Algo Trading - What Is Algorithmic Trading In Stock Market?

Trading involves buying and selling financial instruments such as stocks, equities, etc., based on the current market situation to generate profits. A trader may have to deal with a vast number of transactions daily, which may be difficult for him to track and perform efficiently.Here lies the need for Algo Trading to perform trade transactions based on an algorithm that helps make trade decisions. Though it is already in use for a long time, many investors who are new to trading may not be aware of what is Algo Trading .

Algo trading is an automated trading system that applies a set of rules or algorithm developed by experts while making trade transactions. The algorithm is designed as per the specifications of quantity, timing, pricing, and other guiding factors significant while making trade decisions. A large number of transactions can be carried out quickly in an error-free manner with the deployment of these algorithms.Earlier, the algorithms were simple decision-making programs. However, eventually, with the application of AI concepts, it has emerged as complex and intelligent programs that can speculate and forecast to generate better profits for the traders.

Much of the Algo trading done today is High-Frequency Trading (HFT) that takes advantage of buying and selling a large number of stocks rapidly across different markets based on multiple parameters used in the algorithm.Let’s look at some of the major benefits of Algo Trading:

• Quick and Error-Free Transactions: With Algo Trading, the decision-making and execution of transactions can be done within seconds, which is not possible manually. Also, due to no human interventions, there are no or lesser chances of errors in analysing numbers and other factors, thus providing greater accuracy.
• Lower Transaction Cost: Since multiple transactions or trading can be done speedily by the traders simultaneously, the transaction cost is also reduced. Also, with a lesser requirement of manual traders, the overall cost of trading is lowered.
• No Human Interference: Apart from the negation of the possibility of human errors during trading, the chance of decision making based on the trader's emotions or psychology is also minimized.
• Implementation of Multiple Trades/Strategies: With Algo trading, multiple trades can be carried out by implementing multiple strategies, scanning a large number of stock markets and securities at the same time. It is not possible to manually analyse multiple factors quickly and with similar efficiency.
• Backward Testing Possible: Before deploying Algo trading, the trading strategies can be checked for effectiveness and applicability using historical and real-time data. Hence the algorithm can be rectified or updated as per the test results before it is put to use.

Algo trading uses different strategies to identify profit-making opportunities while making trade transactions. Let’s look at some of the popularly used strategies:

• Trend-Following: This is the most common strategy used that simply captures price movements, moving averages, and other market indicators to follow trends and trade accordingly. These algorithms use a simple and straightforward approach and do not include any predictive analysis or forecasting.
• Arbitrage Opportunity: An arbitrage strategy focuses on opportunities wherein the same stock or share is listed at different prices in different markets to capture the price difference as profit margin. An algorithm that uses this strategy identifies arbitrage opportunities and carries out buying and selling of stocks accordingly to generate profits for the traders.
• Mean Reversion Strategy: Mean reversion strategy focuses on the fact that the price of an asset goes up and down only temporarily and will reach its average value from time to time. Under this strategy, whenever the price goes out of a pre-decided range for an asset, the trade is placed as per the set instructions.
• Strategies Based on Mathematical Models It uses proven mathematical models for making trading decisions based on a combination of different options and related security. For example, a delta-neutral trading strategy is one such example that uses multiple positions with balancing positive and negative delta values to bring the overall delta of the asset to zero.
• Index Fund Rebalancing Index funds have defined periods to rebalance their holdings to match their benchmark indices. This is an opportunity for Algo traderswho focus on taking advantage of expected trades offering 20-80 basis points profits as per the number of stocks in the fund before the index fund rebalancing happens. An algorithm can execute trading as per this strategy promptly and at the best price.
• Implementation Shortfall This strategy works on trading-off the real-time market to reduce the execution cost of an order. It benefits from the opportunity cost of late execution. The target participation rate will be increased when the asset price moves favourably, whereas it will be decreased if the price movement is adverse.

Though Algo trading has many benefits as discussed above, it has its risks and challenges too. There may be network connectivity issues, system failures, or faulty algorithms due to which it may fail to deliver the desired results. Algo trading is a powerful tool that can efficiently handle bulk transactions, but it needs to be explored further by investors to reap its true benefits.

The information contained herein is generic in nature and is meant for educational purposes only. Nothing here is to be construed as an investment or financial or taxation advice nor to be considered as an invitation or solicitation or advertisement for any financial product. Readers are advised to exercise discretion and should seek independent professional advice prior to making any investment decision in relation to any financial product. Aditya Birla Capital Group is not liable for any decision arising out of the use of this information.