🚀 Master the language of AI with our brand new course: "Prompt Engineering for Everyone" Learn more

Offered By: IBM

Forecasting Crypto Portfolios Like a Quant

How to easily use SARIMAX models to forecast your portfolio? At least $1 billion of client funds are missing at failed crypto firm FTX, and their FTX token has lost most of its value. How would you prevent your portfolio from having massive losses in a black swan event? This guided project will show you how to create your portfolio index that contains diverse cryptocurrencies to track your performance and use Machine Learning to forecast the index movement in the near future.

Continue reading

Guided Project

Machine Learning

319 Enrolled
(58)

At a Glance

How to easily use SARIMAX models to forecast your portfolio? At least $1 billion of client funds are missing at failed crypto firm FTX, and their FTX token has lost most of its value. How would you prevent your portfolio from having massive losses in a black swan event? This guided project will show you how to create your portfolio index that contains diverse cryptocurrencies to track your performance and use Machine Learning to forecast the index movement in the near future.

About

You are a seasoned investor who often uses Ethereum to purchase NFT on Opensea. You also think it is better not to put all your money in the same cryptocurrency; therefore, you decide to put your money in 8 different cryptocurrencies, like an ETF. Since the end of 2019, your portfolio has been doing great. Yet the economy has recently been heading into recession, and you want to know how to track your portfolio trends efficiently.

This tutorial will teach you step by step how to handle the datasets you find on internet to make it proper time series data and help you understand the cleaning of time series data and how the big financial companies create popular indexes like the S&P 500 or Nasdaq to track the industry. The project will also guide you how to determine what other critical external factors will influence your portfolio. You will use  ARIMA and SARIMAX models to predict your custom index performance. You will practice with the examples from Coincodex and United States Department of the Treasury.




A Look at the Project Ahead

After completing this guided project you will be able of:



  • Understand the basic knowledge of time series
  • Know your time series data and make raw data into a clean and prepared form
  • Understand the index formation
  • Create your own index
  • Understand the training process of time series
  • Apply ARIMA and SARIMAX models to forecast time series

What You'll Need

This project mainly uses Python and JupyterLabs to process the time series data, and we recommend you review the concepts of  before starting. Yet, we welcome everyone with no prior experience to enjoy this guided project.

WARNING: THIS GUIDED PROJECT IS NOT FINANCIAL ADVICE
The information contained on this Website and the resources available for download through this website is not intended as, and shall not be understood or construed as, financial advice. The information contained on this Website is not a substitute for financial advice from a professional who is aware of the facts and circumstances of your individual situation.

Frequently Asked Questions

  • Do I need to install any software to participate in this project?
    Everything you need to complete this project will be provided to you via the Skills Network Labs and it will all be available via a standard web browser.



  • What web browser should I use?
    The Skills Network Labs platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Estimated Effort

30 Minute

Level

Beginner

Industries

Financial Services

Skills You Will Learn

Machine Learning, Python, Financial Investment, Data Science, time series

Language

English

Course Code

GPXX0R8TEN

Released

January 18, 2023

Last Updated

January 31, 2023

Tell Your Friends!

Saved this page to your clipboard!

Instructors

Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

Read more

Sheng-Kai Chen

Data Scientist

Sheng-Kai Chen is a graduate student at the University of Toronto, concentrating on Information Systems & Design. Having several experiences analyzing data for retail stores and designing small software for small businesses. Sheng-Kai was inspired to shift toward answering new challenges with machine learning and new technics.

Read more