyse trade volume, asset prices and thus streamline a trading process.
This sort of trading leverages the speed and precision of computer programmes that usually exceed human capabilities. Due to its effectiveness while trading, about 50% of trading across India is now being done through algo trading.
If you want to start with this type of trading, learn about it in this blog.
What is Algorithmic Trading?
As the dynamics of the investment market move fast, capturing profitable trading opportunities might seem difficult for you as a trader. It is because such opportunities often appear and then disappear in a matter of seconds.
If you put algorithmic trading in play here, with preset instructions, it might be able to catch such trading opportunities as it automates trades, responds to price changes almost instantly and might book you profits.
Alongside increasing speed of trade executions, algo trading strategies usually have a higher precision. It means while trading manually, you might make errors or wrong trading moves, which might lead to lost opportunities. Algorithmic trading eliminates the chances of human error, which allows you to trade more efficiently.
How Does Algorithmic Trading Work?
With an algorithmic trading approach as per your instructions, an underlying trading algorithm becomes able to trade in various types of securities. These usually include buying and selling of stocks, futures, options, etc:
-
Trade Criteria in Algo Trading
It includes two different criteria, such as buy and sell signals. For example, you might set a buy signal to open a long position when a 20-day moving average of the stock prices of a company surpasses its 50-day moving average. You might put a sell signal to liquidate the existing position if the 20-day moving average falls below its 50-day moving average.
-
System Implementation and Automation
Now this present trade criteria gets executed automatically. The underlying algorithm of the trading software tracks stock prices while calculating the 20-day and 50-day averages in real time. Thus, when the set instructions meet, the algorithm executes the buy or sell orders.
What are the Most Popular Algorithmic Trading Strategies?
While you might implement various popular trading strategies manually, you can increase the speed of such trade execution with precision. It is because you can fuse some of the popular trading strategies with algorithmic trading strategies, as shown below:
-
Trend Following Strategy
Using the algo trading strategies, you can implement a trend following strategy as a trader. Such a strategy is especially designed to identify and ride with ongoing trends in the market. To do this, algorithms usually process huge volumes of live and historical market data to locate patterns and trends in price movements of assets.
Once it locates the trend, e.g. upward or downward, the algorithm executes trades accordingly.
-
Mean Reversion Strategy
This strategy is based on the concept that asset prices might move back to their historical price range over time. Now, if an asset price rises or falls far from its average range, the underlying algorithms take it as the price might bounce back and place trades accordingly.
Suppose a stock price usually trades between INR 1000 and INR 1250. Now, due to a sudden turbulence, it has dropped to INR 900. Now, the algorithm detects this dip and places a buy order, assuming its price will revert.
-
Arbitrage Strategy
This strategy usually aims to capitalise on the price differences of the same asset trading on different exchanges or markets. Suppose a company’s stock trades on the NSE at INR 1000 and on the BSE it trades at INR 1050. An algo trading strategy automatically buys from the NSE and sells on the BSE, capturing INR 50 per share.
-
Market Timing Strategy
With the market timing strategy of trading algorithmic trading aims to locate ideal timings for entering or exiting the market, while booking potential profits. To do this, underlying algorithms analyse market signals and indicators.
-
Index Fund Rebalancing Strategy
Index funds generally rebalance their underlying asset allocations to align with their respective indices. Here, algo trading identifies any upcoming rebalancing event and detects which stocks might get impacted. Thus, as an algo trader, you can act in advance and might profit from the price movements.
-
VWAP and TWAP Execution Strategies
With the VWAP strategy, algorithms break large orders into smaller pieces. Then it trades the orders throughout a trading day, potentially matching the average weighted price by the volume traded. With TWAP, algorithmic trading aims to ignore the trade volume while distributing the order equally. It is generally effective for low-volume stocks or assets.
-
Machine Learning and AI-Based Algo Strategies
It continuously updates itself by collecting fresh data. This uses such data to update, learn from its earlier mistakes and prevent it from repeating. It leverages Natural Language Processing (NLP), which helps analyse news articles, reports, etc, to efficiently understand the market sentiment. Thus, unlike traditional algorithms, it helps in more precise trade executions.
