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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.