How is AI Helping Retail Investors?

Artificial intelligence, or AI, is the latest buzzword. From boardroom discussions to everyday life, AI has made inroads faster than we would have imagined. Even stock market participants, including retail investors, have embraced AI for decision-making, risk management, and more.

AI for stock trading has gained momentum of late. As much as 60% of trading in India now happens via algo. Read on to learn how AI is impacting retail investors' access to the stock market and revolutionising markets.

What is AI in the Stock Market?

AI in the stock market is when computer algorithms help investors make sense of market information. Note that every day, the stock market throws up prices, news updates, company results, and sudden reactions to global events. For most investors, keeping up with it all is not easy. This is where AI steps in. It analyses large amounts of data and identifies patterns. It then presents them in an easy-to-understand manner.

It is a very fast assistant that does not get tired. It can scan past price movements, compare them with current conditions, and identify trends that may not be obvious at first glance. However, it does not mean it can predict the future. It helps reduce guesswork.

How AI Works in Stock Trading?

The working of AI in stock trading involves several processes. These include:

Machine Learning Algorithms for Predicting Stock Prices

Machine learning is a system that learns by example. Imagine teaching a child to recognise patterns. You show many such as circle, square, rectangle, etc. Over time, the child recognises these patterns and uses them as needed. Machine learning works similarly.

The system is fed years of stock prices, trading volumes, and market movements. It studies what happened before a rise. It notes what usually came before a fall. Once trained, it tries to spot similar situations in real time.

Natural Language Processing (NLP) for Analysing News and Sentiment

Every day, there is abundant news. Headlines, opinions, tweets, and a lot more. For a retail investor, it may not be possible to make sense of everything that comes in. This is where natural language processing, or NLP, can help. NLP is simply a way for computers to read and understand written words.

Think about how you read the news. You may not read every word. You scan. However, you pause at strong phrases. You sense whether the story feels positive, worrying, or unsure. NLP tries to do something similar, only at a much larger scale.

Pattern Recognition in Historical Data

An essential aspect of AI for trading socks is pattern recognition in historical data, which involves spotting market behaviours over several years. When you look at historical data over the years, stories begin to form.

Certain stocks tend to rise after long, quiet phases. Some fall sharply after sudden spikes. AI helps identify patterns that can help investors better prepare their trading and investing strategies.

Automation of Trading Strategies

AI is helping investors automate their trading strategies. When a particular condition is met, an action happens. The system does exactly what it is told to do. For instance, if a stock price hits a certain high, it is sold.

On the other hand, if it falls to a certain level, the system can sell it and protect investors from further losses if prices slide further. Automated strategies work in the background even when the investor is occupied with other tasks.

Types of AI Trading Strategies

Here are some of the common types of AI trading strategies that you can explore:

Pattern-Based Trading

Markets repeat themselves more often than we think. Prices can move up, down, and then pause. Pattern-based strategies focus on spotting them. The system analyses past price movements and compares them with current market conditions. If something looks familiar, it acts.

High-Speed Trading

This trading strategy is all about speed. They act in fractions of a second. They look for tiny price gaps and try to benefit from them before others even notice. High-speed trading is generally observed in intraday trading, where buying and selling happen on the same day.

Risk-Controlled Trading

Not every trading strategy is about making more money. Some are about losing less. Risk-controlled strategies focus on limits. How much to invest? When to step out? How much loss is acceptable? If prices move sharply in the wrong direction, the system reacts immediately.

Benefits of Using AI in Stock Trading

Using AI for trading stocks can offer several advantages. Some of these are:

Makes Decisions Less Overwhelming

Too many choices can be confusing. Which stock to invest in? When to buy? When to sell? AI narrows things down. It highlights a few options based on what you are looking for. That helps reduce stress.

Helps Spot Patterns That You May Miss

Markets move fast. Prices change every second, and it is easy to miss small shifts. It can be difficult for you to observe and list every pattern. However, things are different with AI. It can track markets all day without getting tired and help you notice trends early.

Saves Research Time

Reading reports takes time. Tracking news takes time. Comparing numbers takes even more. AI speeds all of these. It scans data quickly and presents the information you need to make informed trading decisions.

Risks and Limitations of Using AI for Trading

While AI in stock trading offers benefits, it also has limitations. These include:

Can Lead to Overconfidence

While AI can offer suggestions based on past trends, it can sometimes feel too reliable. This blind trust can be dangerous. If a recommendation goes wrong, there is no shared responsibility. So, as an investor, you should do due diligence before acting.

One Size Does Not Fit All

Most AI tools in stock trading follow a standard approach. They group users into broad categories. However, things are different in reality. Your income may change. Your expenses may rise suddenly. Your goals may shift. AI does not always catch these changes in time. It may still suggest actions that no longer suit your situation. What works for one person may not work for another.

Can Lead to Too Much Trading Too Often

AI reacts fast, sometimes extremely fast. This can lead to frequent buying and selling. However, in the process, it may quietly increase the costs and taxes you might need to pay. In other words, it may increase your tax liability.

Future of AI in Stock Trading

Going forward, the future of AI in stock trading looks bright. The algorithmic trading market in India is expected to reach US$ 2312.3 million in revenue by 2030. It is anticipated to grow at a CAGR of 14.3% from 2025 to 2030.

This growth is a testament to rising investment in AI, machine learning, and automated systems across brokerages and trading firms. Notably, 84% of Indian stockbrokers planned to increase their IT budgets in 2024-25 with a focus on AI, machine learning, and other technologies.

Sources:

Moneycontrol
Grandviewresearch
Economic Times