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ai4finance_job_info

Job Infor in the intersection of AI, Big data, and Finance.

awesome-ai-in-finance

🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.

awesome-conformal-prediction

A professionally curated list of awesome Conformal Prediction videos, tutorials, books, papers, PhD and MSc theses, articles and open-source libraries.

awesome_ai4finance

Resources

deep-reinforcement-learning-for-stock-trading-ddpg-algorithm-nips-2018

Practical Deep Reinforcement Learning Approach for Stock Trading. NeurIPS 2018 AI in Finance.

elegantrl

Massively Parallel Deep Reinforcement Learning. 🔥

fin-emotion

financial-news-for-stock-prediction-using-dp-lstm-nips-2019

Differential Privacy-inspired LSTM for Stock Prediction Using Financial News. NeurIPS Robust AI in Financial Services 2019.

fingpt

Data-Centric FinGPT. Open-source for open finance! Revolutionize 🔥 We'll soon release the trained model.

finmarketpy

Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)

finnlp

Democratizing Internet-scale financial data.

finrl

FinRL: Financial Reinforcement Learning. 🔥

finrl-blogs

Blogs, tutorials, news. Please star.

finrl-meta

FinRL­-Meta: Dynamic datasets and market environments for FinRL.

finrl-trading

For trading. Please star.

finrl-tutorials

Tutorials. Please star.

finrl_crypto

FinRL_Crypto: Cryptocurrency trading of FinRL

finrl_imitation_learning

finrl_market_simulator

finrl_podracer

Cloud-native Financial Reinforcement Learning

fortitudo.tech

Conditional Value-at-Risk (CVaR) portfolio optimization and Entropy Pooling views / stress-testing in Python.

hudson-and-thames-quantitative-research

hudson-and-thames-research

Research Repo (Archive)

hudsonthames_soldieroffortune

"Soldier of Fortune" skill set challenge for Hudson & Thames' (c) quant developer application. Exercise consists in writing Python code for a minimum spanning tree computation, where graph nodes are financial instruments and edges are correlation distances between mutual historical price data sets.

liquidation-analysis-using-multi-agent-reinforcement-learning-icml-2019

Multi-agent Reinforcement Learning for Liquidation Strategy Analysis. ICML 2019 AI in Finance.

machine-learning-for-stock-recommendation-ieee-2018

A Practical Machine Learning Approach for Dynamic Stock Recommendation. IEEE TrustCom 2018.

meta-labeling

Code base for the meta-labeling papers published with the Journal of Financial Data Science

michelleandrews

Hudson and Thames: A Machine Learning based Pairs Trading Investment Strategy

mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

optimistic-bull-pessimistic-bear-drl-stock-portfolio-allocation-icml-2019