Table Of Content
Market Risk Analysis
Volume I
Quantitative Methods in Finance
Market Risk Analysis
Volume I
Quantitative Methods in Finance
Carol Alexander
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Contents
List of Figures xiii
List of Tables xvi
List of Examples xvii
Foreword xix
Preface to Volume I xxiii
I.1 Basic Calculus for Finance 1
I.1.1 Introduction 1
I.1.2 Functions and Graphs, Equations and Roots 3
I.1.2.1 Linear and Quadratic Functions 4
I.1.2.2 Continuous and Differentiable Real-Valued Functions 5
I.1.2.3 Inverse Functions 6
I.1.2.4 The Exponential Function 7
I.1.2.5 The Natural Logarithm 9
I.1.3 Differentiation and Integration 10
I.1.3.1 Definitions 10
I.1.3.2 Rules for Differentiation 11
I.1.3.3 Monotonic, Concave and Convex Functions 13
I.1.3.4 Stationary Points and Optimization 14
I.1.3.5 Integration 15
I.1.4 Analysis of Financial Returns 16
I.1.4.1 Discrete and Continuous Time Notation 16
I.1.4.2 Portfolio Holdings and Portfolio Weights 17
I.1.4.3 Profit and Loss 19
I.1.4.4 Percentage and Log Returns 19
I.1.4.5 Geometric Brownian Motion 21
I.1.4.6 Discrete and Continuous Compounding in Discrete Time 22
I.1.4.7 Period Log Returns in Discrete Time 23
I.1.4.8 Return on a Linear Portfolio 25
I.1.4.9 Sources of Returns 25
I.1.5 Functions of Several Variables 26
I.1.5.1 Partial Derivatives: Function of Two Variables 27
I.1.5.2 Partial Derivatives: Function of Several Variables 27
viii Contents
I.1.5.3 Stationary Points 28
I.1.5.4 Optimization 29
I.1.5.5 Total Derivatives 31
I.1.6 Taylor Expansion 31
I.1.6.1 Definition and Examples 32
I.1.6.2 Risk Factors and their Sensitivities 33
I.1.6.3 Some Financial Applications of Taylor Expansion 33
I.1.6.4 Multivariate Taylor Expansion 34
I.1.7 Summary and Conclusions 35
I.2 Essential Linear Algebra for Finance 37
I.2.1 Introduction 37
I.2.2 Matrix Algebra and its Mathematical Applications 38
I.2.2.1 Basic Terminology 38
I.2.2.2 Laws of Matrix Algebra 39
I.2.2.3 Singular Matrices 40
I.2.2.4 Determinants 41
I.2.2.5 Matrix Inversion 43
I.2.2.6 Solution of Simultaneous Linear Equations 44
I.2.2.7 Quadratic Forms 45
I.2.2.8 Definite Matrices 46
I.2.3 Eigenvectors and Eigenvalues 48
I.2.3.1 Matrices as Linear Transformations 48
I.2.3.2 Formal Definitions 50
I.2.3.3 The Characteristic Equation 51
I.2.3.4 Eigenvalues and Eigenvectors of a 2×2 Correlation
Matrix 52
I.2.3.5 Properties of Eigenvalues and Eigenvectors 52
I.2.3.6 Using Excel to Find Eigenvalues and Eigenvectors 53
I.2.3.7 Eigenvalue Test for Definiteness 54
I.2.4 Applications to Linear Portfolios 55
I.2.4.1 Covariance and Correlation Matrices 55
I.2.4.2 Portfolio Risk and Return in Matrix Notation 56
I.2.4.3 Positive Definiteness of Covariance and Correlation
Matrices 58
I.2.4.4 Eigenvalues and Eigenvectors of Covariance and
Correlation Matrices 59
I.2.5 Matrix Decomposition 61
I.2.5.1 Spectral Decomposition of a Symmetric Matrix 61
I.2.5.2 Similarity Transforms 62
I.2.5.3 Cholesky Decomposition 62
I.2.5.4 LU Decomposition 63
I.2.6 Principal Component Analysis 64
I.2.6.1 Definition of Principal Components 65
I.2.6.2 Principal Component Representation 66
I.2.6.3 Case Study: PCA of European Equity Indices 67
I.2.7 Summary and Conclusions 70
