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Financial Modeling Using Quantum Computing

Financial Modeling Using Quantum Computing

By : Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere
5 (8)
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Financial Modeling Using Quantum Computing

Financial Modeling Using Quantum Computing

5 (8)
By: Anshul Saxena, Javier Mancilla, Iraitz Montalban, Christophe Pere

Overview of this book

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.
Table of Contents (16 chapters)
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Part 1: Basic Applications of Quantum Computing in Finance
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Chapter 2: Quantum Machine Learning Algorithms and Their Ecosystem
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Part 2: Advanced Applications of Quantum Computing in Finance
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Part 3: Upcoming Quantum Scenario
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Chapter 8: Simulators and HPC’s Role in the NISQ Era
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Index
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Preface

Welcome to the fascinating world of financial modeling through the lens of quantum computing. This book seeks to offer an enlightening exploration into the uncharted territory of quantum computing applications in the financial realm. Our journey begins with a comprehensive understanding of digital technology’s limitations and how quantum computing serves to transcend these boundaries.

Within these pages, we delve into the nuances of Quantum Machine Learning (QML) and how its unique attributes can be harnessed to revolutionize various aspects of financial modeling. We will explore derivatives valuation, portfolio management, and credit risk analysis, laying bare the transformative potential of QML algorithms in these areas.

However, as with any technological implementation, simply understanding quantum technology doesn’t ensure smooth sailing. Thus, this book also provides guidance on how institutions such as fintech firms and banks can navigate these project implementations, minimizing risks and ensuring successful, uninterrupted execution.

This book also elucidates the role of classical means and high-performance hardware in achieving a short-term quantum advantage. It further explores the potential evolution of noisy intermediate-scale hardware based on different provider strategies, emphasizing its long-term implications.

We have curated this material based on years of research and experience in quantum technology and financial modeling. The insights you will find here are the result of comprehensive research and extensive interviews with industry experts leading the field of quantum finance.

As per recent reports, quantum computing is poised to revolutionize the financial industry. As more institutions adopt this technology and the complexity of the financial models increase, understanding and successfully implementing quantum computing strategies will become a necessity rather than an option. This book aims to guide you through this transition, preparing you for the quantum leap in financial modeling.

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