Kontoghiorghes / Rustem / Winker Computational Methods in Financial Engineering

Essays in Honour of Manfred Gilli
1. Auflage 2008
ISBN: 978-3-540-77958-2
Verlag: Springer Berlin Heidelberg
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 425 Seiten

Computational models and methods are central to the analysis of economic and financial decisions. Simulation and optimisation are widely used as tools of analysis, modelling and testing. The focus of this book is the development of computational methods and analytical models in financial engineering that rely on computation. The book contains eighteen chapters written by leading researchers in the area on portfolio optimization and option pricing; estimation and classification; banking; risk and macroeconomic modelling. It explores and brings together current research tools and will be of interest to researchers, analysts and practitioners in policy and investment decisions in economics and finance.

Autoren/Hrsg.

Rustem, Berç

Winker, Peter

Kontoghiorghes, Erricos

Rustem, Berc

Inhaltsverzeichnis

1;Preface;7
2;Contents;9
3;List of Contributors;11
4;Part I Portfolio Optimization and Option Pricing;16
4.1;Threshold Accepting Approach to Improve Bound- based Approximations for Portfolio Optimization;17
4.1.1;1 Introduction;17
4.1.2;2 Portfolio Problem;20
4.1.3;3 Time Discretization;22
4.1.4;4 Multistage Stochastic Programs;24
4.1.5;5 Space Discretization;26
4.1.6;6 Case Study;33
4.1.7;Acknowledgments;38
4.1.8;References;38
4.2;Risk Preferences and Loss Aversion in Portfolio Optimization;41
4.2.1;1 Assets and Asset Selection;41
4.2.2;2 Portfolio Optimization under Loss Aversion;44
4.2.3;3 Heuristic Methods for Portfolio Optimization;46
4.2.4;4 Empirical Study;50
4.2.5;5 Conclusion;57
4.2.6;Acknowledgements;58
4.2.7;References;58
4.3;Generalized Extreme Value Distribution and Extreme Economic Value at Risk ( EE- VaR);61
4.3.1;1 Introduction;61
4.3.2;2 Model and Methodology;66
4.3.3;3 Data Description;69
4.3.4;4 Empirical Modelling and Results on Implied RNDs;70
4.3.5;5 Conclusions;82
4.3.6;Acknowledgements;83
4.3.7;References;83
4.4;Portfolio Optimization under VaR Constraints Based on Dynamic Estimates of the Variance- Covariance Matrix;87
4.4.1;1 Introduction;87
4.4.2;2 Model;90
4.4.3;3 Optimization Method;93
4.4.4;4 Empirical Analysis;96
4.4.5;5 Conclusion;105
4.4.6;Acknowledgements;106
4.4.7;References;106
4.5;Optimal Execution of Time-Constrained Portfolio Transactions;109
4.5.1;1 Introduction;109
4.5.2;2 Problem Definition;110
4.5.3;3 Price Dynamics;110
4.5.4;4 An Approximation Approach;111
4.5.5;5 Numerical Example;113
4.5.6;6 Monte Carlo Simulation;114
4.5.7;7 Concluding Remarks;114
4.5.8;Acknowledgements;116
4.5.9;References;116
4.6;Semidefinite Programming Approaches for Bounding Asian Option Prices;117
4.6.1;Preamble;117
4.6.2;1 Introduction;117
4.6.3;2 SDP Strategy for Bounding Option Prices;119
4.6.4;3 Conclusion;127
4.6.5;References;127
4.7;The Evaluation of Discrete Barrier Options in a Path Integral Framework;131
4.7.1;1 Introduction;131
4.7.2;2 The General Barrier Structure;133
4.7.3;3 The Barrier Option as a Functional Recurrence Relation Equation;135
4.7.4;4 The Fourier-Hermite Series Expansion;136
4.7.5;5 Results;142
4.7.6;6 Conclusion;145
4.7.7;Acknowledgements;146
4.7.8;References;146
4.7.9;Appendix;147
4.7.9.1;A The Coefficient;147
4.7.9.2;B The Coefficient;148
4.7.9.3;C The Coefficient;149
4.7.9.4;D The Coefficient;150
4.7.9.5;E The Coefficient;151
4.7.9.6;F The Coefficient;153
4.7.9.7;G The Coefficient;155
4.7.9.8;H Useful Notation;157
5;Part II Estimation and Classi.cation;159
5.1;Robust Prediction of Beta;161
5.1.1;Preamble;161
5.1.2;1 Introduction;161
5.1.3;2 Shrinkage Robust Estimators of Beta;163
5.1.4;3 Empirical Evidence;165
