Project case study
Algorithmic Trading System
Finance
Python/C++ libraries powering live execution and backtesting across equities, options, futures, and crypto
PythonC++NumPySciPyPandasNumbastatsmodels
Python and C++ tools and libraries interfacing with market brokers to execute and backtest algorithmic trading across equities, options, futures, and crypto markets.
Unified object-oriented libraries written in Python, with C++ for performance-critical paths, power both live execution and backtesting for rules-based and ML-driven strategies. They also provide built-in exposure to key trading metrics for evaluating strategy performance.