How to Backtest Any Trading Strategy for NSE Stocks (Step-by-Step Guide)
How to Backtest Any Trading Strategy for NSE Stocks (Step-by-Step Guide)
Before risking your money on any trading strategy, ask this:
Thank you for reading this post, don't forget to subscribe!“Has this strategy worked in the past?”
That’s where backtesting comes in.
Backtesting helps you validate your trading setup by applying it to historical data—so you can see how it would’ve performed on NSE stocks or indices like Nifty & Bank Nifty.
Whether you’re using RSI, MACD, moving averages, or a custom price action system, this step-by-step guide will show you how to backtest like a pro.
What Is Backtesting?
Backtesting is the process of applying a trading strategy to historical data to see how it would have performed.
It helps answer questions like:
- Would this strategy be profitable?
- What’s the win rate and risk-reward?
- When does it work best—and when does it fail?
Tools You Need
✅ Charting Platform
- TradingView (Free and paid plans)
- Zerodha Kite (limited historical view)
- Investing.com (basic tools)
✅ Spreadsheet Software
- Google Sheets or Excel for recording trades and results
✅ (Optional) Python with NSEpy / Backtrader
For advanced, automated backtesting
Step-by-Step Guide to Manual Backtesting (Using TradingView)
🔹 Step 1: Define Your Trading Strategy
Be crystal clear on the setup.
Example Strategy:
- Buy when RSI < 30 and MACD crossover happens
- Sell when RSI > 60
- Timeframe: Daily
- Stock: Infosys
🔹 Step 2: Pick the Stock and Timeframe
Choose liquid stocks like:
📌 Nifty 50: HDFC Bank, Reliance, Infosys
📌 F&O stocks: Tata Motors, ICICI Bank
Use Daily or 15-min timeframe depending on your strategy.
🔹 Step 3: Scroll Back on the Chart
On TradingView:
🔙 Press “←” or use your mouse to go back in time
⚠️ Hide future candles to avoid bias (don’t cheat by looking ahead)
🔹 Step 4: Mark Every Entry and Exit
Apply your rules and note:
- Entry date, price
- Exit date, price
- Stop loss, target hit?
- Profit or loss
Do this over at least 20–50 trades.
🔹 Step 5: Record and Analyze in a Spreadsheet
Then calculate:
✅ Win rate
✅ Average gain/loss
✅ Risk-reward ratio
✅ Max drawdown
Optional: Using Python for Automated Backtesting
If you’re coding-savvy, use:
- NSEpy for downloading stock data
- Pandas for logic & processing
- Backtrader / QuantConnect for full simulation
Example:
Backtest a 20-50 EMA crossover strategy across top 10 Nifty stocks over the past 5 years.
Example: Backtesting RSI + MACD on Infosys
- RSI < 30, MACD bullish crossover
- Backtested from 2020–2024 (Daily chart)
- Win Rate: 62%
- Avg RR: 1.8:1
- Observed: Best results in trending markets, failed in sideways zones
⚠️ Common Mistakes in Backtesting
❌ Looking at future candles (hindsight bias)
❌ Not factoring in slippage & brokerage
❌ Overfitting strategy to specific timeframe
❌ Ignoring market phases (trending vs sideways)
Pro Tips
✅ Backtest over multiple stocks & years
✅ Use fixed position size for consistency
✅ Segment trades into bullish, bearish, and flat markets
✅ After backtesting, move to paper trading before going live
Conclusion
Backtesting turns guesswork into data-backed conviction.
Before putting real money into any setup, run it through the past and find out:
- Is it profitable?
- Is it reliable?
- Does it fit your psychology?
“Trade the strategy you’ve tested—not the one that just looks good on a YouTube chart.”
Related Blogs:
Key Financial Ratios Explained Simply (ROE, ROCE, D/E & More)
Gap Up & Gap Down: How to Trade Market Gaps on NSE with Confidence
How to Use Option Chain Data for Predicting Nifty & Bank Nifty Moves
Disclaimer: This blog post is intended for informational purposes only and should not be considered financial advice. The financial data presented is subject to change over time, and the securities mentioned are examples only and do not constitute investment recommendations. Always conduct thorough research and consult with a qualified financial advisor before making any investment decisions.