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Computational Methods in Financial Engineering

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Cover of 'Computational Methods in Financial Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Threshold Accepting Approach to Improve Bound-based Approximations for Portfolio Optimization
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    Chapter 2 Risk Preferences and Loss Aversion in Portfolio Optimization
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    Chapter 3 Generalized Extreme Value Distribution and Extreme Economic Value at Risk (EE-VaR)
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    Chapter 4 Portfolio Optimization under VaR Constraints Based on Dynamic Estimates of the Variance-Covariance Matrix
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    Chapter 5 Optimal Execution of Time-Constrained Portfolio Transactions
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    Chapter 6 Semidefinite Programming Approaches for Bounding Asian Option Prices
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    Chapter 7 The Evaluation of Discrete Barrier Options in a Path Integral Framework
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    Chapter 8 Robust Prediction of Beta
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    Chapter 9 Neural Network Modelling with Applications to Euro Exchange Rates
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    Chapter 10 Testing Uncovered Interest Rate Parity and Term Structure Using Multivariate Threshold Cointegration
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    Chapter 11 Classification Using Optimization: Application to Credit Ratings of Bonds
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    Chapter 12 Evolving Decision Rules to Discover Patterns in Financial Data Sets
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    Chapter 13 A Banking Firm Model: The Role of Market, Liquidity and Credit Risks
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    Chapter 14 Identification of Critical Nodes and Links in Financial Networks with Intermediation and Electronic Transactions
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    Chapter 15 An Analysis of Settlement Risk Contagion in Alternative Securities Settlement Architectures
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    Chapter 16 Integrated Risk Management: Risk Aggregation and Allocation Using Intelligent Systems
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    Chapter 17 A Stochastic Monetary Policy Interest Rate Model
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    Chapter 18 Duali: Software for Solving Stochastic Control Problems in Economics
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Title
Computational Methods in Financial Engineering
Published by
Springer Berlin Heidelberg, January 2008
DOI 10.1007/978-3-540-77958-2
ISBNs
978-3-54-077957-5, 978-3-54-077958-2
Editors

Prof. Erricos J. Kontoghiorghes, Prof. Berç Rustem, Prof. Peter Winker

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 4%
Portugal 1 4%
Unknown 25 93%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 6 22%
Professor 5 19%
Student > Master 5 19%
Student > Ph. D. Student 5 19%
Other 2 7%
Other 3 11%
Unknown 1 4%
Readers by discipline Count As %
Economics, Econometrics and Finance 6 22%
Engineering 6 22%
Mathematics 4 15%
Computer Science 4 15%
Business, Management and Accounting 4 15%
Other 2 7%
Unknown 1 4%