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.

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.

What this book covers

Chapter 1, Quantum Computing Paradigm, helps readers understand the challenges and limitations of digital technology and how quantum computing can help them overcome these.

Chapter 2, Quantum Machine Learning and Optimization Algorithms, considers how quantum machine learning utilizes qubits and quantum operations for specialized quantum systems to improve computational speed and data storage. This is done by algorithms in a program. This chapters explain how the quantum machine learning algorithm works in theory and in real life.

Chapter 3, Quantum Finance Landscape, helps readers understand the quantum finance landscape and the types of financial problems to which quantum computing principles can be applied.

Chapter 4, Derivatives Valuation, highlights that the valuation of derivatives is often highly complex and can only be carried out numerically—which requires a correspondingly high computing effort. This chapter examines the role of QML algorithms in derivatives valuation.

Chapter 5, Portfolio Optimization, considers portfolio management as the process of managing a group of financial securities and making ongoing decisions to meet investment objectives. Portfolio management also includes a number of steps, such as managing costs and risks, allocating assets, researching the market, and choosing securities. This chapter examines the role of QML algorithms in portfolio allocation.

Chapter 6, Credit Risk Analytics, outlines how credit risk is associated with the possibility of a client failing to meet contractual obligations, such as mortgages, credit card debts, and other types of loans. Minimizing the risk of default is a major concern for financial institutions. Machine learning models have been helping these companies to improve the accuracy of their credit risk analysis, providing a scientific method to identify potential debtors in advance. Learn how a QML algorithm can help solve this problem using real-world data.

Chapter 7, Implementation in Quantum Clouds, dicusses how the implementation of quantum machine learning and optimization architectures in productive environments, or as a backtest for current systems, is a crucial part to retrieve knowledge and start using this technology.

Chapter 8, Simulators’ and HPCs’ roles in the NISQ Era, highlights how classical means and in particular, high-performance hardware, have a key part to play in the delivery of short-term quantum advantage. In this chapter, we will explore some of the most relevant approaches in order to map the quantum-classical landscape comprehensively.

Chapter 9, NISQ Quantum Hardware Roadmap, demonstrates how Noisy Intermediate-Scale Quantum (NISQ) Hardware can evolve in various ways depending on the provider. Different approaches, ranging from fault-tolerant logical qubits to circuit knitting, could be among the early steps towards achieving fault-tolerant devices. In this chapter, we outline the key aspects of these approaches and their long-term potential.

Chapter 10, Business Implementation, underlines that knowing quantum technology does not guarantee that companies will successfully implement quantum computing with the lowest risk possible. In this chapter, we will provide helpful information for how fintech firms and banks can implement these kinds of projects without getting stuck half-way.

To get the most out of this book

Software/hardware covered in the book	Operating system requirements
Python	Windows, macOS, or Linux
Jupyter notebook	Windows, macOS, or Linux
Dwave Leap	Windows, macOS, or Linux
AWS Braket	Windows, macOS, or Linux
Azure	Windows, macOS, or Linux

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Financial-Modeling-using-Quantum-Computing. If there’s an update to the code, it will be updated in the GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots and diagrams used in this book. You can download it here: https://packt.link/1xxSu.

Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: “Mount the downloaded WebStorm-10*.dmg disk image file as another disk in your system.”

A block of code is set as follows:

import numpy as np 
from scipy.stats import norm 
t = 1.0 # year 
K = 105 # Strike price 
r = 0.05 # Riskless short rate 
sigma = 0.25 # Volatility (stdev) 
S0 = 100 # Present price

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

[default]
exten => s,1,Dial(Zap/1|30)
exten => s,2,Voicemail(u100)
exten => s,102,Voicemail(b100)
exten => i,1,Voicemail(s0)

Any command-line input or output is written as follows:

$ mkdir css
$ cd css

Bold: Indicates a new term, an important word, or words that you see onscreen. For instance, words in menus or dialog boxes appear in bold. Here is an example: “Select System info from the Administration panel.”

Tips or important notes

Appear like this.

Get in touch

Feedback from our readers is always welcome.

General feedback: If you have questions about any aspect of this book, email us at [e-mail] and mention the book title in the subject of your message.

Errata: Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you have found a mistake in this book, we would be grateful if you would report this to us. Please visit www.packtpub.com/support/errata and fill in the form.

Piracy: If you come across any illegal copies of our works in any form on the internet, we would be grateful if you would provide us with the location address or website name. Please contact us at [e-mail] with a link to the material.

If you are interested in becoming an author: If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, please visit authors.packtpub.com.

Share Your Thoughts

Once you’ve read Financial Modeling using Quantum Computing, we’d love to hear your thoughts! Scan the QR code below to go straight to the Amazon review page for this book and share your feedback.

https://packt.link/r/1-804-61842-X

Your review is important to us and the tech community and will help us make sure we’re delivering excellent quality content.

Download a free PDF copy of this book

Thanks for purchasing this book!

Do you like to read on the go but are unable to carry your print books everywhere?
Is your eBook purchase not compatible with the device of your choice?

Don’t worry, now with every Packt book you get a DRM-free PDF version of that book at no cost.

Read anywhere, any place, on any device. Search, copy, and paste code from your favorite technical books directly into your application.

The perks don’t stop there, you can get exclusive access to discounts, newsletters, and great free content in your inbox daily

Follow these simple steps to get the benefits:

1. Scan the QR code or visit the link below

https://packt.link/free-ebook/9781804618424

2. Submit your proof of purchase
3. That’s it! We’ll send your free PDF and other benefits to your email directly