In this video, I’m giving you a complete demo of my new Trading Strategy Backtester — a simple yet powerful Python-based tool to backtest stock market strategies using EMA crossover logic, TALib indicators, and Pandas data engine.

💡 Whether you’re a quant developer, algo trader, or Python enthusiast, this project will help you:
✅ Backtest your custom trading strategies on historical data
✅ Load any dataset (Open, High, Low, Close, Volume)
✅ Use Pandas or TA-Lib for indicator calculations
✅ Instantly view performance metrics (returns, drawdown, profit factor, win-rate)
✅ Download trade logs in CSV format for verification
✅ Extend easily — just create a new class and define buy/sell conditions

📈 Tech Stack: Python, Pandas, NumPy, TA-Lib, Flask (Web UI)

🔥 In this video you’ll learn:
0️⃣ How to load custom OHLC data
1️⃣ Add & select your strategy (EMA crossover example)
2️⃣ Adjust parameters (fast/slow EMA, initial balance, trading mode)
3️⃣ Run instant backtest with complete metrics
4️⃣ Validate signals directly on TradingView charts

💡 Try it yourself or get a custom version built for your strategies.
👉 Reach out: hello@thinkstak.com

🔗 Connect with me:
💼 LinkedIn → https://www.linkedin.com/in/codewithpulkit/
🌐 Website → https://www.thinkstak.com/
💻 GitHub → https://github.com/PulkitChadha125
▶️ YouTube → / @codewithpulkit

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