With the rise of artificial intelligence and open source software, developers have created some amazing free platforms that leverage AI to empower investors. On GitHub, one can find python libraries for backtesting, neural network based trading systems, portfolio optimization tools and more. These open source projects make intelligent investing accessible to everyone.
Mature frameworks like FinRL and ElegantRL enable quick strategy iteration
The FinRL library from AI4Finance foundation provides complete pipelines for developing and evaluating AI trading strategies. It incorporates various simulated trading environments and deep reinforcement learning algorithms like DQN, DDPG, PPO. This accelerates strategy research and backtesting. ElegantRL takes a similar approach, with an emphasis on implementing cutting edge deep RL innovations for finance. Both libraries have helped students and professionals prototyping trading systems.
Research projects like zvt and vectorbt push the boundaries of data analysis
On GitHub one can also find more research oriented projects that explore new ways of analyzing market data. The zvt project offers an extendable Python framework for retrieving, storing and backtesting with Chinese stock data. Vectorbt analyzes pandas data structures at scale to backtest thousands of strategies in seconds. These novel approaches shows the potential of open source in financial data engineering.
Decentralized finance protocols promise transparent automated trading
The decentralized finance or DeFi movement aims to build free, open financial systems on blockchain networks. DeFi protocols like Hummingbot allow creating automated market making bots that provide liquidity on decentralized exchanges. While still early stage, these innovations can reduce reliance on centralized institutions for trading and investing.
GitHub has enabled an ecosystem of open source AI tools for finance, powering accessible intelligent investing. Projects like FinRL and ElegantRL lower barriers with reusable strategy pipelines, while initiatives like zvt and vectorbt push data engineering boundaries. Decentralized finance adds transparency. Undoubtedly these platforms will continue to develop innovative solutions.