Table Of ContentTheoretical
Foundations for
Quantitative Finance
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Theoretical
Foundations for
Quantitative Finance
Luca Spadafora
Università Cattolica del Sacro Cuore, Italy
Gennady P Berman
Los Alamos National Laboratory, USA & New Mexico Consortium, USA
World Scientific
NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TAIPEI • CHENNAI • TOKYO
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Published by
World Scientific Publishing Co. Pte. Ltd.
5 Toh Tuck Link, Singapore 596224
USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601
UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE
Library of Congress Cataloging-in-Publication Data
Names: Spadafora, Luca, author. | Berman, Gennady P., 1946– author.
Title: Theoretical foundations for quantitative finance / by Luca Spadafora,
Università Cattolica del Sacro Cuore, Italy, Gennady P. Berman,
Los Alamos National Laboratory, USA & New Mexico Consortium, USA.
Description: New Jersey : World Scientific, [2017] |
Includes bibliographical references and index.
Identifiers: LCCN 2016055368 | ISBN 9789813202474 (hc : alk. paper)
Subjects: LCSH: Finance--Mathematical models. | Investments--Mathematical models.
Classification: LCC HG106 .S628 2017 | DDC 332.01/5195--dc23
LC record available at https://lccn.loc.gov/2016055368
British Library Cataloguing-in-Publication Data
A catalogue record for this book is available from the British Library.
Copyright © 2017 by World Scientific Publishing Co. Pte. Ltd.
All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means,
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Preface
The last decade was characterized by several financial crises that
dramaticallychangedthewholefinancialframework,thebehaviorofmarket
participants and, in general, the perception of financial investments. As a
consequenceofthissortofrevolution,differentcornerstonesofthe classical
QuantitativeFinance (QF)frameworkhavebeenchangedby moremodern
approaches that can better describe such a different financial system.
ThisbookpresentsboththeclassicalandmodernQFtopicsinaunified
framework.Itdiscusseswhichoftheoldparadigmsarestillvalidinthisnew
financial worldand which havebeen reformulated.This coherentintroduc-
tion to modern QF theory is addressed to readers with a strong quantita-
tive backgroundwho seek to become employedinthis fieldasQuantitative
Analysts(orQuants)andtoactivepractitionersinterestedinreviewingthe
recent changes in QF.
The book deals with quite a wide class of models, ranging from the
rational pricing of financial derivatives to quantitative risk estimation. For
this reason, it is a broadintroduction in the sense that it is not focused on
a particular topic, but aims to summarize the technical tools required in a
wide range of QF topics. The applications described in the book, although
close to professional models, should be regarded as summaries of concepts
thatshowhowamathematicaltoolcanbeexploitedinpracticalsituations.
For this reason, this book is well suited for junior professionals who want
v
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vi Preface
to learn more advanced topics that can be utilized in a variety of practical
situations during their future careers.
Ontheotherside,thisbookdoesnotdealwithissuesrelatedtooptimal
investmentstrategiesandtheforecastingoffinancialtrends,evenifwethink
that most of the mathematical tools and models described in the book can
be considered as a good starting point for these kinds of applications.
Most of the topics in this book are derived from the lectures of a QF
coursegivenbyoneoftheauthorstograduatestudentsatCatholicUniver-
sityofthe SacredHeart,DepartmentofMathematics,PhysicsandNatural
Sciences,Italy;examplescomefrompracticalexperienceinthemainItalian
banks.
The authors gratefully acknowledge the assistance of E. Benzi,
G. D. Doolen, M. Dubrovich, G. Giusteri, A. Marziali, A. Pallavicini,
N. Picchiotti, A. Spuntarelli and M. Terraneo, who carefully reviewed the
manuscriptandprovidedmanycorrectionsandsuggestionsforitsimprove-
ment. The authors thank N. Balduzzi for providing the illustrations.
Any remaining flaws are the responsibility of the authors.
