Skip to Content
Mastering Python for Finance - Second Edition
book

Mastering Python for Finance - Second Edition

by James Ma Weiming
April 2019
Intermediate to advanced
426 pages
11h 13m
English
Packt Publishing
Content preview from Mastering Python for Finance - Second Edition

Preparing the independent and target variables

Let's obtain the datasets of GS and JPM prices from Alpha Vantage with the following code:

In [ ]:    from alpha_vantage.timeseries import TimeSeries    # Update your Alpha Vantage API key here...    ALPHA_VANTAGE_API_KEY = 'PZ2ISG9CYY379KLI'    ts = TimeSeries(key=ALPHA_VANTAGE_API_KEY, output_format='pandas')    df_jpm, meta_data = ts.get_daily_adjusted(        symbol='JPM', outputsize='full')    df_gs, meta_data = ts.get_daily_adjusted(        symbol='GS', outputsize='full')

The pandas DataFrame objects df_jpm and df_gs contain the downloaded prices of JPM and GS respectively. We will be extracting the adjusted closing prices from the fifth column of each dataset.

Let's prepare our independent variables with the following ...

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Start your free trial

You might also like

Python for Finance - Second Edition

Python for Finance - Second Edition

Yuxing Yan
Python for Finance

Python for Finance

Yves Hilpisch

Publisher Resources

ISBN: 9781789346466Supplemental Content