Solving problems in finance with machine learning.
Experiments based on "Advances in financial machine learning" book.
Using advanced ML solutions to overcome real-world investment problems.
Learn Fintech Online.
Book about how to build financial software hands-on using generative AI tools like ChatGPT and Copilot.
Sources codes for: Mastering Python for Finance, Second Edition.
Slides, scripts and materials for the Machine Learning in Finance course at NYU Tandon, 2022.
🌟 - Quantitative analysis, strategies and backtests https://letianzj.github.io/
In this tutorial you won't build an ML system that will make you rich. But you will master the MLOps frameworks and tools you need to build ML systems that, together with tons of experimentation, can take you there.
A live crypto currency historical trade data blotter. Download live historical trade data from any crypto exchange.
Stock Market and Financial Data API.
Gekko trading bot dataset dumps. Download and use history files in SQLite format.
🌟 - Get millions of financial and economic dataset from hundreds of publishers via a single free API.
Crawling historical data of Chinese stocks.
Python module to get stock data from Yahoo! Finance.
Scalable, event-driven, deep-learning-friendly backtesting library.
Shanghai future exchange CTP api.
Connect HUOBIPRO exchange, get market/historical data for ABAT trading platform backtest analysis and live trading.
Python API for the Interactive Brokers on-line trading system.
Highly customizable professional lightweight financial charts
Visualizer for deep learning and machine learning models.
Javascript SDK for Trading/Data API and Websockets for cryptocurrency exchanges like FTX, FTXUS, OKX, Bybit, & More
Play with neural networks.
High-performance TensorFlow library for quantitative finance.
🌟 - Trading and Backtesting environment for training reinforcement learning agent.
Trading environment for RL agents, backtesting and training.
🌟 - Explore the use of AI to make trading decisions.
Use ChatGPT to determine which cryptocurrency to trade based on technical indicators.
🌟🌟 - GPT-4 can outperform professional financial analysts in predicting future earnings changes, generating useful narrative insights, and resulting in superior trading strategies with higher Sharpe ratios and alphas, thereby suggesting a potential central role for LLMs in financial decision-making.
Provides a playground for all people interested in LLMs and NLP in Finance.
Train and deploy a real-time financial advisor chatbot with Falcon 7B and CometLLM.
Asked ChatGPT on which indicators are the most popular for trading. We used all of the recommendations given.
🌟🌟 - A Financial Market Simulation Engine Powered by Generative Foundation Model.
An open-source resource providing a financial large language model, a dataset with 136K instruction samples, and a comprehensive evaluation benchmark.
A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance).
🌟 - Quant / Algorithm trading resources with an emphasis on Machine Learning.
Explore a curated list of Fintech popular & new libraries, top authors, trending project kits, discussions, tutorials & learning resources on kandi.
A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.
🌟🌟 - A curated list of practical financial machine learning (FinML) tools and applications. This collection is primarily in Python.
AI gateway and marketplace for developers, enables streamlined integration and least volatile approach of AI features into products
An UI port for gekko trading bot using Quasar framework.
🌟🌟🌟 - Stock-Prediction-Models, Gathers machine learning and deep learning models for Stock forecasting, included trading bots and simulations.
TensorBoard as a Zipline dashboard.
The common-stock prices can be regarded as an ensemble of decisions in statistical equilibrium.
Propose an ensemble strategy that employs deep reinforcement schemes to learn a stock trading strategy by maximizing investment return.
The power laws in the distributions of event sizes under a broad range of conditions in a large variety of systems.
Deep reinforcement learning provides a framework toward end-to-end training of such trading agent.
Introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies.
With an appropriate choice of the reward function, reinforcement learning techniques can successfully handle the risk-averse case.
Slides review few important financial ML applications.
The influences which determine the movements of the Stock Exchange are.
Performance analysis of predictive (alpha) stock factors.
Common financial risk and performance metrics. Used by Zipline and pyfolio.
An open source quant strategies research platform.
Quant resources from ArXiv (sanity), SSRN, RePec, Journals, Podcasts, Videos, and Blogs.
Portfolio and risk analytics in Python.
AI-powered collaborative environment for Research.
🌟🌟 - Trade efficiently with reinforcement learning.
Zero vector trader.
Arbitrage bot that currently works on bittrex & poloniex.
Build a Deep Q-learning reinforcement agent model as automated trading robot.
Bitcoin arbitrage opportunity detector.
Bitcoin MACD crossover trading strategy backtest.
Code for "Bitcoin Prediction" by Siraj Raval on YouTube.
Long / short market-neutral strategy.
ML powered analytics engine for outlier/anomaly detection and root cause analysis..
Automated crypto trading & technical analysis (TA) bot for Bittrex, Binance, GDAX, and more.
A crypto currency arbitrage opportunity calculator. Over 800 currencies and 50 markets.
A light-weight deep reinforcement learning framework for portfolio management.
Portfolio optimization with deep learning.
Machine learning in quant analysis.
Trading environment(OpenAI Gym) + DDQN (Keras-RL).
🌟 - Deep Reinforcement Learning for Automated Stock Trading.
Ethereum trading algorithm using Python 3.5 and the library ZipLine.
A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance.
Node.js native library performing technical analysis over an OHLC dataset with use of genetic algorithmv.
Calculate down peak and trade on.
Gekko RSI_WR strategies.
Gekko bot resources.
Gann's Swing trade strategy for Gekko trade bot.
Neural network strategy for Gekko.
Strategies to Gekko trading bot with backtests results and some useful tools.
Genetic algorithm for solving optimization of trading strategies using Gekko.
ANN trading strategies for the Gekko trading bot.
Gekko strategies, tools etc.
Awesome crypto currency trading platform.
Environment for reinforcement-learning algorithmic trading models.
Analysis of High Frequency Trading on Bitcoin exchanges.
A high-frequency trading model using Interactive Brokers API with pairs and mean-reversion.
Use LSTM to predict lottery.
Predicting price trends in crypto markets using an LSTM-RNN for trading.
Scalable machine learning based time series forecasting.
🌟 - Implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
A Deep Reinforcement Learning framework for the financial portfolio management problem.
Reinforcement Learning for portfolio management.
A powerful and flexible Python framework for designing, backtesting, optimizing, and deploying algotrading bots
Python quantitative trading strategies.
Papers and code implementing Quantitative-Trading.
Automatic arbitrage trading system powered by Node.js + TypeScript.
🌟 - Solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Python library for portfolio optimization built on top of scikit-learn.
🌟🌟 - A complete process for predicting stock price movements.
🌟🌟 - Complete process for predicting stock price movements.
Stock market trading OpenAI Gym environment with Deep Reinforcement Learning using Keras.
A population model that trade cyrpto and breed and mutate iteratively.
TensorForce Bitcoin trading bot.
Trading environment(OpenAI Gym) + PPO(TensorForce).
Trading agent to train with episode of short term trading itself.
Deep Reinforcement Learning for Financial Trading using Price Trailing.
🌟 - A stock trading bot powered by Trump tweets.
A framework for machine-learning bots.
Common financial technical indicators implemented in Python-Pandas (70+ indicators).
A Python Pandas implementation of technical analysis indicators.
A visual, technical analysis and charting (Candlestick, OHLC, indicators) library built on D3.
Official Node.js wrapper for Tulip Indicators. Provides over 100 technical analysis overlay and indicator functions.
A quant trading system base on python.
Python backtesting library for trading strategies.
High-frequency crypto currency trading bot developed by Zenbot.
An algorithmic trading library for Crypto-Assets in python.
As backtest frameworks for coin trading strategy.
Tests bt and Quantopian Zipline as backtesting frameworks for coin trading strategy.
Batch backtest, import and strategy params optimalization for Gekko Trading Bot.
Kungfu Master trading system.
Algorithmic trading engine built for easy strategy research, backtesting and live trading.
Zenbot MACD Auto-Trader.
Crypto currency trading bot using Node.js and MongoDB.
🌟🌟🌟 - AI-powered opensource research and analytics workspace.
Python live trade execution library with zipline interface.
Quant Research dev & Traders open source project.
A extendable, replaceable Python algorithmic backtest & trading framework.
🌟 - Get real-time information and market insights.
Command-line crypto currency trading bot using Node.js and MongoDB.
🌟🌟 - A python algorithmic trading library.