Do you remember the first time you watched a price chart or a candlestick chart closely? Not casually, but with intent! You might have seen a continuously moving candlestick chart, moving up and down with longer and shorter candlesticks following one another. As you look at the chart, you realise that markets move in patterns, and rules can define these patterns.
This simple realisation is the beginning of your journey toward algo trading.
In recent years, India’s markets have transformed from bustling trading halls to quiet server rooms running millions of instructions per second. Retail investors can now access tools that were previously limited to large institutions.
A SEBI study from September 2024 states that “the profits were generated by larger entities that used trading algorithms, with 97% of FPI profits and 96% of proprietary trader profits coming from algorithmic trading.” (SEBI)
In this blog, we will discuss what is algo trading, how does it work, benefits, how it is different from manual trading and much more. Let’s quickly dive in and talk more about it.
Simply, trading with computer programmes that rely on the use of algorithms (pre-defined rules or instructions) for order execution is called algo trading. It can effectively remove human intervention from the execution phase of trading. A successful system is designed to rely on three core components: Strategy, Market Data and Automated Execution Engine.
Strategy: The brain of any algo trading operation is strategy. Strategy defines the logic where you define rules. Your logic could be technical indicator-based, price-action driven, or a hybrid of both. For example, if price breaks a level, retests it, and forms a rejection candle, you can execute a long trade.
Market Data: Market data becomes the eyes in algo trading. It is used to provide the required inputs or instruction. It requires accurate price, volume, and timing information to make decisions.
Automated Execution Engine: The hand that places the trade is an automated execution engine. It sends orders to the exchange through a Trade API, ensuring seamless operation.
These three components work together to identify and make the most of market opportunities. Now let’s understand how it works.
Algo trading systems use sophisticated computer programmes for automatic trade execution. The operational workflow of algorithmic trading follows a logical and structured sequence. You must know how it works:
Choose a Strategy and Define Trading Rules: To begin the algo trading process, select a specific strategy. You must first translate the strategy into code, defining precise entry and exit points.
Import Real-Time Market Data: The system then connects to a data feed. Thus, the system can monitor asset prices and volumes in real time.
The algorithm will then implement the following steps:
Algorithm Identifies Opportunity: The computer programme continuously scans the incoming data. It will look for conditions that match the predefined trading rules.
Automated System Executes Orders - After the algorithm has spotted a valid opportunity, it generates a signal. The system would immediately send buy or sell orders to the exchange without human delay.
Risk Controls Applied - Advanced algorithms can simultaneously apply risk checks, ensuring the order size remains within limits and the stop-loss parameters are in place.
The last step highlights your role in managing algo trading performance.
The process of algo trading flows from you to the algorithm and back to you. However, even as it begins with you as the trader, it considerably reduces human error instances.
There are various benefits associated with automation over traditional manual methods.
Strategies are the foundation of any algorithm. The idea behind algo trading is that you set the strategy and the computer system does the rest.
Different approaches apply to different market conditions. Here is a table outlining common algo trading strategies.
| Strategy Type | How it works | Example |
|---|---|---|
Trend Following | The algorithm would identify and follow established market trends. Technical indicators are used to determine market direction. | Buying a stock when its 50-day MA crosses above its 200-day MA. |
Mean Reversion | It is based on the assumption that prices will eventually return to their average level. To buy when prices are low and sell when they are high. | Buying a stock when its RSI (Relative Strength Index) drops below 30, indicating it is oversold. |
Arbitrage | The system exploits price differences for the same asset across different markets or forms. | Buying a stock on the NSE and simultaneously selling it on the BSE to profit from a small price difference. |
Now let’s understand the difference between Algo Trading vs Manual Trading
The automation in algo trading enhances efficiency of a trading strategy. The distinction between automated and manual trading lies in execution and capacity.
Here is a table summarising algo trading vs manual trading:
| Feature | Algo Trading | Manual Trading |
|---|---|---|
Speed | Order executed in milliseconds. | Depends on human reaction time. |
Emotion | Completely emotionless and disciplined. | Susceptible to emotions such as fear, greed, and hesitation. |
Capacity | Can simultaneously monitor hundreds of charts. | Limited to monitoring only a few screens at a time. |
Accuracy | Higher precision in order placement. | Prone to manual entry errors. |
Thus, algo trading can considerably reduce human errors in trading. However, the success of any algo trading strategy depends on the strength of the strategy, and the adoption of dynamic market conditions.
