Dynamic Copula Methods in Finance (eBook, PDF)
Dynamic Copula Methods in Finance (eBook, PDF)
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung
Hier können Sie sich einloggen
Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
The latest tools and techniques for pricing and risk management This book introduces readers to the use of copula functions to represent the dynamics of financial assets and risk factors, integrated temporal and cross-section applications. The first part of the book will briefly introduce the standard the theory of copula functions, before examining the link between copulas and Markov processes. It will then introduce new techniques to design Markov processes that are suited to represent the dynamics of market risk factors and their co-movement, providing techniques to both estimate and…mehr
- Geräte: PC
- mit Kopierschutz
- eBook Hilfe
- Größe: 12.28MB
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
- Produktdetails
- Verlag: John Wiley & Sons
- Seitenzahl: 288
- Erscheinungstermin: 7. Oktober 2011
- Englisch
- ISBN-13: 9781119954514
- Artikelnr.: 37356909
- Verlag: John Wiley & Sons
- Seitenzahl: 288
- Erscheinungstermin: 7. Oktober 2011
- Englisch
- ISBN-13: 9781119954514
- Artikelnr.: 37356909
and Risk Management 1 1.2 Implied vs Realized Correlation 3 1.3 Bottom-up
vs Top-down Models 4 1.4 Copula Functions 4 1.5 Spatial and Temporal
Dependence 5 1.6 Long-range Dependence 5 1.7 Multivariate GARCH Models 7
1.8 Copulas and Convolution 8 2 Copula Functions: The State of the Art 11
2.1 Copula Functions: The Basic Recipe 11 2.2 Market Co-movements 14 2.3
Delta Hedging Multivariate Digital Products 16 2.4 Linear Correlation 19
2.5 Rank Correlation 20 2.6 Multivariate Spearman's Rho 22 2.7 Survival
Copulas and Radial Symmetry 23 2.8 Copula Volume and Survival Copulas 24
2.9 Tail Dependence 27 2.10 Long/Short Correlation 27 2.11 Families of
Copulas 29 2.11.1 Elliptical Copulas 29 2.11.2 Archimedean Copulas 31 2.12
Kendall Function 33 2.13 Exchangeability 34 2.14 Hierarchical Copulas 35
2.15 Conditional Probability and Factor Copulas 39 2.16 Copula Density and
Vine Copulas 42 2.17 Dynamic Copulas 45 2.17.1 Conditional Copulas 45
2.17.2 Pseudo-copulas 46 3 Copula Functions and Asset Price Dynamics 49 3.1
The Dynamics of Speculative Prices 49 3.2 Copulas and Markov Processes: The
DNO approach 51 3.2.1 The * and * Product Operators 52 3.2.2 Product
Operators and Markov Processes 55 3.2.3 Self-similar Copulas 58 3.2.4
Simulating Markov Chains with Copulas 62 3.3 Time-changed Brownian Copulas
63 3.3.1 CEV Clock Brownian Copulas 64 3.3.2 VG Clock Brownian Copulas 65
3.4 Copulas and Martingale Processes 66 3.4.1 C-Convolution 67 3.4.2 Markov
Processes with Independent Increments 75 3.4.3 Markov Processes with
Dependent Increments 78 3.4.4 Extracting Dependent Increments in Markov
Processes 81 3.4.5 Martingale Processes 83 3.5 Multivariate Processes 86
3.5.1 Multivariate Markov Processes 86 3.5.2 Granger Causality and the
Martingale Condition 88 4 Copula-based Econometrics of Dynamic Processes 91
4.1 Dynamic Copula Quantile Regressions 91 4.2 Copula-based Markov
Processes: Non-linear Quantile Autoregression 93 4.3 Copula-based Markov
Processes: Semi-parametric Estimation 99 4.4 Copula-based Markov Processes:
Non-parametric Estimation 108 4.5 Copula-based Markov Processes: Mixing
Properties 110 4.6 Persistence and Long Memory 113 4.7 C-convolution-based
Markov Processes: The Likelihood Function 116 5 Multivariate Equity
Products 121 5.1 Multivariate Equity Products 121 5.1.1 European
Multivariate Equity Derivatives 122 5.1.2 Path-dependent Equity Derivatives
125 5.2 Recursions of Running Maxima and Minima 126 5.3 The Memory Feature
130 5.4 Risk-neutral Pricing Restrictions 132 5.5 Time-changed Brownian
Copulas 133 5.6 Variance Swaps 135 5.7 Semi-parametric Pricing of
Path-dependent Derivatives 136 5.8 The Multivariate Pricing Setting 137 5.9
H-Condition and Granger Causality 137 5.10 Multivariate Pricing Recursion
138 5.11 Hedging Multivariate Equity Derivatives 141 5.12 Correlation Swaps
