Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Artificial Intelligence for Banking

You're reading from   Hands-On Artificial Intelligence for Banking A practical guide to building intelligent financial applications using machine learning techniques

Arrow left icon
Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781788830782
Length 240 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (2):
Arrow left icon
Subhash Shah Subhash Shah
Author Profile Icon Subhash Shah
Subhash Shah
Jeffrey Ng Jeffrey Ng
Author Profile Icon Jeffrey Ng
Jeffrey Ng
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Section 1: Quick Review of AI in the Finance Industry
2. The Importance of AI in Banking FREE CHAPTER 3. Section 2: Machine Learning Algorithms and Hands-on Examples
4. Time Series Analysis 5. Using Features and Reinforcement Learning to Automate Bank Financing 6. Mechanizing Capital Market Decisions 7. Predicting the Future of Investment Bankers 8. Automated Portfolio Management Using Treynor-Black Model and ResNet 9. Sensing Market Sentiment for Algorithmic Marketing at Sell Side 10. Building Personal Wealth Advisers with Bank APIs 11. Mass Customization of Client Lifetime Wealth 12. Real-World Considerations 13. Other Books You May Enjoy

Understanding time series analysis

A time series is technically defined as the ordered sequence of values of a variable captured over a uniformly spaced time interval. Put simply, it is the method of capturing the value of a variable at specific time intervals. It can be 1 hour, 1 day, or 20 minutes. The captured values of a variable are also known as data points. Time series analysis is performed in order to understand the structure of the underlying sources that produced the data. It is also used in forecasting, feedforward control, monitoring, and feedback. The following is a list of some of the known applications of time series analysis:

  • Utility studies
  • Stock market analysis
  • Weather forecasting
  • Sales projections
  • Workload scheduling
  • Expenses forecasting
  • Budget analysis

Time series analysis is achieved by applying various analytical methods to extract meaningful information from raw...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image