Course details
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… + Read More
Course details
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
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)
Cashflow Statements
50+ Technical Indicators (e.g. SMA, Bollinger Bands)
Real-time and Historical Data (back to 1960s)
Streaming high-frequency real-time Data
Stock Splits and Dividends and how these are reflected in Stock Prices
Learn how Stock Prices are adjusted for Stock Splits and Dividends...
and use appropriately adjusted data for your tasks! (avoid the Pitfalls!)
Build your own Financial Databases...
And save thousands of USDs!
What are you waiting for? As always, I provide a 30-Days-Money-Back Guarantee. So, there is no risk for you!
Looking forward to seeing you in the course!
Updated on 11 March, 2020 - Read Less
