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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
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 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

Finding the optimal capital structure

Now, we can start analyzing how much equity and debt capital we should raise in the capital market to support demand (new projects and businesses or by replacing existing machinery that is worn out or obsolete) and supply (generated from profit). Our projection of optimal capital structure is time-bound; that is, it concerns the optimal mix for a given period, such as the next year. We can certainly expand it to cover the next 5 years. The formula used to forecast business performance is as follows:

Revenue growth * Fixed Capital Required / Sales

The optimal capital structure is the capital structure that delivers the lowest possible cost of funding but delivers the required capital to generate values within the firm.

Implementation steps

In this section, we will learn how to implement a machine learning model that can find the optimal capital structure that delivers the lowest possible cost...

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