Learn 🧠 All Concepts (20) 🤖 What is an LLM? 📚 RAG Explained ⚡ AI Agents 💻 Run AI Locally 🇮🇳 AI in India 📖 Learn Tracks 🔧 DevOps Track ⚙️ AI Ops Track 🗺️ AI Engineer Roadmap
Tools 🔧 AI Tools Directory 🔓 Open Source AI ⭐ Top GitHub Repos ✦ Claude Skill Repos 🚀 Ready-to-Deploy Projects
Build 🏗️ Build Hub 🎯 Master Prompts 🧩 RAG Agents 🚀 App Megaprompts
Workflows ⚡ All Workflows (22) 🎥 Text to Video 🎞️ Image to Video 🔊 Text to Speech ♻️ Automation
Resources 🧪 Colab Notebooks ⚙️ n8n Workflows 📈 Algo Trading 💰 Passive Income
🗂️ Browse All Topics About AItheGuru
← Resources

NSE/BSE algorithmic
trading strategies

Full Python source code with backtesting and live Zerodha integration. Test thoroughly before using real capital.

⚠️ Educational purposes only. This is not financial advice. Algorithmic trading involves substantial risk of loss. Always backtest with 2+ years of data before live trading. SEBI requires registration for client-side automated trading.

⚡ NSE Momentum Strategy — Backtest + Live trading via Zerodha

Backtest + live trading via Zerodha (Kite). Strategy: Momentum + Mean Reversion.

BrokerZerodha (Kite)
Capital₹50,000+
RiskMedium
StrategyMomentum + Mean Reversion
# Complete NSE momentum strategy with backtesting and live trading # Broker: Zerodha via kiteconnect # Strategy: Buy top 5 momentum stocks from Nifty 50 every week import yfinance as yf import pandas as pd import numpy as np from kiteconnect import KiteConnect # pip install kiteconnect from datetime import datetime, timedelta import logging import time