How to Trade Using AI?

The stock market is evolving rapidly. What once required hours of manual analysis, technical charting, and emotional decision-making is now being streamlined by Artificial Intelligence (AI). Whether you’re a beginner trader from Kerala or a professional investor from Mumbai, AI is changing how trades are identified, executed, and optimised.

But how exactly do you trade using AI?

In this comprehensive guide, we’ll break down everything you need to know, from how AI-based trading works, to the best AI trading tools available in India and how you can use them to enhance your profits while managing risk effectively.

By the end, you’ll understand how to integrate AI into your trading strategy, and how platforms like Entri’s Stock Market Courses can help you build the right foundation to master this futuristic skill.

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What Is AI Trading?

AI Trading, or Algorithmic Trading with Artificial Intelligence, refers to using machine learning models, predictive analytics, and automation tools to make trading decisions.

In simpler terms, it’s when a computer system analyses stock data, such as price movement, volume, and sentiment, and executes trades based on mathematical models, without human emotions influencing decisions.

How AI Trading Works

1. Data Collection:
   AI systems collect massive datasets, from stock prices, global news, financial reports, and even social media sentiment.
2. Pattern Recognition:
   Machine learning algorithms identify patterns and correlations in market movements.
3. Prediction & Decision:
   Based on historical trends and predictive modelling, the AI system predicts price directions.
4. Execution:
   Once conditions are met, the algorithm executes trades automatically.
5. Continuous Learning:
   AI systems adapt by learning from new data, improving their accuracy over time.

This makes AI trading faster, smarter, and more data-driven than traditional trading.

Why AI Trading Is Becoming Popular in India

India’s retail participation in stock markets has exploded in the last five years,  thanks to affordable internet, smartphone apps, and financial literacy platforms like Entri.

With more than 12 crore active Demat accounts (as per SEBI 2025 data), investors are now seeking smart, automated, and efficient trading tools.

Here’s why AI is trending in Indian stock markets:

• 📈 Real-Time Insights: AI provides instant analysis of stocks and sectors.
• 💹 Emotion-Free Decisions: Avoid panic selling or greed-based buying.
• 🧠 Smarter Predictions: Machine learning algorithms forecast price movements better than manual guessing.
• ⚙️ Automation: AI bots execute trades without human intervention.
• 🧩 Accessibility: Many Indian platforms now integrate AI features into trading dashboards.

Types of AI Trading Strategies

Different traders use AI differently. Here are some of the most common AI-based trading strategies:

1. Quantitative Trading

Uses mathematical models and statistics to analyse market data and identify profitable opportunities.
Example: AI identifying when NIFTY50 is overbought based on RSI and historical data.

2. Sentiment Analysis Trading

AI tools scan social media, news portals, and financial headlines to gauge market sentiment.
Example: A sudden rise in positive sentiment around Reliance Industries may signal a potential uptrend.

3. High-Frequency Trading (HFT)

AI executes thousands of trades per second to profit from minute price differences, ideal for advanced traders or institutions.

4. Predictive Modelling

Machine learning algorithms predict price movement based on historical data and trends.
Example: Predicting TCS stock’s movement based on quarterly earnings performance.

5. Portfolio Optimisation

AI helps investors manage risk and return by optimising portfolio weightage and diversification.

Best AI Trading Tools and Platforms

Here’s a curated list of some of the top AI-powered trading tools you can explore in India:

1. Zerodha Streak

• Integrated with Zerodha Kite.
• Let’s users create and backtest AI-based trading strategies without coding.
• Provides visual dashboards and real-time alerts.

2. Tradetron

• Cloud-based algorithmic trading platform.
• Enables traders to build, backtest, and deploy AI strategies across brokers like Angel One, Alice Blue, and Zerodha.

3. AlgoBulls

• Offers AI-driven strategy recommendations.
• Supports automated trading in equities, options, and futures.
• Features predictive analytics and performance tracking.

4. Upstox Pro AI Assistant

• AI assistant that provides real-time insights and strategy suggestions.
• Especially helpful for beginners exploring Indian equities.