144 5.13 The Term Structure of Multivariate Equity Derivatives 147 5.13.1
Altiplanos 148 5.13.2 Everest 150 5.13.3 Spread Options 150 6 Multivariate
Credit Products 153 6.1 Credit Transfer Finance 153 6.1.1 Univariate Credit
Transfer Products 154 6.1.2 Multivariate Credit Transfer Products 155 6.2
Credit Information: Equity vs CDS 158 6.3 Structural Models 160 6.3.1
Univariate Model: Credit Risk as a Put Option 160 6.3.2 Multivariate Model:
Gaussian Copula 161 6.3.3 Large Portfolio Model: Vasicek Formula 163 6.4
Intensity-based Models 164 6.4.1 Univariate Model: Poisson and Cox
Processes 165 6.4.2 Multivariate Model: Marshall-Olkin Copula 165 6.4.3
Homogeneous Model: Cuadras Augé Copula 167 6.5 Frailty Models 170 6.5.1
Multivariate Model: Archimedean Copulas 170 6.5.2 Large Portfolio Model:
Schönbucher Formula 171 6.6 Granularity Adjustment 171 6.7 Credit Portfolio
Analysis 172 6.7.1 Semi-unsupervised Cluster Analysis: K-means 172 6.7.2
Unsupervised Cluster Analysis: Kohonen Self-organizing Maps 174 6.7.3
(Semi-)unsupervised Cluster Analysis: Hierarchical Correlation Model 175
6.8 Dynamic Analysis of Credit Risk Portfolios 176 7 Risk Capital
Management 181 7.1 A Review of Value-at-Risk and Other Measures 181 7.2
Capital Aggregation and Allocation 185 7.2.1 Aggregation: C-Convolution 187
7.2.2 Allocation: Level Curves 189 7.2.3 Allocation with Constraints 191
7.3 Risk Measurement of Managed Portfolios 193 7.3.1 Henriksson-Merton
Model 195 7.3.2 Semi-parametric Analysis of Managed Funds 200 7.3.3
Market-neutral Investments 201 7.4 Temporal Aggregation of Risk Measures
202 7.4.1 The Square-root Formula 203 7.4.2 Temporal Aggregation by
C-convolution 203 8 Frontier Issues 207 8.1 Levy Copulas 207 8.2 Pareto
Copulas 210 8.3 Semi-martingale Copulas 212 A Elements of Probability 215
A.1 Elements of Measure Theory 215 A.2 Integration 216 A.2.1 Expected
Values and Moments 217 A.3 The Moment-generating Function or Laplace
Transform 218 A.4 The Characteristic Function 219 A.5 Relevant Probability
Distributions 219 A.6 Random Vectors and Multivariate Distributions 224
A.6.1 The Multivariate Normal Distribution 225 A.7 Infinite Divisibility
226 A.8 Convergence of Sequences of Random Variables 228 A.8.1 The Strong
Law of Large Numbers 229 A.9 The Radon-Nikodym Derivative 229 A.10
Conditional Expectation 229 B Elements of Stochastic Processes Theory 231
B.1 Stochastic Processes 231 B.1.1 Filtrations 231 B.1.2 Stopping Times 232
B.2 Martingales 233 B.3 Markov Processes 234 B.4 Lévy Processes 237 B.4.1
Subordinators 240 B.5 Semi-martingales 240 References 245 Extra Reading 251
Index 259
and Risk Management 1 1.2 Implied vs Realized Correlation 3 1.3 Bottom-up
vs Top-down Models 4 1.4 Copula Functions 4 1.5 Spatial and Temporal
Dependence 5 1.6 Long-range Dependence 5 1.7 Multivariate GARCH Models 7
1.8 Copulas and Convolution 8 2 Copula Functions: The State of the Art 11
2.1 Copula Functions: The Basic Recipe 11 2.2 Market Co-movements 14 2.3
Delta Hedging Multivariate Digital Products 16 2.4 Linear Correlation 19
2.5 Rank Correlation 20 2.6 Multivariate Spearman's Rho 22 2.7 Survival
Copulas and Radial Symmetry 23 2.8 Copula Volume and Survival Copulas 24
2.9 Tail Dependence 27 2.10 Long/Short Correlation 27 2.11 Families of
Copulas 29 2.11.1 Elliptical Copulas 29 2.11.2 Archimedean Copulas 31 2.12
Kendall Function 33 2.13 Exchangeability 34 2.14 Hierarchical Copulas 35
2.15 Conditional Probability and Factor Copulas 39 2.16 Copula Density and
Vine Copulas 42 2.17 Dynamic Copulas 45 2.17.1 Conditional Copulas 45
2.17.2 Pseudo-copulas 46 3 Copula Functions and Asset Price Dynamics 49 3.1
The Dynamics of Speculative Prices 49 3.2 Copulas and Markov Processes: The
DNO approach 51 3.2.1 The * and * Product Operators 52 3.2.2 Product
Operators and Markov Processes 55 3.2.3 Self-similar Copulas 58 3.2.4
Simulating Markov Chains with Copulas 62 3.3 Time-changed Brownian Copulas
63 3.3.1 CEV Clock Brownian Copulas 64 3.3.2 VG Clock Brownian Copulas 65
