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Hands-On Artificial Intelligence for Banking

You're reading from  Hands-On Artificial Intelligence for Banking

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781788830782
Pages 240 pages
Edition 1st Edition
Languages
Authors (2):
Jeffrey Ng Jeffrey Ng
Profile icon Jeffrey Ng
Subhash Shah Subhash Shah
Profile icon Subhash Shah
View More author details

Table of Contents (14) Chapters

Preface 1. Section 1: Quick Review of AI in the Finance Industry
2. The Importance of AI in Banking 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

Sensing market requirements using sentiment analysis

One of the key requirements of a security firm/investment bank on the sell side is to manufacture the relevant securities for the market. We have explored the fundamental behaviors and responsibilities of companies in Chapter 4, Mechanizing Capital Market Decisions, and Chapter 5, Predicting the Future of Investment Bankers. We learned about the momentum approach in Chapter 6, Automated Portfolio Management Using the Treynor–Black Model and ResNet. While the market does not always act rationally, it could be interesting to hear about the market's feelings. That is what we will be doing in this chapter.

In this example, we will be playing the role of the salesperson of an investment bank on the trading floor, trading in equities. What we want to find out is the likes and dislikes regarding securities so that they can market the relevant securities, including derivatives. We got our insights from Twitter Search...

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