Risk-Neutral Valuation

Similar documents
Institute of Actuaries of India. Subject. ST6 Finance and Investment B. For 2018 Examinationspecialist Technical B. Syllabus

Interest Rate Modeling

Martingale Methods in Financial Modelling

Contents. Part I Introduction to Option Pricing

INTRODUCTION TO THE ECONOMICS AND MATHEMATICS OF FINANCIAL MARKETS. Jakša Cvitanić and Fernando Zapatero

Subject CT8 Financial Economics Core Technical Syllabus

Martingale Methods in Financial Modelling

Introduction to Stochastic Calculus With Applications

Fixed Income Modelling

Continuous-time Stochastic Control and Optimization with Financial Applications

Preface Objectives and Audience

Discrete-time Asset Pricing Models in Applied Stochastic Finance

Option Pricing under Delay Geometric Brownian Motion with Regime Switching

From Discrete Time to Continuous Time Modeling

Monte Carlo Methods in Financial Engineering

Financial Engineering MRM 8610 Spring 2015 (CRN 12477) Instructor Information. Class Information. Catalog Description. Textbooks

MSc Financial Mathematics

MSc Financial Mathematics

Mathematical Modeling and Methods of Option Pricing

ADVANCED ASSET PRICING THEORY

Curriculum. Written by Administrator Sunday, 03 February :33 - Last Updated Friday, 28 June :10 1 / 10

MODULE SPECIFICATIONS. Mathematical Methods of Finance (Online Version) Level M, Certificate Stage, 20 credits

Asset Pricing and Portfolio. Choice Theory SECOND EDITION. Kerry E. Back

MFE Course Details. Financial Mathematics & Statistics

FIXED INCOME SECURITIES

MFE Course Details. Financial Mathematics & Statistics

Computational Finance. Computational Finance p. 1

SYLLABUS. IEOR E4728 Topics in Quantitative Finance: Inflation Derivatives

STOCHASTIC MODELLING OF ELECTRICITY AND RELATED MARKETS

We discussed last time how the Girsanov theorem allows us to reweight probability measures to change the drift in an SDE.

MFIN 7003 Module 2. Mathematical Techniques in Finance. Sessions B&C: Oct 12, 2015 Nov 28, 2015

Financial Statistics and Mathematical Finance Methods, Models and Applications. Ansgar Steland

CHAPTER 2: STANDARD PRICING RESULTS UNDER DETERMINISTIC AND STOCHASTIC INTEREST RATES

1.1 Basic Financial Derivatives: Forward Contracts and Options

MFE/3F Questions Answer Key

AMSTERDAM BOSTON HEIDELBERG LONDON NEW YORK OXFORD PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO Academic Press is an Imprint of Elsevier

Martingale Methods in Financial Modelling

Table of Contents. Part I. Deterministic Models... 1

Bibliography. Principles of Infinitesimal Stochastic and Financial Analysis Downloaded from

Handbook of Financial Risk Management

FINANCIAL DERIVATIVE. INVESTMENTS An Introduction to Structured Products. Richard D. Bateson. Imperial College Press. University College London, UK

by Kian Guan Lim Professor of Finance Head, Quantitative Finance Unit Singapore Management University

Introduction to Bonds The Bond Instrument p. 3 The Time Value of Money p. 4 Basic Features and Definitions p. 5 Present Value and Discounting p.

Implementing Models in Quantitative Finance: Methods and Cases

Interest rate models in continuous time

Lecture 17. The model is parametrized by the time period, δt, and three fixed constant parameters, v, σ and the riskless rate r.

and K = 10 The volatility a in our model describes the amount of random noise in the stock price. Y{x,t) = -J-{t,x) = xy/t- t<pn{d+{t-t,x))

Fundamentals of Stochastic Filtering

MFE/3F Questions Answer Key

NEWCASTLE UNIVERSITY SCHOOL OF MATHEMATICS, STATISTICS & PHYSICS SEMESTER 1 SPECIMEN 2 MAS3904. Stochastic Financial Modelling. Time allowed: 2 hours

Enlargement of filtration

Markov Processes and Applications

Change of Measure (Cameron-Martin-Girsanov Theorem)

Springer Finance. Editorial Board. M. Avellaneda G. Barone-Adesi M. Broadie M.H.A. Davis E. Derman C. Klüppelberg E. Kopp W.

