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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 Sentiment for Algorithmic Marketing at Sell Side

In the previous chapter, we learned about investment portfolio management. We also learned some of the portfolio management techniques, such as the Markowitz mean-variance model and the Treynor–Black model for portfolio construction. We also learned about how to predict a trend for a security. So, the previous chapter was based on the buy side of a market. It depicted the behavior of portfolio managers or asset managers.

In this chapter, we will look at the sell side of the market. We will understand the behavior of the counterpart of the portfolio managers. Sell side refers to securities firms/investment banks and their main services, including sales, trading, and research. Sales refers to the marketing of securities to inform investors about the securities available for selling. Trading refers to the services that investors use to buy and sell off...

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