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 . Downloading Historical Prices and Fundamentals for thousands of Stocks, Indexes, Mutual Funds and ETFs . Saving / Storing the Data locally is the most critical and most expensive part when working with financial data . Creating advanced Algorithms to analyse and optimize portfolios? Building solutions for Algorithmic Trading and Robo Advising? Maybe! But very often it is … getting the Data!Authentication failed. Unique API key is not valid for this user.
Who this course is for:
- Investment & Finance Professionals (and their Companies) spending thousands of USD p.a. on Financial Data.
- (Finance) Students and Researchers who need to work with large financial datasets with only small budgets.
- Everybody working occasionally with Financial Data.
|File Name :||Importing Finance Data with Python from Free Web Sources free download|
|Genre / Category:||Office Productivity|
|File Size :||4.22 gb|
|Publisher :||Alexander Hagmann|
|Updated and Published:||05 May,2022|