5.1.5;4 Monte Carlo Simulations;168
5.1.6;5 Conclusion;174
5.1.7;Acknowledgements;174
5.1.8;References;174
5.2;Neural Network Modelling with Applications to Euro Exchange Rates;177
5.2.1;1 Introduction;177
5.2.2;2 Feedforward Neural Network Models;180
5.2.3;3 Variable Selection in Neural Network Models;183
5.2.4;4 Numerical Examples and Monte Carlo Results;186
5.2.5;5 An Application to Euro Exchange Rates;190
5.2.6;6 Conclusions;193
5.2.7;Acknowledgements;194
5.2.8;References;194
5.3;Testing Uncovered Interest Rate Parity and Term Structure Using Multivariate Threshold Cointegration;205
5.3.1;Preamble;205
5.3.2;1 Introduction;206
5.3.3;2 The Economic Relations;208
5.3.4;3 The Econometric Framework;210
5.3.5;4 Empirical Analysis;216
5.3.6;5 Conclusion;220
5.3.7;Acknowledgements;220
5.3.8;References;220
5.4;Classification Using Optimization: Application to Credit Ratings of Bonds;225
5.4.1;1 Introduction;225
5.4.2;2 Description of Methodology;227
5.4.3;3 Constraints;232
5.4.4;4 Choosing Model Flexibility;237
5.4.5;5 Error Estimation;244
5.4.6;6 Bond Classi.cation Problem;245
5.4.7;7 Description of Data;246
5.4.8;8 Numerical Experiments;247
5.4.9;9 Concluding Remarks;250
5.4.10;References;251
5.5;Evolving Decision Rules to Discover Patterns in Financial Data Sets;253
5.5.1;1 Introduction;253
5.5.2;2 Previous Work;254
5.5.3;3 PerformanceMetrics;255
5.5.4;4 Evolving Comprehensible Rules;258
5.5.5;5 Results and Discussion;260
5.5.6;6 Conclusions;265
5.5.7;Acknowledgements;267
5.5.8;References;267
6;Part III Banking, Risk and Macroeconomic Modelling;271
6.1;A Banking Firm Model: The Role of Market, Liquidity and Credit Risks;273
6.1.1;1 Introduction;273
6.1.2;2 The Model;275
6.1.3;3 Conclusion;282
6.1.4;Acknowledgements;285
6.1.5;References;285
6.2;Identification of Critical Nodes and Links in Financial Networks with Intermediation and Electronic Transactions;287
6.2.1;1 Introduction;287
6.2.2;2 The Financial Network Model with Intermediation and Electronic Transactions;290
6.2.3;3 The Financial Network Performance Measure and the Importance of Financial Network Components;298
6.2.4;4 Numerical Examples;302
6.2.5;5 Summary and Conclusions;307
6.2.6;Acknowledgements;307
6.2.7;References;308
6.3;An Analysis of Settlement Risk Contagion in Alternative Securities Settlement Architectures;313
6.3.1;Preamble;313
6.3.2;1 Introduction;313
6.3.3;2 The Basic Framework;318
6.3.4;3 Numerical Analysis;320
6.3.5;4 Conclusions;327
6.3.6;Acknowledgements;328
6.3.7;References;328
6.4;Integrated Risk Management: Risk Aggregation and Allocation Using Intelligent Systems;331
6.4.1;1 Introduction;331
6.4.2;2 Current Silo-Based Approach to Risk Management;332
6.4.3;3 An Integrated Approach to Risk Management;334
6.4.4;4 Summary and Outlook;351
6.4.5;Acknowledgements;353
6.4.6;References;353
6.5;A Stochastic Monetary Policy Interest Rate Model;357
6.5.1;1 Introduction;357
6.5.2;2 Continuous-time Lattices;359
6.5.3;3 The Interest Rate Model;368
6.5.4;4 Conclusions;396
6.5.5;A Continuous-time Finite-state Markov Chains;397
6.5.6;B Markov Generator Discretization;400
6.5.7;C Option Pricing with Continuous-time Lattices;401
6.5.8;D Moments Method for Range Accruals;402
6.5.9;References;404
6.6;Duali: Software for Solving Stochastic Control Problems in Economics;407
6.6.1;Preamble;407
6.6.2;1 Introduction;408
6.6.3;2 The Beck and Wieland Model in Wieland’s Notation;409
6.6.4;3 The Beck and Wieland Model in Kendrick’s Notation;410
6.6.5;4 Open Loop;414
6.6.6;5 Optimal Feedback;415
6.6.7;6 Expected Optimal Feedback;417
6.6.8;7 OF versus EOF;422
6.6.9;8 Expected Optimal Feedback with Time-Varying Parameters (EOFwT);423
6.6.10;9 OFwT versus EOFwT;424
6.6.11;10 Conclusion;425
6.6.12;References;425
6.6.13;A The Beck and Wieland Model in;427
7;Index;435