Financial Modeling Using Quantum Computing

Part 1: Basic Applications of Quantum Computing in Finance
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Part 1: Basic Applications of Quantum Computing in Finance
Chapter 1: Quantum Computing Paradigm
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Chapter 1: Quantum Computing Paradigm
The evolution of quantum technology and its related paradigms
Basic quantum mechanics principles and their application
The business application of quantum computing
Summary
Chapter 2: Quantum Machine Learning Algorithms and Their Ecosystem
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Chapter 2: Quantum Machine Learning Algorithms and Their Ecosystem
Technical requirements
Foundational quantum algorithms
QML algorithms
Quantum programming
Quantum clouds
Summary
References
Chapter 3: Quantum Finance Landscape
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Chapter 3: Quantum Finance Landscape
Introduction to types of financial institutions
Key problems in financial services
Summary
Further reading
References
Part 2: Advanced Applications of Quantum Computing in Finance
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Part 2: Advanced Applications of Quantum Computing in Finance
Chapter 4: Derivative Valuation
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Chapter 4: Derivative Valuation
Derivatives pricing – the theoretical aspects
Machine learning
Quantum computing
Summary
Further reading
References
Chapter 5: Portfolio Management
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Chapter 5: Portfolio Management
Financial portfolio management
Financial portfolio diversification
Financial portfolio simulation
Portfolio management using traditional machine learning algorithms
Quantum algorithm portfolio management implementation
Conclusion
Chapter 6: Credit Risk Analytics
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Chapter 6: Credit Risk Analytics
The relevance of credit risk analysis
Data exploration and preparation to execute both ML and QML models
Implementation of classical and quantum machine learning algorithms for a credit scoring scenario
Quantum Support Vector Machines
Conclusion
Further reading
Chapter 7: Implementation in Quantum Clouds
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Chapter 7: Implementation in Quantum Clouds
Challenges of quantum implementations on cloud platforms
Cost estimation
Summary
Further reading
References
Part 3: Upcoming Quantum Scenario
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Part 3: Upcoming Quantum Scenario
Chapter 8: Simulators and HPC’s Role in the NISQ Era
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Chapter 8: Simulators and HPC’s Role in the NISQ Era
Local simulation of noise models
Summary
Further reading
References
Chapter 9: NISQ Quantum Hardware Roadmap
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Chapter 9: NISQ Quantum Hardware Roadmap
Logical versus physical qubits
Circuit knitting
Error mitigation
Annealers and other devices
Summary
Further reading
References
Chapter 10: Business Implementation
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Chapter 10: Business Implementation
The quantum workforce barrier
Infrastructure integration barrier
Identifying the potentiality of advantage with QML
Funding or budgeting issues
Market maturity, hype, and skepticism
Road map for early adoption of quantum computing for financial institutions
Quantum managers’ training
Conclusions
References
Index
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Index
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