Quanturf’s Datasets! - Free Financial data for building Financial models¶
This documentation contains the information about the Free financial dataset for thousands of asset classes, macroeconomic data, fundamentals and alternative data that can be used for building models on Quanturf.
This doumentation shows you how to get massive amounts of Financial Data and explains how to install required Libraries and how to download/import the data with few lines of Python Code.
The data covered in this documentation include:¶
Historical Price and Volume Data for 100,000+ Symbols/Instruments.
50+ Exchanges all around the world.
Real-time and Historical Data (back to 1960s)
High-frequency real-time Data
Foreign Exchange (FOREX): 150+ Currency Pairs
500+ Cryptocurrencies
Commodities (Crude Oil, Gold, Silver, etc.)
Futures and Option data
Macroeconomic variables
Stock Options, Stock Splits and Dividends for 5000+ Stocks
Fundamentals, Metrics and Ratios for Stocks, Bonds, Indexes, Mutual Funds and ETFs
Balance Sheets, Cashflow and Profit and Loss Statements (P&L)
50+ Technical Indicators (i.e. SMA, Bollinger Bands).
Financial Datasets - Summary by source and types:¶
Categories
- Equities
- Fixed Income
- FX
- Commodities
- Cryptocurrencies
- Stock Fundamentals
- Options and Future
- Macroeconomic Data
- News and Sentiments
- Alternative Data
- Volume and Price data:
- Importing Many Stocks:
- Indices
- Stock Splits and Dividends
- Technical Indicators
- Which algorithm should I use?
- Tips and Tricks when creating a custom environment
- Tips and Tricks when implementing an RL algorithm
Contributing¶
To any interested in making the FinAIML better, there are still some improvements that need to be done. A full TODO list is available in the roadmap.
If you want to contribute, please go through CONTRIBUTING.md first.