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eISBN : 9780470164891

Sommaire : Contents
Preface
About the Authors
CHAPTER 1 Introduction
Quantitative Techniques in the Investment Management Industry
Central Themes of This Book
Overview of This Book
PART ONE Portfolio Allocation: Classical Theory and Extensions
CHAPTER 2 Mean-Variance Analysis and Modern Portfolio Theory
The Benefits of Diversification
Mean-Variance Analysis: Overview
Classical Framework for Mean-Variance Optimization
The Capital Market Line
Selection of the Optimal Portfolio When There Is a Risk-Free Asset
More on Utility Functions: A General Framework for Portfolio Choice
Summary
CHAPTER 3 Advances in the Theory of Portfolio Risk Measures
Dispersion and Downside Measures
Portfolio Selection with Higher Moments through Expansions of Utility
Polynomial Goal Programming for Portfolio Optimization with Higher Moments
Some Remarks on the Estimation of Higher Moments
The Approach of Malevergne and Sornette
Summary
CHAPTER 4 Portfolio Selection in Practice
Portfolio Constraints Commonly Used in Practice
Incorporating Transaction Costs in Asset-Allocation Models
Multiaccount Optimization
Summary
PART TWO Robust Parameter Estimation
CHAPTER 5 Classical Asset Pricing
Definitions
Theoretical and Econometric Models
Random Walk Models
General Equilibrium Theories
Capital Asset Pricing Model (CAPM)
Arbitrage Pricing Theory (APT)
Summary
CHAPTER 6 Forecasting Expected Return and Risk
Dividend Discount and Residual Income Valuation Models
The Sample Mean and Covariance Estimators
Random Matrices
Arbitrage Pricing Theory and Factor Models
Factor Models in Practice
Other Approaches to Volatility Estimation
Application to Investment Strategies and Proprietary Trading
Summary
CHAPTER 7 Robust Estimation
The Intuition behind Robust Statistics
Robust Statistics
Robust Estimators of Regressions
Confidence Intervals
Summary
CHAPTER 8 Robust Frameworks for Estimation: Shrinkage,
Practical Problems Encountered in Mean-Variance Optimization
Shrinkage Estimation
Bayesian Approaches
Summary
PART THREEOptimization Techniques
CHAPTER 9 Mathematical and Numerical Optimization
Mathematical Programming
Necessary Conditions for Optimality for Continuous Optimization Problems
Optimization Duality Theory
How Do Optimization Algorithms Work?
Summary
CHAPTER 10 Optimization under Uncertainty
Stochastic Programming
Dynamic Programming
Robust Optimization
Summary
CHAPTER 11 Implementing and Solving Optimization Problems in Practice
Optimization Software
Practical Considerations When Using Optimization Software
Implementation Examples
Specialized Software for Optimization Under Uncertainty
Summary
PART FOUR Robust Portfolio Optimization
CHAPTER 12 Robust Modeling of Uncertain Parameters in Classical
Portfolio Resampling Techniques
Robust Portfolio Allocation
Some Practical Remarks on Robust Portfolio Allocation Models
Summary
CHAPTER 13 The Practice of Robust Portfolio Management: Recent Trends and
Some Issues in Robust Asset Allocation
Portfolio Rebalancing
Understanding and Modeling Transaction Costs
Rebalancing Using an Optimizer
Summary
CHAPTER 14 Quantitative Investment Management Today and Tomorrow
Using Derivatives in Portfolio Management
Currency Management
Benchmarks
Quantitative Return-Forecasting Techniques and Model-Based Trading Strategies
Trade Execution and Algorithmic Trading
Summary
APPENDIX A Data Description: The MSCI World Index
INDEX

Langue : Anglais

Localisation : Bibliothèque Campus de Nice

Support : Numérique

Etat : Présent

Propriétaire : Bibliothèque