Financial Modeling of the Equity Market

An inside look at modern approaches to modeling equity portfolios Financial Modeling of the Equity Market is the most comprehensive, up-to-date guide to modeling equity portfolios. The book is intended for a wide range of quantitative analysts, practitioners, and students of finance. Without sacrificing mathematical rigor, it presents arguments in a concise and clear style with a wealth of real-world examples and practical simulations. This book presents all the major approaches to single-period return analysis, including modeling, estimation, and optimization issues. It covers both static and dynamic factor analysis, regime shifts, long-run modeling, and cointegration. Estimation issues, including dimensionality reduction, Bayesian estimates, the Black-Litterman model, and random coefficient models, are also covered in depth. Important advances in transaction cost measurement and modeling, robust optimization, and recent developments in optimization with higher moments are also discussed. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm, The Intertek Group. He is a member of the editorial board of the Journal of Portfolio Management. He is also the author of numerous articles and books on financial modeling. Petter N. Kolm, PhD (New Haven, CT and New York, NY), is a graduate student in finance at the Yale School of Management and a financial consultant in New York City. Previously, he worked in the Quantitative Strategies Group of Goldman Sachs Asset Management, where he developed quantitative investment models and strategies.

An inside look at modern approaches to modeling equityportfoliosFinancial Modeling of the Equity Market is themost comprehensive, up-to-date guide to modeling equity portfolios.The book is intended for a wide range of quantitative analystspractitioners, and students of finance. Without sacrificingmathematical rigor, it presents arguments in a concise and clearstyle with a wealth of real-world examples and practicalsimulations. This book presents all the major approaches tosingle-period return analysis, including modeling, estimation, andoptimization issues. It covers both static and dynamic factoranalysis, regime shifts, long-run modeling, and cointegration.Estimation issues, including dimensionality reduction, Bayesianestimates, the Black-Litterman model, and random coefficientmodels, are also covered in depth. Important advances intransaction cost measurement and modeling, robust optimization, andrecent developments in optimization with higher moments are alsodiscussed.Sergio M. Focardi (Paris, France) is a founding partnerof the Paris-based consulting firm, The Intertek Group. He is amember of the editorial board of the Journal of PortfolioManagement. He is also the author of numerous articles and books onfinancial modeling. Petter N. Kolm, PhD (New Haven, CT and NewYork, NY), is a graduate student in finance at the Yale School ofManagement and a financial consultant in New York City. Previouslyhe worked in the Quantitative Strategies Group of Goldman SachsAsset Management, where he developed quantitative investment modelsand strategies.

Preface.Acknowledgments.About the Authors.Chapter 1. Introduction.PART ONE: PORTFOLIO ALLOCATION: CLASSICAL THEORY AND MODERNEXTENSIONS.Chapter 2. Mean-Variance Analysis and Modern PortfolioTheory.Chapter 3. Transaction and Trading Costs.Chapter 4. Applying the Portfolio Selection Framework inPractice.Chapter 5. Incorporating Higher Moments and Extreme RiskMeasures.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 PortfolioAllocation.PART THREE: DYNAIC MODELS FOR EQITY 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 AMD 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.Index.