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Financial Modeling Using Quantum Computing

You're reading from  Financial Modeling Using Quantum Computing

Product type Book
Published in May 2023
Publisher Packt
ISBN-13 9781804618424
Pages 292 pages
Edition 1st Edition
Authors (4):
Anshul Saxena Anshul Saxena
Profile icon Anshul Saxena
Javier Mancilla Javier Mancilla
Profile icon Javier Mancilla
Iraitz Montalban Iraitz Montalban
Profile icon Iraitz Montalban
Christophe Pere Christophe Pere
Profile icon Christophe Pere
View More author details

Table of Contents (16) Chapters

Preface 1. Part 1: Basic Applications of Quantum Computing in Finance
2. Chapter 1: Quantum Computing Paradigm 3. Chapter 2: Quantum Machine Learning Algorithms and Their Ecosystem 4. Chapter 3: Quantum Finance Landscape 5. Part 2: Advanced Applications of Quantum Computing in Finance
6. Chapter 4: Derivative Valuation 7. Chapter 5: Portfolio Management 8. Chapter 6: Credit Risk Analytics 9. Chapter 7: Implementation in Quantum Clouds 10. Part 3: Upcoming Quantum Scenario
11. Chapter 8: Simulators and HPC’s Role in the NISQ Era 12. Chapter 9: NISQ Quantum Hardware Roadmap 13. Chapter 10: Business Implementation 14. Index 15. Other Books You May Enjoy

Part 2: Advanced Applications of Quantum Computing in Finance

This section explores the role of Quantum Machine Learning (QML) in diverse financial domains. First, it unpacks how QML eases the complex task of derivatives valuation. Next, it investigates the potential of QML in redefining portfolio management, a process involving prudent financial decision-making. The analysis then moves to credit risk, where QML could help identify potential defaulters more accurately. Finally, it emphasizes the significance of the practical implementation of these quantum technologies in real-world environments.

This part has the following chapters:

  • Chapter 4, Derivatives Valuation
  • Chapter 5, Portfolio Valuations
  • Chapter 6, Credit Risk Analytics
  • Chapter 7, Implementation in Quantum Clouds
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