Using Traditional Finance Models you own this product

prerequisites
intermediate Python • basic scikit-learn and Matplotlib • basic financial concepts • intermediate machine learning
skills learned
volatility forecasting in financial modeling using ARCH and GARCH • optimizing financial model parameters using BIC
Abdullah Karasan
1 week · 8-10 hours per week · BEGINNER
Included with a Manning Online subscription
try now

pro $24.99 per month

  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose one free eBook per month to keep
  • exclusive 50% discount on all purchases

lite $19.99 per month

  • access to all Manning books, including MEAPs!

team

5, 10 or 20 seats+ for your team - learn more

Look inside

In this liveProject, you’ll play the part of a freelance consultant who’s been hired to assess a company’s financial risk. Using the traditional volatility modeling packages ARCH and GARCH, you’ll model the volatility of S&P-500 stock prices—a good proxy for the entire financial market—and measure model performance. Then, you’ll optimize the model parameters using information criteria such as Bayesian Information Criteria (BIC). When you’ve completed the project, you’ll have a solid understanding of the logic of these traditional models and be ready to apply it to other models.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Abdullah Karasan
Abdullah Karasan was born in Berlin, Germany. After studying economics and business administration, he obtained his master's degree in applied economics from the University of Michigan, Ann Arbor, and his PhD in financial mathematics from the Middle East Technical University, Ankara. He is a former Treasury employee of Turkey and currently works as a principal data scientist at Magnimind and as a lecturer at the University of Maryland, Baltimore. He has also published several papers in the field of financial data science.

prerequisites

The liveProject is for intermediate Python programmers who know the basics of data science. To begin this liveProject, you will need to be familiar with the following:


TOOLS
  • Intermediate Python knowledge and skills
  • Jupyter Notebook
TECHNIQUES
  • Basic financial concepts
  • Intermediate machine learning knowledge
  • sklearn for running classical time series analysis and stationary analysis
  • Matplotlib for visualization
  • ARCH for modeling
  • scipy.optimize.minimize for modeling volatility by hand

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.

related titles

choose your plan

pro

monthly
annual
$24.99
$249.99
only $20.83 per month
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Using Traditional Finance Models project for free

team

monthly
annual
$49.99
$499.99
only $41.67 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Using Traditional Finance Models project for free