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Robo-Advisor with Python

You're reading from   Robo-Advisor with Python A hands-on guide to building and operating your own Robo-advisor

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781801819695
Length 250 pages
Edition 1st Edition
Languages
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Author (1):
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Aki Ranin Aki Ranin
Author Profile Icon Aki Ranin
Aki Ranin
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Table of Contents (22) Chapters Close

Preface 1. Part 1: The Basic Elements of Robo-Advisors
2. Chapter 1: Introduction to Robo-Advisors FREE CHAPTER 3. Chapter 2: What Makes Up a Robo-Advisor? 4. Chapter 3: Robo-Advisor Platforms versus Algorithms 5. Chapter 4: Leasing, Buying, or Building Your Own Robo-Advisor 6. Part 2: Building Your Own Robo-Advisor
7. Chapter 5: Basic Setup and Requirements for Building a Robo-Advisor 8. Chapter 6: Goal-Based Investing 9. Chapter 7: Risk Profiling and Scoring 10. Chapter 8: Model Portfolio Construction 11. Chapter 9: Investment Projections 12. Chapter 10: Account Opening and KYC 13. Chapter 11: Funding Your Account 14. Chapter 12: Order Management and Execution 15. Part 3: Running and Operating Your Own Robo-Advisor
16. Chapter 13: Performance Reporting 17. Chapter 14: Rebalancing 18. Chapter 15: Dividends and Fee Management 19. Chapter 16: Regulations for Robo-Advisors 20. Index 21. Other Books You May Enjoy

Key concepts in risk profiling and scoring

Following from what we established in Chapter 2, What Makes Up a Robo-Advisor?, the fundamental basis of Robo-advisors is Markowitz’s Modern Portfolio Theory (MPT). This isn’t to say that it is impossible to avoid MPT, but that in most countries, the regulations set by the government for oversight of financial services dictate the usage of at least certain aspects and assumptions of MPT.

One of those assumptions is that investors should only take more risk in return for more rewards or higher returns. This means we need a way to gauge how much variance and volatility the investors are willing to endure in order to achieve a desired investment return. One such approach would be simply asking that exact question in numerical terms, but in reality, that isn’t viable for most investors to answer rationally. Therefore, the industry practice has defined proxies for risk in the form of risk tolerance and risk capacity. These...

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