Ignacio Ruiz - Machine Learning for Risk Calculations: A Practitioners View

1. Chapter 1
2. Chapter 12
3. Chapter 14
4. Chapter 15
5. Chapter 16
6. Chapter 17
7. Chapter 18
8. Chapter 19
9. Chapter 20
10. Appendix D
11. Appendix E
12. Appendix F
13. Appendix G

1. Chapter 1
2. Chapter 2
3. Chapter 3
4. Chapter 4
5. Chapter 5
6. Chapter 6
7. Chapter 8
8. Chapter 10
9. Chapter 12
10. Chapter 14
11. Chapter 15
12. Chapter 16
13. Chapter 17
14. Chapter 18
15. Chapter 19
16. Chapter 20
17. Chapter 21
18. Chapter 23
19. Appendix B
20. Appendix C
21. Appendix F
22. Appendix G

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I. RUIZ

M. ZERON

Foreword by P. Karasinski

This edition first published 2021

Copyright 2022 by Ignacio Ruiz and Mariano Zeron. All rights reserved.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by law. Advice on how to obtain permission to reuse material from this title is available at http://www.wiley.com/go/permissions.

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Library of Congress Cataloging-in-Publication Data

Names: Ruiz, Ignacio, 1972- author. | Laris, Mariano Zeron Medina, author.

Title: Machine learning for risk calculations : a practitioner's view / Ignacio Ruiz, Mariano Zeron Medina Laris.

Description: Hoboken, New Jersey : Wiley, [2022] | Includes index.

Identifiers: LCCN 2021036694 (print) | LCCN 2021036695 (ebook) | ISBN 9781119791386 (hardback) | ISBN 9781119791393 (adobe pdf) | ISBN 9781119791409 (epub)

Subjects: LCSH: Machine learning. | Financial risk management.

Classification: LCC Q325.5 .R855 2022 (print) | LCC Q325.5 (ebook) | DDC 332.10285/631dc23

LC record available at https://lccn.loc.gov/2021036694

LC ebook record available at http://lccn.loc.gov/2021036695

Cover image: korkeng/Shutterstock

Cover design: Wiley

To my sister Cristina, a beautiful soul around us, an inspiration in my life.

To my parents, for their unwavering support.

This book has been significantly benefited from the support and input of a whole range of individuals whom we want to thank. In particular, we would like to thank our friend Emilio Videz, who directly contributed to many of the chapters in this book. Most importantly, he has been an extraordinary companion in the journey of which this book is one of the results.

We would also like to thank (in no particular order of importance) Jesus Alonso, Andrew Aziz, Dimitra Bampou, Russell Barker, Assad Bouayoun, Juan Antonio Burgos, Paul Burnett, Pablo Cassatella, Justin Chan, Lucia Cipolina, Alex Daminoff, Matthew Dear, Piero Del Boca, Thomas Devereux, Alberto Elices, Eduardo Epperlein and his group at NOMURA, Andrew Green, Stephen Hancock, Brian Huge, Marc Jeannin, Akshay Jha, Paul Jones, Christian Kappen, Piotr Karasinski, Gordon Lee, Udit Mahajan, Navneet Mathur, Adolfo Montoro, Cesar Mora, Rubn Moral, Yacine Moulay-Rchid, Laura Mller, Stuart Neil, Maria Nogueiras, Yogi Patel, Jose Mara Pesquero, Maxim Petrashev, Carlos Rioja, Samir Saurav, Joaqun Seco, Naimish Shah, Anton Simanenka, Jono Simpson, Takis Sironis, John Sleath, Robert Smith, Theo Stampoulis, Lauri Tamminen, Alok Tiwari, Alessandro Vecci, Satya Vemireddy and Hernan Ziga for the time and patience they had with us in different occasions.

The reader can find further resources on the topics of this book at

mocaxintelligence.org

and on the YouTube channel

youtube.com/mocax

I met Mariano and Ignacio at the Quantitative Finance 2019 Rome conference. Mariano gave a presentation on the joint work with Ignacio on the Chebyshev Tensors techniques for CVA pricing and FRTB capital. After the talk I went to speak to Mariano, as I had found the results he had shown quite remarkable. That was the beginning of my productive relationship with both of them.