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eISBN : 9780470037690

Contents : Contents
Preface
Acknowledgments
About the Authors
CHAPTER 1 Introduction
Historical Perspective on the Financial Modeling of the Equity Market
Central Themes of the Book
Organization of the Book
PART ONE Portfolio Allocation: Classical Theory and Modern 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 Transaction and Trading Costs
A Taxonomy of Transaction Costs
Liquidity and Transaction Costs
Market Impact Measurements and Empirical Findings
Forecasting and Modeling Market Impact
Incorporating Transaction Costs in Asset-Allocation Models
Optimal Trading
Integrated Portfolio Management: Beyond Expected Return and Portfolio Risk
Summary
CHAPTER 4 Applying the Portfolio Selection Framework in Practice
Rebalancing in the Mean-Variance Optimization Framework
Portfolio Constraints Commonly Used in Practice
Summary
CHAPTER 5 Incorporating Higher Moments and Extreme 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 6 Mathematical and Numerical Optimization
Mathematical Programming
Necessary Conditions for Optimality for Continuous Optimization Problems
How Do Optimization Algorithms Work?
Optimization Software
Practical Considerations when Using Optimization Software
Summary
PART TWO Managing Uncertainty in Practice
CHAPTER 7 Equity Price Models
Definitions
Theoretical and Econometric Models
Random Walk Models
General Equilibrium Theories
Capital Asset Pricing Model (CAPM)
Arbitrage Pricing Theory (APT)
Summary
CHAPTER 8 Forecasting Expected Return and Risk
Dividend Discount and Residual Income Valuation Models
The Sample Mean and Covariance Estimator
Random Matrices
Arbitrage Pricing Theory and Factor Models
Factor Models in Practice
Factor Models in Practice: An Example
Other Approaches to Volatility Estimation
Application to Investment Strategies and Proprietary Trading
Summary
CHAPTER 9 Robust Frameworks for Estimation and Portfolio Allocation
Practical Problems Encountered in Mean-Variance Optimization
Shrinkage Estimation
Bayesian Approaches
Incorporating Estimation Error and Uncertainty in the Portfolio Allocation Process
Summary
PART THREE Dynamic Models for Equity Prices
CHAPTER 10 Feedback and Predictors in Stock Markets
Random Walk Models and Their Shortcomings
Time Diversification
A Multiagent Economy: Effects of Agent Heterogeneity and Interactions
Market Predictors
Time Aggregation
Summary
CHAPTER 11 Individual Price Processes: Univariate Models
Time Series Concepts
Digression on White Noise and Martingale Difference Sequences
The Lag Operator L
Univariate Autoregressive Moving Average (ARMA) Models
Stationarity Conditions
Auto Correlations at Different Lags
Solutions of an AR(p) Process
MA(q) Moving Average Models
ARMA(p, q) Models
Integrated Processes
Summary
CHAPTER 12 Multivariate Models
Dynamic Models: A Historical Perspective
Vector Autoregressive Models
Vector Autoregressive Moving Average Models (VARMA)
Distributional Properties
Cointegration
Stochastic and Deterministic Cointegration
Common Trends
Error Correction Models
Forecasting with VAR Models
State-Space Models
Autoregressive Distributed Lag Models
Dynamic Factor Models
The ARCH/GARCH Family of Models
Nonlinear Markov-Switching Models
Summary
CHAPTER 13 Model Selection and its Pitfalls
Model Selection and Estimation
The (Machine) Learning Approach to Model Selection
Sample Size and Model Complexity
Dangerous Patterns of Behavior
Data Snooping
Survivorship Biases and Other Sample Defects
Moving Training Windows
Model Risk
Model Selection in a Nutshell
Summary
PART FOUR Model Estimation amd Model Risk Mitigation
CHAPTER 14 Estimation of Regression Models
Probability Theory and Statistics
Populations of Prices and Returns
Estimation at Work
Estimators
Sampling Distributions
Critical Values and Confidence Intervals
Maximum Likelihood, OLS, and Regressions
The Fisher Information Matrix and the Cramer-Rao Bound
Regressions
Linear Regressions
Sampling Distributions of Regressions
Relaxing the Normality and Uncorrelated Noise Assumptions
Pitfalls of Regressions
The Method of Moments and its Generalizations
Summary
CHAPTER 15 Estimation of Linear Dynamic Models
An Approach to Estimation
Unit Root Testing
Estimation of Linear Regression Models
Estimation of Stable Vector Autoregressive (VAR) Models
Estimating the Number of Lags
Autocorrelation and Distributional Properties of Residuals
Stationary Autoregressive Distributed Lag Models
Applying Stable VAR Processes to Financial Econometrics
Stationary Dynamic Factor Models
Estimation of Nonstationary VAR Models
Estimation with Canonical Correlations
Estimation with Principal Component Analysis
Estimation with the Eigenvalues of the Companion Matrix
Estimation with Subspace Methods and Dynamic Factor Analysis
Application of Cointegration Methods to the Analysis of Predictors
Summary
CHAPTER 16 Estimation of Hidden Variable Models
Estimation of State-Space Models
Estimation of Factor Analytic Models
Estimation Methods for Markov-Switching Models
Applications
Summary
CHAPTER 17 Model Risk and its Mitigation
Sources of Model Risk
The Information Theory Approach to Model Risk
Bayesian Modeling
Model Averaging and the Shrinkage Approach to Model Risk
Random Coefficients Models
Summary
APPENDICES
APPENDIX A Difference Equations
Homogeneous Difference Equations
Nonhomogeneous Difference Equations
Systems of Linear Difference Equations
Systems of Homogeneous Linear Difference Equations
APPENDIX B Correlations, Regressions, and Copulas
Probability Density Function, Marginal Density, and Conditional Density
Expectations and Conditional Expectations
Variances, Covariances, and Correlations
Normal Distributions
Regression
Multivariate Extension
Multiple and Multivariate Regressions
Canonical Correlations
Copula Functions
APPENDIX C Data Description
INDEX

Language : English

Location : Nice Library

Material : Electronic

Statement : Présent

Owner : Bibliothèque