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Explore what algorithmic trading means, how it functions in modern financial markets, and the advantages and risks of using automated trading systems.
Algorithmic trading, often referred to as algo trading, is the use of computer programmes to execute financial trades according to pre-defined instructions. These algorithms consider variables such as time, price, quantity, and other complex mathematical models. This automation aims to execute orders faster and more efficiently than a human trader. In India, algorithmic trading has gained prominence, especially among institutional investors, and is gradually becoming accessible to retail traders via regulated platforms.
Algorithmic trading automates the trading process using coded instructions. These algorithms analyse market conditions in real-time and place buy or sell orders based on pre-set logic. The approach eliminates manual intervention and often enhances execution speed, consistency, and accuracy.
Algo trading is essentially rule-based trading where the system reacts to market inputs as per the algorithm's logic. This logic is based on tested strategies involving technical indicators, price patterns, or statistical models.
SEBI defines algorithmic trading as any order that is generated using automated execution logic. Platforms offering algorithmic trading services must comply with SEBI guidelines for risk management, audit trails, and transparency.
Understanding the process helps demystify how technology drives trades:
Market Data Feed: Real-time prices, volumes, and other indicators.
Algorithm Logic: The code that interprets data and makes trading decisions.
Execution System: Connects to a stock exchange to place and manage orders.
Risk Controls: Prevent trades that breach limits or logical flaws.
Algorithms often use:
Price and volume movements
Moving averages (50-day, 200-day)
Historical volatility
Time of day
Different strategies suit different market conditions and risk appetites:
These use indicators like moving averages and momentum oscillators to identify market trends and execute trades in the direction of those trends.
These involve exploiting price discrepancies of the same stock across different markets or instruments.
Used for ETF (Exchange Traded Fund) management or index replication, these track performance metrics and rebalance portfolios accordingly.
Based on the belief that prices tend to revert to their average over time. When prices deviate significantly, the algorithm initiates trades assuming a correction.
Executes trades in proportion to volume distribution to minimise market impact.
Spreads the order evenly across a given time to avoid sudden market movements.
Algorithms can execute orders in milliseconds, improving the likelihood of achieving desired price points.
Automated trading can reduce costs related to manual processes and slippage.
Algorithms do not suffer from human emotions, thereby maintaining objectivity.
Algorithms strictly follow the coded logic, ensuring consistent application of trading rules.
While beneficial, algorithmic trading also comes with potential drawbacks:
System outages, coding bugs, or incorrect input data can result in unintended trades or losses.
Strategies fine-tuned using past data may not perform well in future markets.
Traders must follow SEBI norms, and failing to do so can lead to penalties.
Excessive automation in illiquid markets can lead to sudden price swings.
SEBI has laid out comprehensive guidelines to regulate algorithmic trading:
Platforms must maintain logs of all trades and orders.
Real-time risk checks must be implemented.
APIs must be secure and regulated.
Retail investors can use algorithmic trading via approved brokers who offer pre-approved strategies or platforms compliant with SEBI’s framework.
A range of market participants can access algorithmic systems:
Institutional traders
SEBI-registered brokers
SEBI-compliant retail platforms
Wealth management firms
Reliable infrastructure is essential for successful algorithmic trading:
These connect trading logic with broker platforms or exchanges for execution.
Low-latency and scalable infrastructure improves execution speed.
Popular languages include Python, Java, and C++, each offering robust support for financial modelling and API integration.
Logic Flow:
If 50-day moving average > 200-day moving average
And trade volume > 1,00,000 shares
Then place a buy order for 100 shares
This is a basic trend-following strategy that uses crossover and volume confirmation.
A comparative view helps illustrate their distinct advantages:
Feature |
Algorithmic Trading |
Manual Trading |
|---|---|---|
Speed |
Milliseconds |
Minutes |
Emotional Influence |
None |
Present |
Accuracy |
High |
Variable |
Scalability |
Very high |
Limited |
Monitoring Needs |
Minimal |
Continuous |
The table shows that algorithmic trading brings speed and consistency but needs technical setup and regulatory adherence.
Awareness of these factors can help investors make informed decisions:
Ensure regulatory compliance
Backtest strategies adequately
Understand the platform’s limitations
Confirm that risk controls are active
Algorithmic trading integrates data, logic, and speed to automate market activity. While it enables enhanced execution and reduces human biases, it also demands a solid grasp of programming, risk management, and regulations. With SEBI offering a structured framework for retail and institutional access, algo trading continues to evolve in India’s growing digital marketplace.
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.
Sources
Groww — Benefits of Algorithmic Trading in Stock Market, https://groww.in/blog/benefits-of-algorithmic-trading-in-stock-market
Groww — How to Start Algorithmic Trading? Complete Guide, https://groww.in/blog/how-to-start-algorithmic-trading
SEBI — Participation of Retail Investors in Algorithmic Trading, https://www.sebi.gov.in/reports-and-statistics/reports/dec-2024/participation-of-retail-investors-in-algorithmic-trading_89837.html
Algorithmic trading is a method where computers execute buy or sell orders based on predefined rules such as timing, price, and quantity.
It uses software programmes that analyse market data and place trades when specific conditions coded into the programme are met.
Yes, it is permitted and regulated by SEBI. Traders must comply with platform-level and regulatory norms to use algorithmic systems.
It improves speed, reduces emotional influence, enhances cost efficiency, and ensures consistent execution.
Yes, retail traders can use it through SEBI-compliant brokers and platforms offering approved strategies.
