Financial Modeling of the Equity Market

This book presents complex concepts in a concise and clear manner and includes a wealth of real-world examples and practical simulations. Filled with in-depth insight and expert advice, Financial Modeling of the Equity Market covers a wide range of important topics including:

• The major approaches to single-period portfolio analysis, including modeling, estimation, and optimization issues
• Static and dynamic factor analysis, regime shifts, long-run modeling, and cointegration
• Estimation issues such as dimensionality reduction, Bayesian estimates, the Black-Litterman model, and random coefficient models
• Advances in transaction cost measurement and modeling, robust optimization, and recent developments in optimization with higher moments

Financial Modeling of the Equity Market contains the latest techniques for modeling equity portfolios and offers both financial professionals and students of finance a chance to improve their skills within this important area.

Table of Contents

• Chapter 1. Introduction

Part One: Portfolio Allocation: Classical Theory and Modern Extensions

• Chapter 2. Mean-Variance Analysis and Modern Portfolio Theory
• Chapter 3. Transaction and Trading Costs
• Chapter 4. Applying the Portfolio Selection Framework in Practice
• Chapter 5. Incorporating Higher Moments and Extreme Risk Measures
• Chapter 6. Mathematical and Numerical Optimization
  

Part Two: Managing Uncertainty in Practice

• Chapter 7. Equity Price Models
• Chapter 8. Forecasting Expected Return and Risk
• Chapter 9. Robust Frameworks for Estimation and Portfolio Allocation

Part Three: Dynamic Models for Equity Prices

• Chapter 10. Feedback and Predictors in Stock Markets
• Chapter 11. Individual Price Processes: Univariate Models
• Chapter 12. Multivariate Models
• Chapter 13. Model Selection and its Pitfalls
  

Part Four: Model Estimation and Risk Mitigation

• Chapter 14. Estimation of Regression Models
• Chapter 15. Estimation of Linear Dynamic Models
• Chapter 16. Estimation of Hidden Variable Models
• Chapter 17. Model Risk and its Mitigation
  

Appendix A: Differences Equations
Appendix B: Correlations, Regressions, and Copulas
Appendix C: Data Description