You have understood the nitty-gritties of algo trading, but how do you get hands-on experience? Let’s find out in our next section.
There are many automation benefits available for traders. However, you must know that this automation can also introduce specific risks.
Risks in algo trading can lead even the most perfect strategies to failure. Thus, effective risk management is the foundation of successful algo trading.
Here are three useful strategies to protect your capital.
Use Stop-Loss Automation: You should never rely on mental stop-losses. Automated systems can execute exits faster than any human reaction. With hard-coded stop-loss implementation, orders ensure that a position is automatically closed once it hits a predetermined loss level. Thus, you can prevent a single bad trade from spiralling into a catastrophic loss. This strategy especially works during flash crashes or periods of extreme volatility.
Start Small, Scale Gradually: Resisting the urge to deploy all your capital at once is the core of any risk management planning. You can begin with a small position size, representing a negligible fraction of their portfolio.
Avoid Over-Fitting Strategies: An algorithm tuned too finely to past market noise rather than genuine trends can result in over-fitting. You can mitigate this risk by keeping the strategy logic simple and robust. You can also validate models using out-of-sample data (data the model has not seen before) to ensure its adaptiveness to new and unseen market scenarios.
The SEBI has established a comprehensive framework to ensure the algorithmic trading ecosystem’s integrity. These regulations are designed to protect retail investors and maintain market stability.
Oversight Under SEBI Framework: The regulator has mandated that all algo strategies be approved by stock exchanges before deployment. This is a vetting process to ensure that algorithms do not pose a risk to the market's orderly functioning. Also, all algo orders are to be tagged with a unique identifier for precise audit trails and accountability.
Role of Brokers and APIs: Brokers are responsible for client algorithms’ audit and approval, ensuring built-in risk checks, such as order limits and margin validation for the APIs. To prevent unauthorised use, the use of open APIs is restricted, and access is typically granted only through secured and static IP addresses.
Compliance is Key: Adherence to these norms is mandatory for all retail traders. There are severe penalties for using unapproved algorithms or bypassing broker controls.
Such regulatory compliance is important to ensure a level playing field. They protect individual traders from the risks associated with unregulated and high-frequency trading practices.
The future of algorithmic trading in India seems robust with the right combination of strategy, risk management and compliance. But there is still space to explore and evolve in algo trading.
With the above, trade API testing environments and execution speeds can likely improve, making the field even more competitive.
Your journey begins with understanding the market through structure, levels, and disciplined entries. Algo trading simply takes that same clarity and scales it with greater speed, accuracy, and consistency.
However, in this domain, success requires a solid understanding of market mechanics and strict adherence to risk management. You can leverage a robust Trade API and follow regulatory guidelines to navigate the complexities of the Indian market with confidence.
Sources:
Activities such as manual data gathering, spontaneous market interpretation, ‘set-and-forget’ operations, and human emotional decisions are not a part of algo trading.
Yes, algo trading is legal, but it is strictly regulated by SEBI. Traders need to use exchange-approved platforms and APIs provided by registered brokers for regulatory compliance.
Key rules of algo trading include using SEBI-registered brokers, exchange approval of algorithms, unique "Algo IDs" tag in every order for tracking, and following strict order limits.
Algo trading fees include brokerage charges, platform or software subscriptions (for specific tools), and statutory taxes/exchange fees. The fees vary from free basic access to premium costs, required for high-frequency trading.
This article is for informational purposes only and does not constitute financial advice. It is not produced by the desk of the Kotak Securities Research Team, nor is it a report published by the Kotak Securities Research Team. The information presented is compiled from several secondary sources available on the internet and may change over time. Investors should conduct their own research and consult with financial professionals before making any investment decisions. Read the full disclaimer here.
Investments in securities market are subject to market risks, read all the related documents carefully before investing. Brokerage will not exceed SEBI prescribed limit. The securities are quoted as an example and not as a recommendation. SEBI Registration No-INZ000200137 Member Id NSE-08081; BSE-673; MSE-1024, MCX-56285, NCDEX-1262.