King s College London

Notes for Lecture 5 (February 28)

I Preliminary Material 1

Applied Stochastic Processes and Control for Jump-Diffusions

Statistics and Finance

European call option with inflation-linked strike

Financial and Actuarial Mathematics

Fractional Brownian Motion as a Model in Finance

How to Implement Market Models Using VBA

Hedging of Contingent Claims under Incomplete Information

Optimal Option Pricing via Esscher Transforms with the Meixner Process

Statistical Models and Methods for Financial Markets

MASM006 UNIVERSITY OF EXETER SCHOOL OF ENGINEERING, COMPUTER SCIENCE AND MATHEMATICS MATHEMATICAL SCIENCES FINANCIAL MATHEMATICS.

ICEF, Higher School of Economics, Moscow Msc Programme Autumn Derivatives

Fractional Brownian Motion as a Model in Finance

Non-semimartingales in finance

Module 10:Application of stochastic processes in areas like finance Lecture 36:Black-Scholes Model. Stochastic Differential Equation.

THE USE OF NUMERAIRES IN MULTI-DIMENSIONAL BLACK- SCHOLES PARTIAL DIFFERENTIAL EQUATIONS. Hyong-chol O *, Yong-hwa Ro **, Ning Wan*** 1.

Stochastic Processes and Stochastic Calculus - 9 Complete and Incomplete Market Models

Objective Binomial Model What is and what is not mortgage insurance in Mexico? 3 times model (Black and Scholes) Correlated brownian motion Other

CONTINUOUS TIME PRICING AND TRADING: A REVIEW, WITH SOME EXTRA PIECES

Definition Pricing Risk management Second generation barrier options. Barrier Options. Arfima Financial Solutions

An overview of some financial models using BSDE with enlarged filtrations

Math 416/516: Stochastic Simulation

Financial derivatives exam Winter term 2014/2015

Derivative Securities Fall 2012 Final Exam Guidance Extended version includes full semester

Credit Risk: Modeling, Valuation and Hedging

Equivalence between Semimartingales and Itô Processes

Chapter 1. Introduction and Preliminaries. 1.1 Motivation. The American put option problem

Option Pricing with Delayed Information

Semimartingales and their Statistical Inference

Monte Carlo Methods in Structuring and Derivatives Pricing

Quantitative Finance and Investment Core Exam

Pricing theory of financial derivatives

AMH4 - ADVANCED OPTION PRICING. Contents

Lecture Note 8 of Bus 41202, Spring 2017: Stochastic Diffusion Equation & Option Pricing

Arbeitsgruppe Stochastik. PhD Seminar: HJM Forwards Price Models for Commodities. M.Sc. Brice Hakwa

Basic Concepts and Examples in Finance

MATH3075/3975 FINANCIAL MATHEMATICS TUTORIAL PROBLEMS

Stochastic Finance - A Numeraire Approach

CONTENTS. Introduction. Acknowledgments. What Is New in the Second Edition? Option Pricing Formulas Overview. Glossary of Notations

Limit Theorems for Stochastic Processes

Basic Concepts in Mathematical Finance

Integre Technical Publishing Co., Inc. Chung February 8, :21 a.m. chung page 392. Index

Mathematics of Finance Final Preparation December 19. To be thoroughly prepared for the final exam, you should

Learning Martingale Measures to Price Options

Transcription:

N.H. Bingham and Rüdiger Kiesel Risk-Neutral Valuation Pricing and Hedging of Financial Derivatives W) Springer

Contents 1. Derivative Background 1 1.1 Financial Markets and Instruments 2 1.1.1 Derivative Instruments 2 1.1.2 Underlying securities 4 1.1.3 Markets 5 1.1.4 Types of Traders 6 1.1.5 Modelling Assumptions 7 1.2 Arbitrage 8 1.3 Arbitrage Relationships 11 1.3.1 Fundamental Determinants of Option Values 11 1.3.2 The Put-Call Parity 13 1.3.3 Arbitrage Bounds 16 1.4 Single-Period Market Models 20 Exercises 30 2. Probability Background 33 2.1 Measure 34 2.2 Integral 38 2.3 Probability 41 2.4 Equivalent Measures and Radon-Nikodym Derivatives 47 2.5 Conditional Expectations 48 2.6 Properties of Conditional Expectation 51 2.7 Modes of Convergence 53 2.8 Convolution and Characteristic Functions 56 2.9 The Central Limit Theorem 60 Exercises 63 3. Stochastic Processes in Discrete Time 67 3.1 Information and Filtrations 67 3.2 Discrete-Parameter Stochastic Processes 68 3.3 Discrete-Parameter Martingales 70 3.3.1 Definition and Simple Properties 70 3.3.2 Martingale Convergence 72 3.3.3 Doob Decomposition 73

