nymath/torchqtm
TorchQuantum is a backtesting framework that integrates the structure of PyTorch and WorldQuant's Operator for efficient quantitative financial analysis.
This helps quantitative traders and researchers efficiently test and refine trading strategies, often called 'alphas'. You input historical financial data and defined trading rules, and it outputs simulated performance metrics to evaluate how well your strategy would have performed. It's designed for quantitative analysts and portfolio managers who develop rule-based trading systems.
No commits in the last 6 months.
Use this if you need a high-speed framework to backtest various quantitative trading strategies using historical market data.
Not ideal if you're looking for a simple tool for basic stock chart analysis or don't have programming experience.
Stars
50
Forks
13
Language
Cython
License
MIT
Category
Last pushed
Jul 13, 2023
Commits (30d)
0
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