With the PL Capital Group – Prabhudas Lilladher, you can invest in stocks, mutual funds and more using the PL Capital app. Download it today and start investing!
How to Build a Profitable Algo Trading Strategy?
Now that you have an idea of what is algorithmic trading is and how you can use algo trading strategies to book potential profits, you must learn how to build one. Here is a step-by-step guide explaining it:
Step 1: You must first have an adequate knowledge of how the financial or investment market works. They include learning how the equity, currency, derivative markets, etc, work. Also, you must understand regulatory requirements, liquidity, types of orders, etc, to proceed.
Step 2: You must also have a good grip on programming languages such as Python, Java, C++, etc., as these essentially convert your trading ideas into automated code.
Step 3: Outline your trading rule to design your algorithmic trading. It typically involves entry and exit conditions, position sizing, risk management, timeframe, etc. Here, you must clarify your trading logic so there is no ambiguity left.
Step 4: You must obtain reliable current and historical data of the market. Back-test your algorithm based on the historical data. Backtesting helps evaluate metrics like consistency, performance and drawdowns.
Step 5: Choose a reliable stockbroker such as PL that offers efficient APIs, provides reliable trade executions, and aligns with regulations by exchanges.
Step 6: Once you deploy your algo trading strategy on the broker’s platform, you must keep an eye on its performance. Review the risk management, quality of trade executions, etc. Depending on changing market conditions, make periodic adjustments to your algorithm.
What are the Benefits and Risks of Algo Trading?
Aside from noting how to develop an algo trading strategy, you must also note the detailed benefits and risks of it:
-
Benefits of Algo Trading
Here are some key benefits of using algorithmic trading to potentially boost your trading journey:
-
Instant Trade Executions
Algorithmic trading helps place and execute buy and sell orders almost instantly. Thus, it potentially enables you to grab on optimised profit-making opportunities, which you might miss while trading manually.
-
Helps Avert Price Movement
During a trading day, a market might move adversely, which might lead to losses when you trade manually. With quick order executions, it completes purchases or sales of assets before the market sentiment changes.
-
Risks of Algo Trading
Apart from its benefits, you must also note some of its risks to stay informed:
-
Risks of Latency
Success in algorithmic trading depends on its ability to make ultra-fast trades. Therefore, in case there is a higher latency or delay while executing orders, it might lead to losses, especially if the market is moving fast.
-
Technical dependency
The platform on which you deploy your algorithm must be reliable and stable. System glitches, internet connectivity issues, hardware failure, etc, might lead to investment losses.
Who Should Use Algorithmic Trading Strategies?
Retail traders who have a decent knowledge of underlying algorithms via Python, C++, etc, might choose to build an algorithm and implement specific strategies to trade. Also, traders can use user-friendly algorithm trading platforms of brokers to execute smaller trades.
Institutional investors use it to execute high-volume trades along with hedge funds and proprietary trading firms.
Conclusion
Algorithmic trading automates manual trading with underlying algorithms. It leads to a significantly faster order execution and helps book potential profit-making opportunities. With coding knowledge or using broker platforms, you can implement or use algorithms to automate your trades.
With PL, trade in stocks, invest in mutual funds, gold bonds, ETFs and more. Download the PL Capital app, create a Demat account and start investing!
Frequently Asked Questions
1. What is the best algorithmic trading strategy for beginners?
As a beginner, you might choose a trend-following strategy for algorithmic trading. With indicators such as the moving averages, you can implement it with simpler coding or use a readily available algo trading platform.
2. How does an algorithm decide when to buy or sell?
Algorithmic trading follows the set rules for time, trade volumes, price and other indicators that you set. When these conditions are met, it places buy or sell orders accordingly.
3. Is algorithmic trading profitable in the long run?
Yes, with an efficient trading strategy, effective risk management and periodic updates to the algorithm, it might be beneficial in the long run.
4. What are the risks involved in algorithmic trading?
Risks from latency of trade executions, technical issues, etc., are present in algorithmic trading. These might lead to missing opportunities and investment losses.
5. Can I create my own algorithmic trading strategy?
Yes, with efficient coding experience, you can choose to build a strategy of algo trading from scratch for more customisation. Otherwise, you can use readily available trading platforms that require no coding.
