3 repository-uri
Awesome GitHub RepositoriesStrategy Benchmarkers
Tools for comparing trading strategy returns against reference assets or market indices.
Distinct from Performance Benchmarking: Focuses on financial strategy benchmarking rather than general software performance evaluation.
Explore 3 awesome GitHub repositories matching software engineering & architecture · Strategy Benchmarkers. Refine with filters or upvote what's useful.
Awesome Strategy Benchmarkers GitHub Repositories
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- mementum/backtrader
mementum/backtrader
20,462Vezi pe GitHubBacktrader is a Python framework designed for the development, backtesting, and live execution of algorithmic trading strategies. It provides a comprehensive environment for quantitative finance, allowing users to simulate trading logic against historical market data or connect directly to brokerage platforms for automated real-time trading. The project distinguishes itself through a unified event-driven architecture that treats backtesting and live trading with the same API. This consistency is supported by a flexible data-feed abstraction layer that normalizes diverse financial sources, ena
Compares trading strategy returns against reference assets or market indices to measure relative success and performance.
Pythonbacktestingmetaclasspython - ai4finance-foundation/finrl
AI4Finance-Foundation/FinRL
13,964Vezi pe GitHubFinRL is a reinforcement learning framework designed for the development, training, and backtesting of automated trading strategies. It functions as a quantitative finance toolkit that integrates deep learning algorithms with financial market simulations to address complex portfolio management and asset allocation tasks. The platform provides an end-to-end pipeline for transforming raw market data into actionable trading models. The project distinguishes itself through a layered, modular architecture that separates data processing, environment simulation, and agent training. This design allow
Provides tools for evaluating and comparing the performance of reinforcement learning trading strategies against standardized financial benchmarks.
Jupyter Notebookalgorithmic-tradingdeep-reinforcement-learningdrl-algorithms - ricequant/rqalpha
ricequant/rqalpha
6,166Vezi pe GitHubRQAlpha is a Python-native quantitative trading backtesting framework and live trading execution system. It provides an event-driven engine for simulating trading strategies against historical market data, with realistic transaction costs, slippage models, and corporate action handling. The platform supports multi-asset class trading including stocks, futures, options, and REITs, with separate sub-accounts for different asset types and configurable margin requirements. The framework distinguishes itself through a plugin-based extensible architecture that allows users to swap out core componen
Visualizes strategy net asset value alongside a benchmark index for comparison.
Pythonbacktestfinancefutures
