Popular GitHub Repositories for Carry Trade

阿布量化交易系统(股票，期权，期货，比特币，机器学习) 基于python的开源量化交易，量化投资架构

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

[ICML'24] SeeAct is a system for generalist web agents that autonomously carry out tasks on any given website, with a focus on large multimodal models (LMMs) such as GPT-4V(ision).

Learning to trade under the reinforcement learning framework

Framework for developing, backtesting, and deploying automated trading algorithms and trading bots.

Source code for transferable dialogue state generator (TRADE, Wu et al., 2019). https://arxiv.org/abs/1905.08743

Machine learning models for time series analysis

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A Deep Reinforcement Learning Framework for Stock Market Trading

A Bitcoin trade robot based on Tensorflow LSTM model.Just for fun.

Building a population of models that trade crypto and mutate iteratively

Like ChatGPT's voice conversations with an AI, but entirely offline/private/trade-secret-friendly, using local AI models such as LLama 2 and Whisper

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Our codebase trials provide an implementation of the Select and Trade paper, which proposes a new paradigm for pair trading using hierarchical reinforcement learning. It includes the code for the proposed method and experimental results on real-world stock data to demonstrate its effectiveness.

Implementation of "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading." In Findings of ACL2021

Build your autonomous hedge fund in minutes. AutoHedge harnesses the power of swarm intelligence and AI agents to automate market analysis, risk management, and trade execution.

?Pumpfun Trading AI Agent - Auto Trade Learning AI Bot - Pumpfun Real Time Tracker AI Agent

WATTNet: Learning to Trade FX with Hierarchical Spatio-Temporal Representations of Highly Multivariate Time Series

Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off" and our NeurIPS 2023 paper "Learning to Receive Help: Intervention-Aware Concept Embedding Models"