Importing Finance Data with Python from Free Web Sources

Posted By: naag

Importing Finance Data with Python from Free Web Sources
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | 7 hours 49 minutes | 93 lectures | 3.02 GB
Genre: eLearning | Language: English

Get Historical Prices, Fundamentals, Metrics/Ratios etc. for thousands of Stocks, Bonds, Indexes, (Crypto-) Currencies

(Latest course update and full code review in April 2023!)
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 Statement
s (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!