algorithmic trading
Part 3: a six-stock portfolio and two strategies in one Nautilus Trader account, with OpenAlgo Historify data, and what diversification really...
Part 2 of our Nautilus Trader series: position sizing, market, limit and stop orders, the backtest settings that move results, and...
New to Nautilus Trader? Learn its event-driven architecture, how orders fill in a backtest, and how to backtest an NSE strategy...
Marginism is a Python library that removes that dependency completely. You give it the exchange's daily SPAN risk parameter file and...
Learn how to build survivorship-bias-free NIFTY 50 backtests using historical constituents, official index weights, effective dates, and NSE Indices data. See...
Partial derivatives are the foundation of modern options trading, quantitative finance, and algorithmic trading. Learn how concepts like Delta, Gamma, Theta,...
Build a Python ORB strategy visualizer with OpenAlgo: fetch 1-minute data, compute opening range levels, add stop loss and target logic,...
Event driven backtesting simulates trading the way markets actually work. Instead of calculating everything at once, it processes events step by...
We spent two years building OpenAlgo as an open source, self hostable algorithmic trading infrastructure. Today it has crossed 100000 downloads,...
Python has become the foundation of modern retail algorithmic trading, especially as 2026 brings tighter regulations, clearer expectations and more powerful...
I recently challenged Claude Sonnet 4.5, Anthropic's most advanced model for coding and real-world agents, with what seemed like a straightforward...
OpenAlgo is more than just a broker API wrapper. It is a self-hosted, open-source trading infrastructure designed for traders, brokers, and...