5. Kuants

• Machine-learning-powered trading strategies for NSE and BSE.
• Offers strategy marketplace for retail traders.

6. StockEdge Premium

• AI-backed stock analysis app focusing on fundamentals, trends, and sentiment.
• Great for long-term investors.

7. MetaTrader 5 (MT5) with AI Plugins

• Global trading platform with Indian broker integrations.
• Supports custom AI bots, backtesting, and automated signal trading.

How to Start Trading with AI: Step-by-Step Guide

This is a repeatable process you can follow end-to-end.

1. Learn the basics first

Know market structure (NSE/BSE, order types), basic technical/fundamental analysis and simple risk rules. Enroll in a reliable course (see Entri section below).

2. Choose a platform

Pick a platform that matches your skill level:

• Absolute beginner: tools with no-code strategy builders (Streak, Tradetron).

• Intermediate: platforms with strategy marketplaces and some scripting.

• Advanced: custom ML models using Python + broker APIs.

3. Define a clear strategy hypothesis

Write it down: what market regime it targets, entry rules, exit rules, position sizing, max daily risk.

Example: “Buy mid-cap stocks when 14-day RSI < 30 AND 50-day MA trending upward; exit when RSI > 55 or stop-loss 3%.”

4. Gather and clean data

Use reliable historical price data plus any alternative data (news, volume, options flow). Clean for missing bars, corporate actions and time-zones.

5. Backtest thoroughly

Test your strategy across different years, bulls and bears. Use walk-forward testing to assess robustness (see next section).

6. Start in paper/demo mode

Run the strategy in a simulated/demo account for a few months or a minimum 50–100 trades, whichever comes first.

7. Go live with a small capital

Begin with a small fraction of planned capital (1–3%). Monitor slippage, latency, and real-time performance.

8. Monitor & iterate

Review performance weekly, recalibrate, add guardrails (circuit breaker), and retrain models only when sufficient new data exists.

Benefits of AI in Trading

Backtesting, walk-forward testing and performance sanity checks

Robustness beats curve-fitted complexity. Backtesting is the foundation on which any AI or algo trading approach is built – but only if done properly.

Backtesting basics

• Make sure you’re using pristine, adjusted price data that accounts for corporate actions.
• Don’t forget to include realistic costs: brokerage fees, slippage, and taxes – these can add up quickly.
• Its also important to test your strategy across different market conditions – bull, bear, and sideways markets.

Walk-forward testing

Split your historical data into chunks where you can use the first part to train (or “learn”) and the second part to test (or confirm that your strategy still performs well on unseen data). This can really help prevent overfitting.

Key metrics to track

• Profit and loss, and the profit factor
• Win/loss ratio and average size of wins and losses
• Maximum drawdown and how long it takes to recover from it
• Sharpe ratio and Sortino ratio – these give you an idea of your strategy’s risk-adjusted performance
• Trade frequency and how sensitive your strategy is to slippage – this can make a big difference

If your strategy only performs well in very narrow conditions, then either simplify it or avoid using it in live markets.

Risk management and position sizing – some practical rules to live by

You can have the best AI in the world, but without a solid risk plan, you’re pretty much guaranteed to blow up your account. Here are some hard and fast rules to follow:

• Risk per trade: Keep your trades under 1% of your total capital – that’s a pretty conservative approach, or if you want to take a bit more risk, aim for 1 or 2% of your capital
• Max daily loss: Set a stop trading for the day if you lose 3-5% of your capital – that gives you some breathing space to recover
• Diversification: Don’t put more than 5-8% of your portfolio in a single stock at any given time – especially with short-term strategies
• Capital allocation: Keep a portion of your capital (20-40%) free to rebalance your portfolio or make up for market gaps
• Human override: Always have a pause button – a way to shut off automation if something goes wrong

Practical example: if you’re trading with ₹200,000 and you’re okay with a 1% risk, then your max per-trade loss is ₹2,000. If your stop-loss is 2%, then your trade size should be ₹100,000 notional – because 2% of ₹100,000 = ₹2,000.

