Published 7/2024
Created by Dimitrios Koulialias PhD
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 20 Lectures ( 3h 22m ) | Size: 1.52 GB
A practical introduction applied to ESG rating and stock market data
What you’ll learn:
Get an insight on data acquisition and data analysis processes using financial data from yahoo finance as a test-bed
Get an introduction into HTML and its main tags/elements for understanding a webpage structure
Obtain a first understanding of BeautifulSoup as a means for scraping data from a webpage
Preprocess data in Python using Pandas
Manage and extract further information out of the scraped ESG rating score data
Get an introduction into Markowitz portfolio theory for data analysis based on a (constrained) optimization approach
Incorporate the ESG rating score data into Markowitz’ portfolio theory and assess the effect on the risk and return
Requirements:
Some basic knowledge in Python as well as finance would be helpful, but is not mandatory
Description:
Have you ever wondered how web scraping works and what added value you can gain from the extracted data? Plus the opportunity to get more information by analyzing data in an end-to-end project in Python? Then this is the right course for you!In this course “Web Scraping and Data Analysis with Python – A Practical Introduction Applied to ESG Rating and Stock Market Data,” I will provide you a comprehensive introduction on how to apply web scraping and data analysis approaches in Python using financial data from Yahoo Finance as a test-bed. After a brief insight into HTML, we will cover the essentials of web scraping using BeautifulSoup, a well-known library in Python, in order to extract a series of ESG (Environmental, Social, and Governance) scores along with their underlying stock prices. In turn, we will move to the data analysis part, where we will conduct portfolio optimizations based on the Markowitz model. There, you will get familiar with the approaches on how to perform a classic portfolio optimization and then enhance it by incorporating the ESG scores obtained from the web scraping part. This will help you gaining an understanding on how to make data-driven decisions in finance, and to assess the effect between the risk/return profile and sustainability factors.By the end of this course, you will obtain the skills to build your own web scraping and data analysis projects in Python, enabling you to extract valuable information from the web and turn it into actionable insights.
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