yacht
Unverified ML strategy on Crypto by iusztinpaul. BotFinder score 18 out of 100.
Order execution in the financial markets using Deep Reinforcement Learning.
Source: github
BotFinder analysis pending.
yacht
Yacht: Yet Another Comprehensive Trading Framework Using Deep Reinforcement Learning A Deep Reinforcement Learning framework for trading & order execution in financial markets. The goal of the project is to speed up the development & research of financial agents by building a modular and scalable codebase. The framework supports the following main features: Loading & preprocessing data directly from different APIs Training & evaluating deep reinforcement learning agents Use specific financial metrics or quickly implement your own Visualizing the performance of the agent with some intuitive graphs The nice part is that everything is configurable within a config file. The code is using popular packages like: pytorch pandas stable-baselines3 gym wandb mplfinance Project Architecture The architecture is split into 4 main categories: Data Environment Reinforcement Learning Agents Specific Task Layer The Specific Task Layer is a glue code module that is used for training & backtesting. It can be further be extended into the applicaton layer. Visual Representations Visual representations of
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