August 01, 2023
4 mins read
Algorithmic trading is changing the way traders engage the market. Instead of spending the whole day simply looking at prices, they can rely on a computer to do that for them. It will follow the rules they implement – when to take action, how much to do, and what criteria would prompt one way or the other.
While the idea comes from traders, the system does the hard work. It takes out the emotional component and allows them to remain consistent in your approach.
Traders are still expected to design, test and polish their strategy. Algorithmic trading allows you to act quickly and follow your logic in fast-moving markets.
Summary
Algorithmic trading blends speed, data, and automation to offer a powerful approach to modern markets. But success in algo trading isn't just about technology—it also depends on your understanding of market dynamics, risk tolerance, and strategy design. Relying solely on automation without robust testing or monitoring can result in significant losses. To truly benefit from algorithmic systems, you need to stay informed, continually evaluate performance, and make adjustments as market conditions evolve. With the right foundation and discipline, algorithmic trading can help you scale your efforts while keeping your decisions rule-based and data-driven.
Algorithmic trading, commonly referred to as algo trading, involves the use of a computer program to automatically place trades based on rules set by humans. They are based on inputs from humans, who tell them what to look for — a price, time, or trend — and they will act when the conditions they have asked for are met. You don't have to sit there in a trance state or make impulsive decisions. As soon as you set your conditions, the system watches and reacts.
In India, algo trading can be seen with both institutions and individual traders. You have the idea, the program does the trading, and your order gets executed just to your specification, each time with no thought.
In algorithmic trading, you create specific instructions for a computer to carry out based on your thinking. You might define rules such as “buy when the price rises above a certain average” and “sell when the volume drops below a specified amount.”
Once the market conditions are met, your system will make the trade immediately — no pause, no indecision. You can back-test them on historical data so you know what to expect in advance.
You remain the decision-maker while the algorithm takes care of executing the trade. It is like having a trusty assistant who never gets tired, never panics, and always implements your plan exactly.
Before creating a strategy, you should know your goals and the level of risk you are comfortable with. Each algorithmic trading approach suits a different mindset. Here are a few that can help you structure your plan better.
Trend Following Strategy: You use this when you think the market will continue going in one direction. The algorithm will identify a trend somewhere using tools like moving averages and trade automatically once it sees momentum in that direction.
Arbitrage Strategy: You take advantage of the price differences for the same asset on 2 different platforms. The system will execute the trades on both sides instantly in the hopes of taking the small difference before it disappears, ideally maximising the arbitrage as much as possible.
Mean Reversion Strategy: You assume prices will return to the average price eventually. The algorithm will act somewhat when prices go too far from that mean, with the reasonable assumption that it is likely to correct, therefore returning to that more normal range.
Statistical Arbitrage Strategy: You are looking at a data model to find patterns in the underlying price, in addition to patterns in the effects of data between different securities. The system will trade when it finds that prices temporarily do not match data, so you are creating trades based on more data-based logic rather than guesswork.
Utilising algorithmic trading not only streamlines your process but also relieves you of the stress of constant monitoring. It gives you structure to your routine and provides you with the option to act more rapidly. Here are some benefits you can expect.
Lower transaction costs: For example, you can break a large trade into smaller pieces to get greater execution details. Plus, this allows you to mitigate your trade's effect on the market, as well as control overall costs.
Better accuracy and speed: You do not have to worry about missing out on an opportunity. As soon as your rules are set, the system performs the trades immediately—quicker and more accurately than manual execution.
No emotional bias: You will no longer have the challenges and battles, such as fear or greed. The algorithm follows your rules without emotions, which keeps your trading consistent and rational.
Better back-testing: For instance, you can run every idea before going live. After reviewing the historical market data, you have a greater understanding of the probable results of your strategy based on different market conditions.
Additional Read: What is Scalp Trading and How does it Work?
While algorithmic trading offers speed and automation, it also comes with several limitations that you need to consider before diving in:
Technical glitches: System failures, bugs, or connectivity issues can disrupt order execution and lead to unintended trades.
Market volatility: Algorithms may struggle during unpredictable or volatile market conditions, often triggering trades that don’t align with the original strategy.
Over-optimisation: Strategies fine-tuned using past data might not perform well in real-time markets, especially if conditions have changed.
Lack of human judgment: Algorithms lack the intuition and context that human traders can apply during complex or unexpected scenarios.
Data accuracy: Inaccurate or outdated data can result in flawed decisions and missed opportunities.