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Common pitfalls and how to avoid them

1. Overfitting: Tuning your strategy to past market conditions, only for it to fail in new markets. To avoid this, simplify your strategy and use walk-forward testing to see how it holds up
2. Blind trust: Letting your bot just run wild without checking on it. I’d say schedule some daily checks to make sure everything’s okay
3. Undervaluing execution costs: Don’t forget that brokerage fees and slippage can really eat into your profits – factor them in when backtesting
4. Poor data quality: If your data is rubbish, your models will be rubbish too. Use a reputable data vendor to get some good-quality data
5. Ignoring extreme events: If your bot is only trained on normal market conditions, it’ll struggle when things get really crazy – like during a black swan event. Either disable automation during those times or make sure your bot is equipped to handle them
6. Overleveraging: Don’t get too carried away with margin – it can amplify both your gains and your losses. Use it with caution

Regulatory, ethical, and operational considerations 

• SEBI & broker rules: If you’re using algorithmic trading or direct market access, you’ll need to make sure you’re following the rules laid out by SEBI and your broker
• Taxes: If you’re trading, you’ll need to figure out what taxes you owe – profits from intraday trading, short-term capital gains and long-term capital gains are all taxed differently. Keep good records and if you’re unsure, get a tax pro to help out
• Data privacy & ethics: If you’re using alternative data, make sure you’re respecting people’s data privacy and copyright rules
• Operational reliability: Don’t just assume everything will work fine – make sure you’ve got a stable internet connection, some redundant checks in place, and a plan in case your broker goes down

The Future of AI in Indian Stock Trading

By 2025 and beyond, AI trading in India is expected to grow exponentially.

According to NASSCOM, India’s fintech and trading automation sector is projected to reach $50 billion by 2030, driven by digital literacy and AI integration.

We can expect:

• AI-integrated brokers offering predictive trading signals.
  
• Voice-enabled AI trading assistants.
  
• AI-based risk management dashboards for investors.
  
• Advanced robo-advisors providing personalised investment portfolios.
  

For traders who upskill now, this is a golden opportunity to be future-ready.

How Entri’s Stock Market Courses help you trade

Entri’s Stock Market Courses are designed for Indian learners who want practical, market-ready skills. Here’s how they align with AI trading needs:

• Foundations first: Courses cover market basics, order types and risk management so you won’t misuse AI tools.
• Technical analysis modules: Learn indicators, chart patterns, and timeframes, essential complements to AI signals.
• Algorithmic / automation overview: Practical lessons on how platforms like Streak, Tradetro,n and broker APIs work, no heavy coding required.
• Backtesting & performance analysis: Step-by-step training on how to test strategies and interpret metrics.
• Live demonstrations and mentorship: Real-time sessions showing how to set up a strategy, run a demo, and scale safely.
• India-centric content: Regulatory, tax and broker references relevant to Indian traders and time zones.

If you want to trade using AI, the best route is: learn the markets → learn the tools → paper test → scale. Entri supports each stage with practical lessons and mentorship.

Key Takeaways

• AI trading combines machine learning, automation, and analytics to make trading smarter.
  
• Start simple. Use no-code platforms and conservative strategies first. Tools like Zerodha Streak, Tradetron, and AlgoBulls lead the AI trading revolution in India.
• Always backtest your strategies before going live.
• Manage risk first, returns follow. Keep per-trade risk small and have circuit breakers. Monitor live performance daily.
• AI trading works best when paired with human knowledge and continuous learning.
  

Conclusion

AI is no longer a distant future; it’s today’s trading reality. From analysing charts to executing trades in seconds, Artificial Intelligence is redefining how Indian traders interact with the stock market.

Whether you’re a beginner or an active investor, integrating AI into your trading routine can open new doors to consistency and smarter decision-making.

So, start your journey towards becoming an AI-powered trader, and let Entri’s Stock Market Course guide you every step of the way.