Linear Regression

Capital Asset Pricing Model you own this product

This project is part of the liveProject series Linear Regression for Asset Pricing
prerequisites
basics of Python, finance, Jupyter Notebook, and machine learning
skills learned
risk management • valuation • univariate linear regression
Abdullah Karasan
1 week · 8-10 hours per week · BEGINNER
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liveProject This project is part of the liveProject series Linear Regression for Asset Pricing liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $16.49 $29.99 you save: $13 (45%)
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In this liveProject, you’ll build a machine learning system based on the Capital Asset Pricing Model (CAPM) that can determine if certain stocks are over or undervalued, and the risk level of these stocks relative to the market index. CAPM is a powerful tool in finance due to its intuitive and easy-to-apply nature, and in this project you’ll use it to estimate coefficients, determine valuation accuracy, and finally find which stock promises the best risk-return relationship.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Abdullah Karasan
Abdullah is a Principal Data Scientist at Magnimind Academy and adjunct lecturer at University of Maryland. His specialization is financial data science. He has several papers and also a book titled "Machine Learning for Financial Risk Management with Python", which will be on the market November, 2021. His technical expertise is in Machine Learning, Deep Learning, Python, Financial modeling, Risk Management, Optimization, Econometrics.

prerequisites

This liveProject is for data analysts with an interest in financial services. Some knowledge of the finance industry will be useful. To begin this liveProject you will need to be familiar with:

TOOLS
  • Basics of Python
  • Basics of Jupyter Notebook
TECHNIQUES
  • Basics of finance
  • Usage of APIs for data extraction
  • Python for data cleaning and exploration
  • Running linear regression in Python

you will learn

In this liveProject, you’ll learn to use one of the most reliable machine learning tools for finance and improve your understanding of financial data science.

  • Risk management
  • Financial risk estimation
  • Financial modeling with multivariate case

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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