Financial Modeling Using Quantum Computing
Design and manage quantum machine learning solutions for financial analysis and decision making
- 292 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Financial Modeling Using Quantum Computing
Design and manage quantum machine learning solutions for financial analysis and decision making
About this book
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.
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Information
Table of contents
- Financial Modeling Using Quantum Computing
- Contributors
- Preface
- Part 1: Basic Applications of Quantum Computing in Finance
- 1
- 2
- 3
- Part 2: Advanced Applications of Quantum Computing in Finance
- 4
- 5
- 6
- 7
- Part 3: Upcoming Quantum Scenario
- 8
- 9
- 10
- Index
- Other Books You May Enjoy