Algorithmic Trading Strategies 2024: Evolution and What Lies Ahead
Overview
Algorithmic trading or Algo Trading Options is a new-age trading practice that out beats the human endeavour to generate profits. It is also called Automated Trading or Black-box Trading.
Algorithmic trading, as the name suggests, is a computer-generated program that follows a fixed set of instructions known as an algorithm to bid a trade. The algorithm is based on timing, quantity, and price.
Algorithmic Trading: Evolution and Future Prospects
Algorithmic trading, introduced in India on April 3, 2008, enables automated trading through pre-designed algorithms. Initially offered to institutional investors by SEBI via the Direct Market Access (DMA) facility, it has since gained popularity among various market participants. Algo trading reduces costs, improves execution, and generates better returns with minimal manual intervention. In February 2009, Foreign Institutional Investors (FIIs) began using DMA, further expanding the market. Today, many traders use automated software and APIs to execute strategies, eliminating emotional biases. With AI integration, algorithms learn, adapt, and optimize trading decisions. The global algo trading market is set to grow significantly by 2026.
Top Five Algo Trading Strategies of 2024
Every trader identifies effective algo trading strategies with arbitrage opportunities to earn more profits and reduce cost-plus pricing. Below are the best five types of algorithmic trading strategies for Indian markets which you can follow:
Trends and Momentum Following Strategy
This is one of the most common and algo strategy for intraday trading. Traders execute the trades simply by following the momentum and real-time trends of the Indian financial markets.
When making a decision to buy or sell stocks, traders consider factors such as price changes and moving averages. These processes automate and adhere to specific economic indicators. Comparing the price based on historical and current data makes the trading decision.
Thus, no complex process, simple and straight trend following. To simplify it, here is an example: You can set an automated algorithm to notify the system to buy the stocks if the 30-day average goes above the 120-day moving average. Likewise, the system is set to sell the stocks of the 30 days average that falls below the 120 days moving average. Simple.
Arbitrage Trading Strategy
Interested in trading dual-listed stocks and earning profits? Yes, then go for an arbitrage trading strategy. In this option algo trading strategy, you set an algorithm to compare prices over the different stock exchanges and execute the trade by buying at a low price from a market and selling at a high price in a different market. The arbitrary strategy does it super-fast without any error. A human can never match that speed and accuracy.
For example, the share of TCS Limited is listed on both NSE and BSE. The algorithm determines the stock price difference and automatically buys at a lower price and sells at a higher price. After the execution, the trader receives arbitrage profits. This is one of the best options for buying algo strategy.
Mean Reversion Strategy
In trading, price fluctuations are common. The mean reversion strategy works on the concept of Root Mean Square Error metric that high or low prices of a share are a temporary phenomenon and they will bounce back to their mean or average value. In the mean reversion strategy, the algorithm is set to identify and define the mean price range and execute the trade when the share breaks in and out of its defined price range.
This is a good algo trading strategy to safeguard from extreme price swings. For example: when the 30-day moving average is lower than the 120-day moving average, the simple algo indicator is set to assume that the average price will come back to the 120-day moving average, thus the algorithm is signalled to buy the shares.
Weighted Average Price Strategy
By far one of the best algorithmic trading strategies. It is either based on sales volume or time. Small chunks of large volume holding are released either based on historical volume profiles of the asset or set the time between start and end time.
The aim is to protect from the impact of the volatile market by closing the deal as near as possible to the volume-weighted average price or time-weighted average price. The system and algo together execute the trade successfully without any error that a manual process lacks.
Statistical Arbitrage Strategy
This is a short-term profitable algorithmic trading strategy that indicates price inefficiency and misquoting of similar shares. However, this price change does not last long and corrects itself. But it is difficult for humans to track these minute changes manually. Here the statistical arbitrage strategy comes in handy. The algorithm, which constitutes a complex mathematical trading strategies model, tracks changes and closes the deal before a correction occurs.
For example, if the share of one financial service company goes down, the price of another financial service company will automatically fall but will revive back soon. The algorithm takes advantage of this market inefficiency and quickly buys shares at a low price and sells them when the price is corrected. Thus, the trader earns a profit.
Conclusion
AI-powered algorithms and automated trading platforms can help you trade responsibly and grow your wealth. Manual trading methods can't match the speed, accuracy, and results of algorithmic trading, which has a promising future in India and globally.
Disclaimer: This blog is dedicated exclusively for educational purposes. Please note that the securities and investments mentioned here are provided for informative purposes only and should not be construed as recommendations. Kindly ensure thorough research prior to making any investment decisions. Participation in the securities market carries inherent risks, and it's important to carefully review all associated documents before committing to investments. Please be aware that the attainment of investment objectives is not guaranteed. It's important to note that the past performance of securities and instruments does not reliably predict future performance.
