This repository 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 algo-trading models on Quanturf.
Refer to the detailed documentation here
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.
- 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).
See detailed documentation here.
- Equities
- FixedIncome
- FX
- Commodities
- Crypto
- Fundamentals
- OptionFuture
- Macroeconomic
- Sentiments
- AlternativeData
Seperate notebook for each different library has been included.
- YahooFinance
- Alphavantage
- FundamentalAnalysis
- quandl
- FRED
- Stooq
- IEX
- Oanda
- finviz
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 <https://github.com/users/tatsath/projects/4>_.
If you want to contribute, please go through CONTRIBUTING.md <https://github.com/Quanturf/quanturf_dataset/blob/master/CONTRIBUTING.md>_ first.
- :ref:
genindex - :ref:
search - :ref:
modindex
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We prefer yfinance for technical analysis, because it has an easy-to-use API and very convenient most of the times.
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For Fundamental analysis, FundamentalAnalysis package is the best, as it requires no data cleaning and can be used directly to get detailed financial statements of a company, however it has coverage limitations and doesn't cover a lot many stock exchanges, so you can choose between Web Scraping and FundamentalAnalysis package as per your requirement.