Regulatory challenges: If improperly managed, algorithmic trading can raise compliance issues, especially when trades affect market stability or breach norms.
Algorithmic trading, or algo trading, uses computer programs to execute trades at high speeds based on predefined criteria. Examples include:
Trend-Following Strategies: These algorithms identify and follow market trends, buying in an uptrend and selling in a downtrend.
Index Fund Rebalancing: Algorithms manage large-scale buy and sell orders efficiently during periodic rebalancing.
Market Making: Algorithms continuously place buy and sell orders to profit from the bid-ask spread.
High-Frequency Trading (HFT): These algorithms execute numerous trades within milliseconds to capitalize on tiny price changes.
If you are new to algorithmic trading, approach it progressively. Get comfortable with how markets operate, learn the tools, and gradually develop your strategy. Here are a few key steps to embark on your journey.
Understand market basics: You need to understand how the market works - order types, timing and risk. This gives you the ability to create and design a strategy that is fitting in real life.
Select a robust platform: You want a broker/trading platform which supports API and algorithmic configuration (preferably), and make sure it will allow easy connection to test and operate your strategy.
Design and back-test your strategy: You establish your rules and back-test them using historical data. This gives you an understanding of how your strategy behaves in different scenarios before deploying it live.
Monitoring and tweaking: You will not be able to “set and forget” your algorithm. You will want to review your results and implement changes in your strategy as markets evolve. Monitoring the effective performance of your strategy will give you an indication of whether it is still wholly accurate and operating or not.
If you're planning to use algorithmic trading, you'll need a few technical essentials in place. These elements help you automate trades, cut down delays, and keep your strategy stable. Here’s what you should have set up:
Programming skills or trading software: You should either know how to code your strategies or use platforms that let you build them visually. You can also hire a developer if needed.
Broker API access: You'll need direct access to your broker’s API to place, adjust, or cancel trades automatically.
Live data feed: Real-time data is critical for analysis and triggering trades. Delays in data can affect performance.
Consistent internet connectivity: Your system must stay connected without interruption. Even small lags can cost you trades in fast-moving markets.
Backtesting setup: Before you go live, test your algorithm with historical data to check how it performs under different market conditions.
Historical data quality: Use clean, properly aligned historical data to make your backtesting results more reliable.
Getting these right helps you build an algo system that reacts fast, works reliably, and stays in sync with market conditions.
Share this article: 
No result found
The different algorithmic trading strategies involve trend-following strategies, index fund rebalancing, and mathematical model-based strategies.
Yes, every category of investor can use this trading system for different purposes. Hedge funds can use it to take opposite positions and hedge their investments. Institutional investors use it to buy large quantities of stock without creating an impact on the price of the quantity.
Disclaimer :
The information on this website is provided on "AS IS" basis. Bajaj Broking (BFSL) does not warrant the accuracy of the information given herein, either expressly or impliedly, for any particular purpose and expressly disclaims any warranties of merchantability or suitability for any particular purpose. While BFSL strives to ensure accuracy, it does not guarantee the completeness, reliability, or timeliness of the information. Users are advised to independently verify details and stay updated with any changes. The securities are quoted as an example and not as a recommendation. Past performance is not necessarily a guide to future performance.
The information provided on this website is for general informational purposes only and is subject to change without prior notice. BFSL shall not be responsible for any consequences arising from reliance on the information provided herein and shall not be held responsible for all or any actions that may subsequently result in any loss, damage and or liability. Interest rates, fees, and charges etc., are revised from time to time, for the latest details please refer to our Pricing page.
Neither the information, nor any opinion contained in this website constitutes a solicitation or offer by BFSL or its affiliates to buy or sell any securities, futures, options or other financial instruments or provide any investment advice or service.
BFSL is acting as distributor for non-broking products/ services such as IPO, Mutual Fund, Insurance, PMS, and NPS. These are not Exchange Traded Products. For more details on risk factors, terms and conditions please read the sales brochure carefully before investing.
Investments in the securities market are subject to market risk, read all related documents carefully before investing. This content is for educational purposes only. Securities quoted are exemplary and not recommendatory.
For more disclaimer, check here : https://www.bajajbroking.in/disclaimer
Level up your stock market experience: Download the Bajaj Broking App for effortless investing and trading
Open Your Free Demat Account
Enjoy low brokerage on delivery trades
|
Please Enter Mobile Number
Open Your Free Demat Account
Enjoy low brokerage on delivery trades
|