xii Contents 3.4 Martingale Transforms 73 3.5 Stopping Times and Optional Stopping 75 3.6 The Snell Envelope 78 Exercises 80 4. Mathematical Finance in Discrete Time 83 4.1 The Model 83 4.2 Existence of Equivalent Martingale Measures 87 4.2.1 The No-Arbitrage Condition 87 4.2.2 Risk-Neutral Pricing 93 4.3 Complete Markets 96 4.4 Risk-Neutral Valuation 100 4.5 The Cox-Ross-Rubinstein Model 103 4.5.1 Model Structure 103 4.5.2 Risk-Neutral Pricing 105 4.5.3 Hedging 108 4.5.4 Comparison With the General Arbitrage Bounds 110 4.6 Binomial Approximations Ill 4.6.1 Model Structure 112 4.6.2 The Black-Scholes Option Pricing Formula 113 4.6.3 Further Limiting Models 118 4.7 Multifactor Models 121 4.7.1 Extended Binomial Model 121 4.7.2 Multinomial Models 122 4.8 Further Contingent Claim Valuation in Discrete Time 123 4.8.1 American Options 123 4.8.2 Barrier Options 126 4.8.3 Lookback Options 127 4.8.4 A Three-Period Example 128 Exercises 130 5. Stochastic Processes in Continuous Time 133 5.1 Filtrations; Finite-Dimensional Distributions 133 5.2 Classes of Processes 134 5.3 Brownian Motion 138 5.4 Quadratic Variation of Brownian Motion 141 5.5 Stochastic Integrals; Ito Calculus 144 5.6 Itö's Lemma 149 5.6.1 Geometric Brownian Motion 152 5.7 Stochastic Differential Equations 154 5.8 Stochastic Calculus for Black-Scholes Models 157 5.9 Weak Convergence of Stochastic Processes 161 5.9.1 The Spaces C d and D d 161 5.9.2 Definition and Motivation 162 5.9.3 Basic Theorems of Weak Convergence 164

Contents xiii 5.9.4 Weak Convergence Results for Stochastic Integrals.... 165 Exercises 167 6. Mathematical Finance in Continuous Time 171 6.1 Continuous-time Financial Market Models 171 6.1.1 The Financial Market Model 171 6.1.2 Equivalent Martingale Measures 174 6.1.3 Risk-neutral Pricing 177 6.1.4 Changes of Numeraire 180 6.2 The Generalised Black-Scholes Model 184 6.2.1 The Model 184 6.2.2 Pricing and Hedging Contingent Claims 192 6.2.3 The Greeks 195 6.2.4 Volatility 197 6.3 Further contingent claim valuation 199 6.3.1 American Options 199 6.3.2 Asian Options 202 6.3.3 Barrier Options 204 6.3.4 Lookback Options 207 6.3.5 Binary Options 210 6.4 Discrete- vs. Continuous-Time Models 211 6.4.1 Convergence Reconsidered 211 6.4.2 Finite Market Approximations 212 6.4.3 Examples of Finite Market Approximations 214 6.5 Further Applications 221 6.5.1 Futures Markets 221 6.5.2 Currency Markets 224 Exercises 226 7. Incomplete Markets 229 7.1 Pricing in Incomplete Markets 229 7.1.1 A General Option Pricing Formula 229 7.1.2 The Esscher Measure 232 7.2 Hedging in Incomplete Markets 235 7.2.1 Variance Minimising Hedging 235 7.2.2 Risk-Minimising Hedging 239 7.3 Stochastic Volatility Models 241 8. Interest Rate Theory 245 8.1 The Bond Market 246 8.1.1 The Term Structure of Interest Rates 246 8.1.2 Mathematical Modelling 247 8.1.3 Bond Pricing, 252 8.2 Short Rate Models 254 8.2.1 The Term Structure Equation 255

xiv Contents 8.2.2 Martingale Modelling 256 8.2.3 Parameter Estimation 260 8.3 Heath-Jarrow-Morton Methodology 262 8.3.1 The Heath-Jarrow-Morton Model Class 262 8.3.2 Forward Risk-Neutral Martingale Measures 265 8.3.3 Completeness 267 8.4 Pricing and Hedging Contingent Claims 268 8.4.1 Short Rate Models 268 8.4.2 Gaussian HJM Framework 269 8.4.3 Swaps 271 8.4.4 Caps 272 Exercises 274 A. Hubert Space 277 B. Projections and Conditional Expectations 279 C. The Separating Hyperplane Theorem 281 Bibliography 283 Index 293