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Quantum Machine Learning and Optimisation in Finance

You're reading from Quantum Machine Learning and Optimisation in Finance Drive financial innovation with quantum-powered algorithms and optimisation strategies

Product type Paperback

Published in Dec 2024

Publisher Packt

ISBN-13 9781836209614

Length 494 pages

Edition 2nd Edition

Languages

Python

Tools

Quantum Development Kit

Concepts

Quantum Computing

Authors (2):

Jacquier Antoine

Alexei Kondratyev

View More author details

Table of Contents (21) Chapters

Preface

1. Chapter 1 The Principles of Quantum Mechanics FREE CHAPTER

2. Part I Analog Quantum Computing – Quantum Annealing

3. Chapter 2 Adiabatic Quantum Computing

4. Chapter 3 Quadratic Unconstrained Binary Optimisation

5. Chapter 4 Quantum Boosting

6. Chapter 5 Quantum Boltzmann Machine

7. Part II Gate Model Quantum Computing

8. Chapter 6 Qubits and Quantum Logic Gates

9. Chapter 7 Parameterised Quantum Circuits and Data Encoding

10. Chapter 8 Quantum Neural Network

11. Chapter 9 Quantum Circuit Born Machine

12. Chapter 10 Variational Quantum Eigensolver

13. Chapter 11 Quantum Approximate Optimisation Algorithm

14. Chapter 12 Quantum Kernels and Quantum Two-Sample Test

15. Chapter 13 The Power of Parameterised Quantum Circuits

16. Chapter 14 Advanced QML Models

17. Chapter 15 Beyond NISQ

18. Bibliography

19. Index

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This book is intended as an in-depth introduction to the power of quantum computing techniques for quantitative finance problems. While it is designed to be self-contained, this book assumes that the reader has some familiarity with basic mathematical concepts in algebra, analysis, and computing. Knowledge of quantum mechanics is not required, and the main tools thereof shall be explained and made accessible to non-physicists.

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Authors (2)

Jacquier Antoine

Jacquier Antoine

Antoine Jacquier obtained his PhD in 2010 in Mathematics from Imperial College London, where his research was focused on large deviations and asymptotic methods for stochastic volatility. Over the past 10 years, he has been working on stochastic analysis and volatility modelling, publishing about 50 papers and co-writing several books. He is also the Head of the MSc in Mathematics and Finance at Imperial College and regularly works as a quantitative consultant for the Finance industry.

See other products by Jacquier Antoine

Alexei Kondratyev

Alexei Kondratyev

Oleksiy Kondratyev obtained his PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine, where his research was focused on studying phase transitions in quantum lattice systems. Oleksiy has over 20 years of quantitative finance experience, primarily in banking. He was recognised as Quant of the Year 2019 by Risk magazine and joined Abu Dhabi Investment Authority as a Quantitative Research & Development Lead in the summer of 2021.

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