L. Spadafora and G. P. Berman
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Contents
Preface v
Chapter 1. Introduction 1
Chapter 2. All the Financial Math You Need to Survive
with Interesting Applications 5
2.1 Introduction. . . . . . . . . . . . . . . . . . . . . 5
2.2 Probability Space . . . . . . . . . . . . . . . . . . 5
2.2.1 Probability Measure and Random
Variables . . . . . . . . . . . . . . . . . . 8
2.2.2 The Information Flow Through Time:
The Role of the Filtration . . . . . . . . 11
2.3 How to Estimate a Random Variable —
Expectations and Conditioning . . . . . . . . . . 13
2.4 Main Features of Probability Measure . . . . . . 19
2.5 Moments and Cumulants . . . . . . . . . . . . . 21
2.6 Statistical Estimators . . . . . . . . . . . . . . . 24
2.7 Probability Density Functions . . . . . . . . . . . 25
2.7.1 Uniform Distribution . . . . . . . . . . . 26
2.7.2 Bernoulli and Binomial
Distributions . . . . . . . . . . . . . . . . 27
2.7.3 Normal Distribution . . . . . . . . . . . . 28
vii
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viii Contents
2.7.4 Empirical Distribution . . . . . . . . . . 28
2.7.5 Exponential Distribution and Student’s
t-Distribution . . . . . . . . . . . . . . . 33
2.8 Central Limit Theorem . . . . . . . . . . . . . . 34
2.9 Stochastic Processes . . . . . . . . . . . . . . . . 37
2.10 Brownian Motion . . . . . . . . . . . . . . . . . . 39
2.11 Quadratic Variation . . . . . . . . . . . . . . . . 42
2.12 Martingale . . . . . . . . . . . . . . . . . . . . . 43
2.13 Stochastic Differential Equations (SDEs) . . . . . 44
2.14 Itoˆ’s Lemma. . . . . . . . . . . . . . . . . . . . . 47
2.15 Some Very Useful Theorems . . . . . . . . . . . . 50
2.15.1 Martingale Representation Theorem . . . 50
2.15.2 Feynman–Kac Theorem . . . . . . . . . . 52
2.15.3 Radon–Nikodym Theorem . . . . . . . . 53
2.15.4 Girsanov’s Theorem . . . . . . . . . . . . 55
Chapter 3. The Pricing of Financial Derivatives —
The Replica Approach 59
3.1 Introduction — The Pricing of Financial
Derivatives . . . . . . . . . . . . . . . . . . . . . 59
3.2 What Kind of Model are We Looking For?. . . . 60
3.2.1 Coherence of the Pricing
Methodology . . . . . . . . . . . . . . . . 61
3.2.2 Hedging Strategies. . . . . . . . . . . . . 63
3.3 Are We Able to do the Same?
Replica Pricing . . . . . . . . . . . . . . . . . . . 63
3.3.1 Bank Account . . . . . . . . . . . . . . . 66
3.3.2 Self-Financing Strategies . . . . . . . . . 70
3.3.3 Arbitrage . . . . . . . . . . . . . . . . . . 72
3.3.4 Replica Examples . . . . . . . . . . . . . 74
3.3.4.1 Zero Coupon Bond . . . . . . . 75
3.3.4.2 Depo Rates . . . . . . . . . . . 77
3.3.4.3 Forward . . . . . . . . . . . . . 77
3.3.4.4 Forward Rate Agreement . . . 79
3.4 Derivatives: Call, Put and Digital Options . . . . 82
Chapter 4. Risk-Neutral Pricing 87
4.1 Introduction. . . . . . . . . . . . . . . . . . . . . 87
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Contents ix
4.1.1 Setting the Stage . . . . . . . . . . . . . 89
4.1.2 Point One: Modeling the
Underlying . . . . . . . . . . . . . . . . . 91
4.1.3 Point Two: Guess a Pricing
Formula . . . . . . . . . . . . . . . . . . 92
4.1.4 Point Three: Finding an Equivalent
Martingale Measure . . . . . . . . . . . . 94
4.1.5 Point Four: Defining the Replica
Strategy . . . . . . . . . . . . . . . . . . 96
4.1.6 Point Five: The Pricing Algorithm. . . . 98
Chapter 5. The Black and Scholes Framework and Its Extensions 101
5.1 Black–Scholes Model — Part I . . . . . . . . . . 101
5.2 BS Model — Part II —
Girsanov is Back . . . . . . . . . . . . . . . . . . 106
5.3 Put–Call Parity . . . . . . . . . . . . . . . . . . . 107
5.4 Implied Volatility and the Calibration
Problem . . . . . . . . . . . . . . . . . . . . . . . 109
5.5 Digital Options . . . . . . . . . . . . . . . . . . . 115
5.6 Change of Numeraire. . . . . . . . . . . . . . . . 118
5.6.1 The Forward Measure . . . . . . . . . . . 122
5.7 Greeks . . . . . . . . . . . . . . . . . . . . . . . . 124
5.8 Heston Model . . . . . . . . . . . . . . . . . . . . 130
5.8.1 Incomplete Markets . . . . . . . . . . . . 130
5.8.2 Heston Model Equations . . . . . . . . . 131
5.8.3 Heston Risk Neutral Model . . . . . . . . 132
5.8.4 Heston Pricing Formula . . . . . . . . . . 134
5.8.5 Heston Implied Volatility . . . . . . . . . 136
Chapter 6. Risk Modeling 139
6.1 Introduction. . . . . . . . . . . . . . . . . . . . . 139
6.2 Risk? What is Risk? . . . . . . . . . . . . . . . . 140
6.3 What Kind of Model are You Looking For? . . . 140
6.4 Risk Measures: Value-at-Risk and Expected
Shortfall . . . . . . . . . . . . . . . . . . . . . . . 142
6.4.1 Some Caveats on VaR Estimation . . . . 146
6.4.1.1 Percentile Estimation. . . . . . 147
6.4.1.2 VaR Statistical Error . . . . . . 155
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x Contents
6.5 Real-World Measure . . . . . . . . . . . . . . . . 156
6.6 Market Risk Estimation . . . . . . . . . . . . . . 158
6.6.1 Historical Method . . . . . . . . . . . . . 163
6.6.2 Parametric Method . . . . . . . . . . . . 166
6.6.3 Monte Carlo Method . . . . . . . . . . . 171
6.7 Does it Really Work? The Backtesting
Approach . . . . . . . . . . . . . . . . . . . . . . 172
6.8 From Theory to Practice. . . . . . . . . . . . . . 177
Chapter 7. The New Post-Crisis Paradigms 181
7.1 The Financial World After Financial Crisis . . . 181
7.2 Multi-Curve Framework . . . . . . . . . . . . . . 183
7.3 Fair Value Adjustments . . . . . . . . . . . . . . 187
7.3.1 Credit Value Adjustment . . . . . . . . . 187
7.4 Counterparty Credit Risk . . . . . . . . . . . . . 192
Appendix 199
A.1 Black–Scholes Pricing Formula Derivation —
Risk-Neutral Approach. . . . . . . . . . . . . . . 199
A.2 Delta Formula for Call Options . . . . . . . . . . 202
A.3 Heston Model Pricing Formula Derivation . . . . 203
Bibliography 207
Index 211
