In the last few years, retail participation in the Indian stock market has skyrocketed. In FY24 alone, nearly 3.7 crore demat accounts were opened, bringing the national total to 15 Cr. 

What is driving this growth? As financial awareness increases, Indians have been seeking alternative sources of income, especially triggered by the economic uncertainty experienced during the COVID-19 pandemic. Additionally, trading apps are easily accessible on smartphones, and digital advancements in KYC procedures have made it easy to open accounts and explore trading platforms, especially for new traders.

Trading platforms are racing to integrate Artificial Intelligence (AI) and leverage Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) models to add various smart features on their platforms, equipping traders with tools to make informed decisions.

All these advancements raise the question, ‘Does AI guarantee better outcomes, or is it just a more sophisticated version of speculation?’ 

Let’s take a closer look at how trading platforms in India are using AI for trading stocks and options, and how you can leverage AI to enhance your trading capabilities in the Indian stock market.

Use of AI in Trading Platforms

AI is playing a big role in making trading platforms more efficient. AI Trading is based on tools that provide in-depth financial analysis of huge amounts of data, and predict price movements and market behaviour.

While financial institutions have largely used computer algorithms for trading, retail platforms have depended on software that must be manually updated.

With AI trading software now emerging, trading platforms can now use ML and DL algorithms that learn from past and real-time data and can develop their own rules and patterns. These systems rely on continuous learning, are ‘adaptive’ in nature, and improve predictive accuracy over time. 

If you are looking for an AI trading app in India, you’ll find no shortage of them today. Indian trading platforms offer a wide range of AI-powered trading tools, designed to help you trade smarter.

Here’s a look at some of the main uses of AI for trading in the Indian stock market.

1. Scanners & Screeners: Find the Right Stocks

Scanners scan various stocks using technical indicators. These scanners can be pre-built or customised as per your preferences. AI stock trading allows you to go through thousands of stocks, saving hours of manual research.

Screeners have filters that allow you to put in your criteria based on sectors and technical indicators.

Examples: 

• Fyers One launched FIA ( FYERS Intelligent Assistant), which allows you to create custom stock screeners using Price, Volume, and Open Interest data through simple prompts.
• TradeBrains, with its PortalAI feature, allows you to analyse and screen stocks.
• Shoonya has integrated an AI-powered feature (I Know First) that analyzes and predicts stock market trends.
• Streak (partnered with Zerodha) has access to 250+ scanners that run scans on live markets.

2. Financial Analysis: Research Stocks in Minutes

Many AI tools use NLP to quickly analyze data from company financial reports, brokerage research, news articles, press releases, and even social media chatter. Instead of manually reading a 40 or 50-page report, you can now get a clear summary of a stock with the best and worst points highlighted, giving you quick insights. 

AI systems that use DL can assess the sentiment, i.e., positive, negative, or neutral, towards various market events, and can help you determine when markets are overreacting. 

Examples:

• Sensibull (partnered with Zerodha) offers advanced tools to analyse live options charts, FII DII data flows, real-time stock data, and more, with its focus on AI for trading options.
• TradingView uses AI in its charting feature that allows you to identify trends and price movements without switching screens. Various trading platforms use this charting feature, including Streak, Upstox, Fyers, AngelOne, and Groww.
• Other general AI tools like ChatGPT, NotebookLM, and Claude AI are also being used to analyze financial reports and generate quick insights. Manus AI generates a concise report pack in minutes, covering all key financial highlights.

3. Strategy Builders: Build a Trading Strategy.

Most trading platforms let you build trading strategies without code. You can define your buy/sell criteria, backtest this strategy, and then execute accordingly. 

You can choose from pre-built or customized strategies, using simple prompts. Once a strategy is ready, it can be backtested and then deployed live. This feature allows you to be consistent and avoid panic sell or buy decisions. AI technology has taken this feature further by adapting and creating new rules for building strategies based on past and real-time market data.

Examples of AI trading platforms with strategy builders:

• Sensibull offers a guided strategy builder with AI-powered risk analytics and payoff visualizations, helping you see a potential outcome before making a trade.
• Streak offers access to 150+ pre-built strategies along with backtesting on past data up to 5 years.

4. Algorithmic Trading: For Advanced Trading

In algo trading, trades are executed automatically based on pre-programmed instructions. Once the defined conditions are met, for example, a stock drops below a moving average or moves above a resistance line, the system takes over and trades on your behalf. Algo trading has seen an increase in retail participation recently, with the NSE recently issuing new rules to streamline AI trading for beginners and advanced traders.

AI trading software has improved the efficiency of algorithmic trading by analysing large datasets in real-time and executing trades instantly. There is no coding knowledge required and this eliminates barriers for beginners, contributing to the increase in algorithmic trading.

Examples of AI-based algo trading:

• Tradetron, a no-code algo trading platform, uses AI to scan and identify stocks with favourable conditions.

• BigulAlgo has integrated an AI assistant, JARVIS, on its platform to analyse stocks.
• AlgoBulls uses Phoenix ‘AI’ Copilot to allow traders to build custom trading strategies with simple prompts.

5. Alerts and Anomaly Detection

AI systems send automatic alerts or signals when certain stocks meet a requirement. ML has helped platforms track unusual patterns and offer suggestions automatically. NLP bots notify you of corporate actions, regulatory changes, or major events within the market. 

Given these advancements, AI provides access to accurate data, helping you save time, improve decision-making, and potentially have better trading outcomes. However, in the world of finance, the greater the reward, the greater the risk. Hence, while using AI for trading may give you a competitive edge, it is not without its risks.

Risks and Limitations of Using AI for Trading

1. All AI models are only as good as the data they are trained on

Not all historical data will be relevant in the future. Markets don’t always repeat themselves. Examples like COVID-19 or unforeseen regulatory events can’t always be predicted or modeled correctly. While most tools use past data, it doesn’t always guarantee that those trends will continue in the future.

2. Overfitting can lead to false confidence

Many trading strategies can look perfect, especially after backtesting, but in reality, they may be over-optimized to past data. This creates the illusion of accuracy, and you need to be vigilant of these features and not ignore your instincts.

3. Lack of context and human judgment

AI tools have displayed great efficiency in analyzing numbers, trends, and technical signals. However, they often miss the ’why’ behind market-moving events. Even with AI advancements, you would need to use your judgment to cautiously interpret the sentiment behind bull or bear markets.

4. Over-reliance on AI trading

Access to scanners and high-speed analysis may lead to over-reliance and ignoring your instincts. Hence, it is wise to recognise AI as a tool and not a replacement for experience or responsible decisions.

Human Intuition in an AI-driven Environment

AI trading platforms offer real-time insights, advanced financial analysis, and execution in seconds and minutes, a task that would otherwise take hours or days. Despite these remarkable capabilities, the unique value of human judgment cannot be replaced, especially in the context of broader economic narratives, qualitative factors, and unanticipated events. The most effective approach is to use AI tools for the ‘number and data crunching’ and monitoring market movements, but to retain your valuable oversight and contextual understanding. 

The Future of AI Trading in the Indian Stock Market

AI for trading will continue to expand further, lowering the barriers for Indians to participate in the Indian stock market. AI stock trading will not only reshape the trading industry in India but also impact wealth creation. Regulatory frameworks will continue to evolve to prevent manipulation, ensure market integrity, and protect traders. 

Going forward, it is important to recognise that AI’s role is to help you understand the market better rather than to ‘beat the market’. Ultimately, AI tools cannot understand your financial goals or interpret emotions, or take responsibility for your decisions. Hence, while these tools give you an edge, combine them with your insights to create the best balance while trading.

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