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Financial Modeling Using Quantum Computing Cover

Financial Modeling Using Quantum Computing

Design and manage quantum machine learning solutions for financial analysis and decision making

Publisher:Packt Publishing Limited
By: ,  ,   and    
Paid access
|May 2024
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Description

Achieve optimized solutions for real-world financial problems using quantum machine learning algorithms

Key Features

  • Learn to solve financial analysis problems by harnessing quantum power
  • Unlock the benefits of quantum machine learning and its potential to solve problems
  • Train QML to solve portfolio optimization and risk analytics problems

Book Description

Quantum computing has the potential to revolutionize the computing paradigm. By integrating quantum algorithms with artificial intelligence and machine learning, we can harness the power of qubits to deliver comprehensive and optimized solutions for intricate financial problems.
This book offers step-by-step guidance on using various quantum algorithm frameworks within a Python environment, enabling you to tackle business challenges in finance. With the use of contrasting solutions from well-known Python libraries with quantum algorithms, you’ll discover the advantages of the quantum approach. Focusing on clarity, the authors expertly present complex quantum algorithms in a straightforward, yet comprehensive way. Throughout the book, you'll become adept at working with simple programs illustrating quantum computing principles. Gradually, you'll progress to more sophisticated programs and algorithms that harness the full power of quantum computing.
By the end of this book, you’ll be able to design, implement and run your own quantum computing programs to turbocharge your financial modelling.

What you will learn

  • Explore framework, model and technique deployed for Quantum Computing
  • Understand the role of QC in financial modeling and simulations
  • Apply Qiskit and Pennylane framework for financial modeling
  • Build and train models using the most well-known NISQ algorithms
  • Explore best practices for writing QML algorithms
  • Use QML algorithms to understand and solve data mining problems

Who this book is for

This book is for financial practitioners, quantitative analysts, or developers; looking to bring the power of quantum computing to their organizations. This is an essential resource written for finance professionals, who want to harness the power of quantum computers for solving real-world financial problems. A basic understanding of Python, calculus, linear algebra, and quantum computing is a prerequisite.

Table of Contents

  1. Quantum Computing Paradigm
  2. Quantum Machine Learning Algorithms
  3. Quantum Finance Landscape
  4. Derivatives Valuation
  5. Portfolio Valuations
  6. Credit Risk Analytics
  7. Implementation in Quantum Clouds
  8. HPCs and Simulators Relevance
  9. NISQ Quantum Hardware Evolution
  10. Quantum Roadmap for Banks and Fintechs
https://github.com/PacktPublishing/Financial-Modeling-using-Quantum-Computing/tree/main
PDF ISBN: 978-1-80461-487-7
Publisher: Packt Publishing Limited
Copyright owner: © 2023 Packt Publishing Limited
Publication date: 2024
Language: English
Pages: 292
Related subjects:
Business and economics,
Political economics,
Political economics, other
BISAC subjects:
BUS027010,
COM027000,
BUS027020
Thema subjects:
KFF,
UFK,
GPQD

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