Get Historical Prices, Fundamentals, Metrics/Ratios etc. for thousands of Stocks, Bonds, Indexes, (Crypto-) Currencies
What you'll learn
Importing free / low-priced Financial Data from the Web with Python
Installing the required Libraries and Packages
Working with powerful APIs and Python wrapper packages
Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETF´s
Downloading Historical Prices for Currencies (FOREX), Cryptocurrencies, Bonds & more
Saving / Storing the Data locally
Pandas Coding Crash Course
Some Python Basics
A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
An internet connection capable of streaming videos and downloading data
Ideally first experience with Pandas Library (not necessary, a Pandas crash course is included in the course)
What can be the most critical and most expensive part when working with financial data?
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
Historical Price and Volume Data for thousands of Stocks, Indexes, Mutual Funds and ETFs