A through guide covering Modern Portfolio Theory as well as the recent developments surrounding it Modern portfolio theory (MPT), which originated with Harry Markowitz's seminal paper "Portfolio Selection" in 1952, has stood the test of time and continues to be the intellectual foundation for real-world portfolio management. This book presents a comprehensive picture of MPT in a manner that can be effectively used by financial practitioners and understood by students. Modern Portfolio Theory provides a summary of the important findings from all of the financial research done since MPT was created and presents all the MPT formulas and models using one consistent set of mathematical symbols. Opening with an informative introduction to the concepts of probability and utility theory, it quickly moves on to discuss Markowitz's seminal work on the topic with a thorough explanation of the underlying mathematics. Analyzes portfolios of all sizes and types, shows how the advanced findings and formulas are derived, and offers a concise and comprehensive review of MPT literature Addresses logical extensions to Markowitz's work, including the Capital Asset Pricing Model, Arbitrage Pricing Theory, portfolio ranking models, and performance attribution Considers stock market developments like decimalization, high frequency trading, and algorithmic trading, and reveals how they align with MPT Companion Website contains Excel spreadsheets that allow you to compute and graph Markowitz efficient frontiers with riskless and risky assets If you want to gain a complete understanding of modern portfolio theory this is the book you need to read.
Preface Chapter 1 Introduction 1.1 The Portfolio Management Process 1.2 The Security Analyst's Job 1.3 Portfolio Analysis 1.4 Portfolio Selection 1.5 Mathematics Segregated to Appendices 1.6 Topics To Be Discussed Appendix Various Rates of Return PART One: PROBABILITY FOUNDATIONS Chapter 2 Assessing Risk 2.1 Mathematical Expectation 2.2 What is Risk? 2.3 Expected Return 2.4 Risk of a Security 2.5 Covariance of Returns 2.6 Correlation of Returns 2.7 Using Historical Returns 2.8 Data Input Requirements 2.9 Portfolio Weights 2.10 A Portfolio's Expected Return 2.11 Portfolio Risk 2.12 Summary of Conventions and Formulas Chapter 3 Risk and Diversification: An Overview 3.1 Reconsidering Risk 3.2 Utility Theory 3.3 Risk-Return Space 3.4 Diversification 3.5 Conclusions PART Two: UTILITY FOUNDATIONS Chapter 4 Single-Period Utility Analysis 4.1 Basic Utility Axioms 4.2 The Utility of Wealth Function 4.3 Utility of Wealth and Returns 4.4 Expected Utility of Returns 4.5 Risk Attitudes 4.6 Absolute Risk Aversion 4.7 Relative Risk Aversion 4.8 Measuring Risk Aversion 4.9 Portfolio Analysis 4.10 Indifference Curves 4.11 Summary and Conclusions Appendix PART Three: MEAN-VARIANCE PORTFOLIO ANALYSIS Chapter 5 Graphical Portfolio Analysis 5.1 Delineating Efficient Portfolios 5.2 Portfolio Analysis Inputs 5.3 Two-Asset Isomean Lines 5.4 Two-Asset Isovariance Ellipses 5.5 Three-Asset Portfolio Analysis 5.6 Legitimate Portfolios 5.7 "Unusual" Graphical Solutions Don't Exist 5.8 Representing Constraints Graphically 5.9 The "Interior Decorator Fallacy" 5.10 Summary Appendix Chapter 6 Mathematical Portfolio Analysis 6.1 Risk and Return for Two-Asset Portfolios 6.2 The Opportunity Set 6.3 Markowitz Diversification 6.4 Efficient Frontier Without the Risk-free Asset 6.5 Introducing A Risk-free Asset 6.6 Summary and Conclusions Appendix Equations for a Relationship Between and Chapter 7 Advanced Portfolio Aanalysis Topics 7.1 Efficient Portfolios Without A Risk-Free Asset 7.2 Efficient Portfolios With A Risk-free Asset 7.3 Identifying the Tangency Portfolio 7.4 Summary and Conclusions Appendix Mathematical Derivation of the Efficient Frontier Chapter 8 Index Models and Return Generating Process 8.1 Single-Index Models 8.2 Efficient Frontier and the Single Index Model 8.3 Two-Index Models 8.4 Multi-Index Models 8.5 Concluding Remarks Appendix PART Four: NON-MEAN-VARIANCE PORTFOLIOS Chapter 9 Non-Normal Distributions of Returns 9.1 Stable Paretian Distributions 9.2 The Student-t Distribution 9.3 Mixtures of Normal Distributions 9.4 Poisson Jump-Diffusion Process 9.5 The Log-Normal Distribution 9.6 Conclusions Chapter 10 Non-Mean-Variance Investment Decisions 10.1 Geometric Mean Return Criterion 10.2 The Safety First Criterion 10.3 Semivariance Analysis 10.4 Stochastic Dominance Criterion 10.5 Mean-Variance-Skewness Criterion 10.6 Summary and Concluding Remarks Appendix Chapter 11 Risk Management: Value at Risk 11.1 VaR of a Single Asset 11.2 Portfolio VaR 11.3 Decomposition of A Porfolio's VaR 11.4 Other VaR's 11.5 Methods of Measuring VaR 11.6 Estimation of Volatilities 11.7 Accuracy of VaR Models 11.8 Summary and Conclusions Appendix Delta-Gamma Method PART Five: ASSET PRICING MODELS Chapter 12 The Capital Asset Pricing Model (CAPM) 12.1 Underlying Assumptions 12.2 The Capital Market Line 12.3 The Capital Asset Pricing Model 12.4 Over- and Under-Priced Securities 12.5 The Market Model and the CAPM 12.6 Summary and Concluding Remarks Appendix Derivations of The CAPM Chapter 13 Extensions of the Standard CAPM 13.1 Risk-Free Borrowing or Lending 13.2 Homogeneous Expectations 13.3 Perfect Markets 13.4 Nonmarketable Assets 13.5 Summary and Conclusions Appendix Chapter 14 Empirical Tests of CAPM 14.1 Time-Series Tests of the CAPM 14.2 Cross-Sectional Tests of the CAPM 14.3 Empirical Misspecifications in Cross-Sectional R
