Udemy – Importing Finance Data with Python from Free Web Sources

What you’ll learn:
Working with powerful APIs and Python wrapper packages
Importing free / low-priced Financial Data from the Web with Python
Downloading Historical Prices for Currencies (FOREX), Cryptocurrencies, Bonds & more
Installing the required Libraries and Packages
Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETF´s
Requirements
An internet connection capable of streaming videos.
Some Python Basics
An internet connection capable of streaming videos and downloading data
Description
Pandas coding? Creating some advanced Algorithms to analyse and optimize portfolios? Building solutions for Algorithmic Trading and Robo Advising? Maybe! But very often it is … getting the Data!
Financial Data is scarce and Premium Data Providers typically charge $20,000 p.a. and more!
However, in 95% of all cases where Finance Professionals or Researchers require Financial Data, it can actually be obtained from Free or low-priced web sources. Some of them provide powerful APIs and Python wrapper packages, which makes it easy and comfortable to import the data with and into Python.
+++ This course shows you how to get massive amounts of Financial Data from the web and provides downloadable Python coding templates (Jupyter Notebooks) for your convenience! +++
This course covers four different data sources and explains in detail how to install required Libraries and how to download and import the data with few lines of Python Code. You will have access to
60+ Exchanges all around the world
120,000+ Symbols/Instruments
Historical Price and Volume Data for thousands of Stocks, Indexes, Mutual Funds and ETFs
Foreign Exchange (FOREX): 150+ Physical Currencies / Currency Pairs
500+ Digital- / Cryptocurrencies
Fundamentals, Ratings, Historical Prices and Yields for Corporate Bonds
Commodities (Crude Oil, Gold, Silver, etc.)
Stock Options for 4,500 US Stocks
Fundamentals, Metrics and Ratios for thousands of Stocks, Indexes, Mutual Funds and ETFs
Balance Sheets
Profit and Loss Statements (P&L)
Who this course is for
(Finance) Students and Researchers who need to work with large financial datasets with only small budgets.
Everybody working occasionally with Financial Data.
Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data.
Homepage

https://www.udemy.com/course/importing-finance-data-with-python-from-free-web-sources/

 

 

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