3.4 Copulas and Martingale Processes 66 3.4.1 C-Convolution 67 3.4.2 Markov
Processes with Independent Increments 75 3.4.3 Markov Processes with
Dependent Increments 78 3.4.4 Extracting Dependent Increments in Markov
Processes 81 3.4.5 Martingale Processes 83 3.5 Multivariate Processes 86
3.5.1 Multivariate Markov Processes 86 3.5.2 Granger Causality and the
Martingale Condition 88 4 Copula-based Econometrics of Dynamic Processes 91
4.1 Dynamic Copula Quantile Regressions 91 4.2 Copula-based Markov
Processes: Non-linear Quantile Autoregression 93 4.3 Copula-based Markov
Processes: Semi-parametric Estimation 99 4.4 Copula-based Markov Processes:
Non-parametric Estimation 108 4.5 Copula-based Markov Processes: Mixing
Properties 110 4.6 Persistence and Long Memory 113 4.7 C-convolution-based
Markov Processes: The Likelihood Function 116 5 Multivariate Equity
Products 121 5.1 Multivariate Equity Products 121 5.1.1 European
Multivariate Equity Derivatives 122 5.1.2 Path-dependent Equity Derivatives
125 5.2 Recursions of Running Maxima and Minima 126 5.3 The Memory Feature
130 5.4 Risk-neutral Pricing Restrictions 132 5.5 Time-changed Brownian
Copulas 133 5.6 Variance Swaps 135 5.7 Semi-parametric Pricing of
Path-dependent Derivatives 136 5.8 The Multivariate Pricing Setting 137 5.9
H-Condition and Granger Causality 137 5.10 Multivariate Pricing Recursion
138 5.11 Hedging Multivariate Equity Derivatives 141 5.12 Correlation Swaps
144 5.13 The Term Structure of Multivariate Equity Derivatives 147 5.13.1
Altiplanos 148 5.13.2 Everest 150 5.13.3 Spread Options 150 6 Multivariate
Credit Products 153 6.1 Credit Transfer Finance 153 6.1.1 Univariate Credit
Transfer Products 154 6.1.2 Multivariate Credit Transfer Products 155 6.2
Credit Information: Equity vs CDS 158 6.3 Structural Models 160 6.3.1
Univariate Model: Credit Risk as a Put Option 160 6.3.2 Multivariate Model:
Gaussian Copula 161 6.3.3 Large Portfolio Model: Vasicek Formula 163 6.4
Intensity-based Models 164 6.4.1 Univariate Model: Poisson and Cox
Processes 165 6.4.2 Multivariate Model: Marshall-Olkin Copula 165 6.4.3
Homogeneous Model: Cuadras Augé Copula 167 6.5 Frailty Models 170 6.5.1
Multivariate Model: Archimedean Copulas 170 6.5.2 Large Portfolio Model:
Schönbucher Formula 171 6.6 Granularity Adjustment 171 6.7 Credit Portfolio
Analysis 172 6.7.1 Semi-unsupervised Cluster Analysis: K-means 172 6.7.2
Unsupervised Cluster Analysis: Kohonen Self-organizing Maps 174 6.7.3
(Semi-)unsupervised Cluster Analysis: Hierarchical Correlation Model 175
6.8 Dynamic Analysis of Credit Risk Portfolios 176 7 Risk Capital
Management 181 7.1 A Review of Value-at-Risk and Other Measures 181 7.2
Capital Aggregation and Allocation 185 7.2.1 Aggregation: C-Convolution 187
7.2.2 Allocation: Level Curves 189 7.2.3 Allocation with Constraints 191
7.3 Risk Measurement of Managed Portfolios 193 7.3.1 Henriksson-Merton
Model 195 7.3.2 Semi-parametric Analysis of Managed Funds 200 7.3.3
Market-neutral Investments 201 7.4 Temporal Aggregation of Risk Measures
202 7.4.1 The Square-root Formula 203 7.4.2 Temporal Aggregation by
C-convolution 203 8 Frontier Issues 207 8.1 Levy Copulas 207 8.2 Pareto
Copulas 210 8.3 Semi-martingale Copulas 212 A Elements of Probability 215
A.1 Elements of Measure Theory 215 A.2 Integration 216 A.2.1 Expected
Values and Moments 217 A.3 The Moment-generating Function or Laplace
Transform 218 A.4 The Characteristic Function 219 A.5 Relevant Probability
Distributions 219 A.6 Random Vectors and Multivariate Distributions 224
A.6.1 The Multivariate Normal Distribution 225 A.7 Infinite Divisibility
226 A.8 Convergence of Sequences of Random Variables 228 A.8.1 The Strong
Law of Large Numbers 229 A.9 The Radon-Nikodym Derivative 229 A.10
Conditional Expectation 229 B Elements of Stochastic Processes Theory 231
B.1 Stochastic Processes 231 B.1.1 Filtrations 231 B.1.2 Stopping Times 232
B.2 Martingales 233 B.3 Markov Processes 234 B.4 Lévy Processes 237 B.4.1
Subordinators 240 B.5 Semi-martingales 240 References 245 Extra Reading 251
Index 259