How are you all taking care of static IP requirement for Auto Algotrading in India? VPS ? ISP providing ? What is if ISP is not providing ??
If you use Amibroker in India and need a solid real-time data bridge, definitely check out AmiBridge.
Low latency, stable feed handling, and works really well for serious intraday trading/algo setups. One of those tools that quietly makes the whole AmiBroker experience much smoother.
how to get historical 5m or 15m NSE Nifty futures for say the past 12 - 24 months... free and open source only. Any libraries? any dump repositories? Kaggle has only Index.
10 free GitHub repos that anyone with $100 and a laptop can use to trade like a hedge fund in 2026.
These are the same tools 300+ hedge funds quietly run on. Bookmark this. The list will save you years.
A free Bloomberg Terminal. Stocks, options, futures, crypto, forex, all in one platform. The Bloomberg Terminal costs $25,000 a year. This costs $0.
Repo → https://github.com/OpenBB-finance/OpenBB
The algorithmic trading engine 300+ real hedge funds use right now. Backtest on 25 years of data, deploy live to Interactive Brokers or Alpaca.
Repo → https://github.com/QuantConnect/Lean
Microsoft's full quant investment platform. The most serious open-source quant infrastructure ever shipped.
Repo → https://github.com/microsoft/qlib
The Python backtesting framework every quant learns first. Used in graduate finance programs around the world.
Repo → https://github.com/mementum/backtrader
A multi-agent LLM trading framework from UCLA and MIT. Autonomous AI agents acting as analyst, technician, and risk manager.
Repo → https://github.com/TauricResearch/TradingAgents
The portfolio optimization library quants use to allocate capital. Mean-variance, Black-Litterman, CVaR, all in one place.
Repo → https://github.com/dcajasn/Riskfolio-Lib
The free market data API every Python finance course starts with. Real-time and historical data on 100,000+ tickers.
Repo → https://github.com/ranaroussi/yfinance
150+ financial ratios, indicators, and valuation models in one library.
Repo → https://github.com/JerBouma/FinanceToolkit
The fastest backtesting engine in Python. Test thousands of strategies in seconds.
Repo → https://github.com/polakowo/vectorbt
The charting library powering real fintech apps in production. The reason your trading dashboard looks professional.
Repo → https://github.com/tradingview/lightweight-charts
Here's the wildest part:
A Bloomberg Terminal costs $25,000 a year. A junior hedge fund analyst costs $250,000. Goldman Sachs research costs millions.
These 10 repos give a kid with $100 and a laptop access to most of what Wall Street pays for.
A trading desk in 2010 cost $50,000 to set up. In 2026, the entire stack is free.
The barrier between retail and Wall Street has never been lower.
Save this before you forget.
100% free. 100% open source.
This paper unlocks every algorithm used by hedge funds.
151 trading strategies.
Get it here (361 page PDF):
Tired of CSV imports, delayed feeds, and patchwork solutions?
This changes everything.
🔌 Direct integration with Zerodha Kite, Groww API & more
⚡ True real-time data for ALL broker symbols
⏱️ Lightning-fast 1-second refresh rate
📊 Seamless multi-timeframe backfill (1m, 5m, 60m, Daily)
📈 Full market coverage — NSE, BSE, F&O, Currency & Commodities
Built specifically for Indian markets, not retrofitted.
No hacks. No manual updates. No artificial limits.
Just: Install → Login → Add symbols → Trade.
💰 Plans starting at just ₹499/month
🔗 Fully integrated with Zerodha & Groww
➕ More brokers coming soon
🎥 Watch it in action and see the difference yourself
🌐 Download now: https://amibridge.com
For traders who want institution-grade, real-time data inside AmiBroker — without the friction.
#AmiBroker #AlgoTradingIndia #ZerodhaAPI #Groww #IndianStockMarket #OptionsTradingIndia #IntradayTrading #QuantTrading #TradingAutomation #StockMarketIndia #FuturesAndOptions #AlgoTrader #TradingTools #NSEIndia #BSEIndia #Amibridge
Hey everyone,
Sharing a quick view on today’s market—would love to hear how others are reading this.
Market snapshot:
What stood out today:
Key drivers:
Technical view (short-term):
My take:
What I’m watching:
Curious to know: