https://github.com/xiawu/awesome-finance

https://github.com/xiawu/awesome-finance

List: awesome-finance

Last synced: about 1 month ago
JSON representation

• Host: GitHub
• URL: https://github.com/xiawu/awesome-finance
• Owner: xiawu
• Created: 2025-01-10T10:19:38.000Z (about 1 month ago)
• Default Branch: main
• Last Pushed: 2025-01-10T10:41:00.000Z (about 1 month ago)
• Last Synced: 2025-01-10T11:41:21.900Z (about 1 month ago)
• Size: 5.86 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• ultimate-awesome - awesome-finance - A curated list of awesome financial software, libraries, resources, and tools. (Other Lists / Julia Lists)

README

        
# Awesome Finance [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

A curated list of awesome financial software, libraries, resources, and tools.

## Contents

- [Trading & Investment Platforms](#trading--investment-platforms)

- [Market Data](#market-data)

- [Libraries & SDKs](#libraries--sdks)

- [Trading Frameworks](#trading-frameworks)

- [AI & Machine Learning](#ai--machine-learning)

- [Portfolio Management](#portfolio-management)

- [Cryptocurrency](#cryptocurrency)

- [Personal Finance](#personal-finance)

- [Risk Management](#risk-management)

- [Educational Resources](#educational-resources)

- [Numerical Libraries](#numerical-libraries)

- [Time Series Analysis](#time-series-analysis)

- [Backtesting & Trading](#backtesting--trading)

- [Reinforcement Learning Tools](#reinforcement-learning-tools)

- [Trading Utilities](#trading-utilities)

- [Financial Datasets](#financial-datasets)

- [Time Series Forecasting Models](#time-series-forecasting-models)

## Trading & Investment Platforms

- [Alpaca](https://alpaca.markets/) - Commission-free stock trading API for algorithmic trading

- [Interactive Brokers](https://www.interactivebrokers.com/) - Professional trading platform with comprehensive API

- [Robinhood](https://robinhood.com/) - Commission-free investing platform

- [TD Ameritrade](https://www.tdameritrade.com/) - Trading platform with powerful APIs

## Market Data

- [Alpha Vantage](https://www.alphavantage.co/) - Free APIs for realtime and historical financial data

- [Yahoo Finance](https://finance.yahoo.com/) - Financial news and data platform

- [IEX Cloud](https://iexcloud.io/) - Financial data infrastructure

- [Finnhub](https://finnhub.io/) - Real-time RESTful APIs for stocks, forex, and crypto

- [Marketstack](https://marketstack.com/) - Real-Time, Intraday & Historical Market Data API

- [Financial Modeling Prep](https://site.financialmodelingprep.com/developer/docs) - Realtime and historical stock data

- [SEC EDGAR Data](https://www.sec.gov/edgar/sec-api-documentation) - API to access annual reports of public US companies

- [StockData](https://www.stockdata.org) - Real-Time, Intraday & Historical Market Data, News and Sentiment API

## Libraries & SDKs

### Python

- [QuantLib](https://www.quantlib.org/) - Library for quantitative finance

- [pandas-ta](https://github.com/twopirllc/pandas-ta) - Technical Analysis Indicators in Pandas

- [FinanceAnalysis](https://github.com/JerBouma/FinanceDatabase) - Database for financial data

- [yfinance](https://github.com/ranaroussi/yfinance) - Yahoo Finance market data downloader

- [metrics.py](https://github.com/chrisconlan/algorithmic-trading-with-python/blob/master/src/metrics.py) - Performance metrics for evaluating trading strategies

- [indicators.py](https://github.com/chrisconlan/algorithmic-trading-with-python/blob/master/src/indicators.py) - Common technical indicators implemented in Pandas

- [signals.py](https://github.com/chrisconlan/algorithmic-trading-with-python/blob/master/src/signals.py) - Converting technical indicators into trading signals

- [portfolio.py](https://github.com/chrisconlan/algorithmic-trading-with-python/blob/master/src/portfolio.py) - Object-oriented portfolio simulation tools

### JavaScript

- [ccxt](https://github.com/ccxt/ccxt) - Cryptocurrency trading API

- [finance.js](https://github.com/ebradyjobory/finance.js) - Financial calculations in JavaScript

- [accounting.js](http://openexchangerates.github.io/accounting.js/) - Number, money and currency formatting

### Julia

- [Ito.jl](https://github.com/JuliaQuant/Ito.jl) - Quantitative finance in Julia

- [QuantLib.jl](https://github.com/pazzo83/QuantLib.jl) - QuantLib implementation in pure Julia

- [Miletus.jl](https://github.com/JuliaComputing/Miletus.jl) - Financial contract modeling and valuation framework

### Java

- [Strata](https://strata.opengamma.io/) - Modern open-source analytics and market risk library

- [JQuantLib](http://www.jquantlib.org/) - Free, open-source quantitative finance framework

- [finmath](https://www.finmath.net/) - Mathematical finance algorithms library

### Rust

- [QuantMath](https://github.com/MarcusRainbow/QuantMath) - Financial mathematics library

- [Barter](https://github.com/barter-rs/barter-rs) - Framework for building trading systems

- [RustQuant](https://github.com/avhz/RustQuant) - Quantitative finance library in Rust

## Portfolio Management

- [Portfolio Visualizer](https://www.portfoliovisualizer.com/) - Portfolio analysis and optimization tools

- [OpenBB Terminal](https://openbb.co/) - Open-source investment research platform

- [Quantopian](https://www.quantopian.com/) - Platform for developing trading strategies

## Cryptocurrency

- [CoinGecko](https://www.coingecko.com/) - Cryptocurrency data aggregator

- [Binance](https://www.binance.com/) - Cryptocurrency exchange with extensive API

- [MetaMask](https://metamask.io/) - Ethereum wallet and gateway

- [CryptoCompare](https://www.cryptocompare.com/) - Cryptocurrency market data

## Personal Finance

- [Mint](https://mint.intuit.com/) - Personal finance and budgeting tool

- [YNAB](https://www.ynab.com/) - Zero-based budgeting software

- [Personal Capital](https://www.personalcapital.com/) - Investment and wealth management platform

- [GnuCash](https://www.gnucash.org/) - Open-source accounting software

## Risk Management

- [OpenRisk](https://www.openriskmanagement.com/) - Open-source risk management tools

- [Risk-API](https://www.risk-api.io/) - Risk management API

- [PyRisk](https://github.com/PyRisk/PyRisk) - Python library for risk analytics

## Educational Resources

### Websites

- [Investopedia](https://www.investopedia.com/) - Financial education website

- [Khan Academy - Finance](https://www.khanacademy.org/economics-finance-domain) - Free finance courses

- [Wall Street Oasis](https://www.wallstreetoasis.com/) - Financial careers community

### Books

- "The Intelligent Investor" by Benjamin Graham

- "A Random Walk Down Wall Street" by Burton Malkiel

- "Options, Futures, and Other Derivatives" by John C. Hull

## AI & Machine Learning

- [AI Hedge Fund](https://github.com/virattt/ai-hedge-fund) - Educational proof-of-concept for an AI-powered hedge fund using multiple agents (valuation, sentiment, fundamentals, technical analysis, risk management)

- [FinRL](https://github.com/AI4Finance-Foundation/FinRL) - Deep reinforcement learning framework for quantitative finance

- [OpenBB](https://openbb.co/) - Open source investment research platform with AI capabilities

- [Qlib](https://github.com/microsoft/qlib) - AI-oriented quantitative investment platform by Microsoft

- [FinGPT](https://github.com/AI4Finance-Foundation/FinGPT) - Open source LLMs for financial applications

- [FinCon](https://arxiv.org/abs/2407.06567) - A synthesized LLM multi-agent framework for financial decision making, featuring:

  - Manager-analyst communication hierarchy for collaborative decision making

  - Risk-control component with self-critiquing mechanism

  - Conceptual verbal reinforcement for knowledge updates

  - Applications in stock trading and portfolio management

  - Strong generalization capabilities across various financial tasks

- [Deep Learning for Crypto](https://arxiv.org/abs/2405.11431) - Comprehensive review and evaluation of deep learning models for cryptocurrency price prediction:

  - Evaluation of LSTM variants, CNN variants, and Transformer models

  - Comparison of univariate vs multivariate approaches

  - Multi-step ahead prediction capabilities

  - COVID-19 impact analysis on model performance

  - Best performance achieved by convolutional LSTM with multivariate approach

  - Implementation insights for different market conditions

## Currency & Exchange

- [Fixer.io](https://fixer.io) - Foreign exchange rates and currency conversion API

- [Currency-api](https://github.com/fawazahmed0/currency-api) - Free Currency Exchange Rates API with 150+ Currencies

- [ExchangeRate-API](https://www.exchangerate-api.com) - Free currency conversion

- [Frankfurter](https://www.frankfurter.app/docs) - Exchange rates, currency conversion and time series

- [VATComply.com](https://www.vatcomply.com/documentation) - Exchange rates, geolocation and VAT number validation

## Banking & Payments

- [Plaid](https://plaid.com/docs) - Connect with user's bank accounts and access transaction data

- [Razorpay IFSC](https://razorpay.com/docs/) - Indian Financial Systems Code (Bank Branch Codes)

- [Mono](https://mono.co/) - Connect with users' bank accounts and access transaction data in Africa

- [Nordigen](https://nordigen.com/en/account_information_documentation/integration/quickstart_guide/) - Connect to bank accounts using official bank APIs

## Numerical Libraries

- [NumPy](https://numpy.org/) - Fundamental package for scientific computing with Python

- [SciPy](https://scipy.org/) - Ecosystem of open-source software for mathematics, science, and engineering

- [Pandas](https://pandas.pydata.org/) - High-performance data structures and data analysis tools

- [Polars](https://pola.rs/) - Lightning-fast DataFrame library for data manipulation

- [SymPy](https://www.sympy.org/) - Library for symbolic mathematics

- [PyMC](https://docs.pymc.io/) - Probabilistic programming with Bayesian modeling

- [ArcticDB](https://github.com/man-group/arctic) - High performance datastore for time series and tick data

## Time Series Analysis

- [ARCH](https://github.com/bashtage/arch) - Autoregressive Conditional Heteroskedasticity models in Python

- [statsmodels](https://www.statsmodels.org/) - Statistical modeling and econometrics in Python

- [PyFlux](https://github.com/RJT1990/pyflux) - Time series modeling and inference

- [tsfresh](https://tsfresh.readthedocs.io/) - Automatic extraction of relevant features from time series

- [Prophet](https://facebook.github.io/prophet/) - Tool for producing high quality forecasts for time series data

- [pmdarima](https://alkaline-ml.com/pmdarima/) - ARIMA estimators for Python

- [gluon-ts](https://ts.gluon.ai/) - Probabilistic time series modeling

## Backtesting & Trading

- [Zipline](https://github.com/quantopian/zipline) - Pythonic algorithmic trading library

- [Backtrader](https://www.backtrader.com/) - Python backtesting library for trading strategies

- [QSTrader](https://github.com/mhallsmoore/qstrader) - Backtesting simulation engine

- [bt](https://github.com/pmorissette/bt) - Flexible backtesting for Python

- [PyAlgoTrade](https://github.com/gbeced/pyalgotrade) - Algorithmic trading library

- [VectorBT](https://vectorbt.dev/) - Fast backtesting and research platform

- [FinRL](https://github.com/AI4Finance-Foundation/FinRL) - Deep reinforcement learning for trading

- [Blankly](https://github.com/blankly-finance/blankly) - Unified interface for trading and backtesting

## Trading Frameworks

- [TradeMaster](https://github.com/TradeMaster-NTU/TradeMaster) - Open-source platform for quantitative trading empowered by reinforcement learning, featuring:

  - Multi-modality market data processing

  - High-fidelity market simulators

  - 13+ RL-based trading algorithms

  - Systematic evaluation toolkits

  - Support for multiple trading tasks (portfolio management, high-frequency trading, etc.)

  - Comprehensive visualization tools

- [FinRL](https://github.com/AI4Finance-Foundation/FinRL) - Deep reinforcement learning framework for quantitative finance

- [Blankly](https://github.com/blankly-finance/blankly) - Unified interface for trading and backtesting

## Reinforcement Learning Tools

- [RLlib](https://docs.ray.io/en/latest/rllib/index.html) - Industry-grade library for reinforcement learning with support for:

  - 30+ RL algorithms (PPO, A2C, DDPG, TD3, SAC, IMPALA, etc.)

  - Multi-agent RL

  - Distributed training

  - TensorFlow, PyTorch, and JAX

- [Stable Baselines3](https://github.com/DLR-RM/stable-baselines3) - Set of reliable implementations of RL algorithms in PyTorch

- [SpinningUp](https://spinningup.openai.com/) - Educational resource with clean implementations of key algorithms (PPO, TRPO, DDPG, TD3, SAC)

- [Acme](https://github.com/deepmind/acme) - DeepMind's framework for RL research, supporting:

  - TensorFlow and JAX

  - Distributed training

  - State-of-the-art algorithms (DDPG, D4PG, MPO, R2D2)

- [Dopamine](https://github.com/google/dopamine) - Research framework for fast prototyping of RL algorithms by Google

- [Coax](https://github.com/coax-dev/coax) - Lightweight RL framework with clean implementations using JAX

- [Garage](https://github.com/rlworkgroup/garage) - Toolkit for reproducible reinforcement learning research with:

  - Comprehensive testing suite

  - Support for PyTorch and TensorFlow

  - Multi-task and meta-RL algorithms

## Trading Utilities

- [algorithmic-trading-with-python](https://github.com/chrisconlan/algorithmic-trading-with-python) - Comprehensive collection of trading utilities including:

  - Performance metrics evaluation tools

  - Technical indicators in pure Pandas

  - Ternary signal conversion

  - Grid search optimization

  - Portfolio simulation building blocks

  - Multi-core K-fold cross-validation

  - EOD stock data and alternative data streams

## Financial Datasets

- [Financial Datasets](https://www.financialdatasets.ai/) - A comprehensive platform offering a wide range of financial datasets, including:

  - Stock market data

  - Economic indicators

  - Alternative data sources

  - Historical financial data

  - APIs for easy access to datasets

## Time Series Forecasting Models

- [TimesFM](https://huggingface.co/google/timesfm-2.0-500m-pytorch) - A pretrained time-series foundation model developed by Google Research for time-series forecasting, featuring:

  - Univariate time series forecasting for context lengths up to 2048 time points

  - Point forecasts with optional quantile heads

  - Support for various frequency indicators

  - Installation and usage instructions available on the Hugging Face page

  - Pretraining data includes a variety of datasets for robust performance

## Contributing

Please read the [contribution guidelines](CONTRIBUTING.md) first. Feel free to contribute by submitting a pull request.

## License

[![CC0](https://licensebuttons.net/p/zero/1.0/88x31.png)](https://creativecommons.org/publicdomain/zero/1.0/)

To the extent possible under law, the authors have waived all copyright and related rights to this work.