Risk-Return Analysis, Volume 2: The Theory and Practice of Rational Investing

Table of contents

1. Cover Page
2. Title Page
3. Copyright Page
4. Addendum to Volume I
5. Contents
6. Preface
7. Acknowledgments
8. Chapter 6. The Portfolio Selection Context
   1. Introduction
   2. Temporal Structure and Today’s Choice
   3. Stakeholders Versus “the Investor”
   4. Investor Roles
   5. Diversification Needs and Opportunities: Recognized and Unrecognized
   6. Agenda: Analysis, Judgment, and Decision Support Systems
9. Chapter 7. Modeling Dynamic Systems
   1. Introduction
   2. Definitions
   3. The EAS-E Worldview
   4. The Modeling Process
   5. An EAS Example
   6. Graphical Depiction of Attributes
   7. Graphical Depiction of Sets
   8. Further Specifications
   9. Describing Time
   10. Simultaneity
   11. Endogenous Events Versus Endogenous Phenomena
   12. JLMSim Events
   13. Simplicity, Complexity, Reality
   14. The SIMSCRIPT Advantage
   15. GuidedChoice and the Game of Life
   16. The GC DSS Database
   17. Simulator Versus DSS Modeling
   18. Issues and Alternatives
   19. The SIMSCRIPTs
   20. The Process View
   21. Subsidiary Entities
   22. SIMSCRIPT III Features
   23. Continued in Chapter 12
10. Chapter 8. Game Theory and Dynamic Programming
    1. Introduction
    2. PRWSim (a Possible Real-World Simulator)
    3. Concepts from Game Theory
    4. Non-“Theory of Games” Games
    5. Randomized Strategies
    6. The Utility of a Many-Period Game
    7. Dynamic Programming
    8. Solving Tic-Tac-Toe
    9. Conditional Expected Value: An Example
    10. Generalization
    11. Partitions, Information, and DP Choice: An Example
    12. Generalization: Two Types of Games
    13. The Curse of Dimensionality
    14. Factorization, Simplification, Exploration, and Approximation
11. Chapter 9. The Mossin-Samuelson Model
    1. Introduction
    2. The MS Model and Its Solution
    3. Markowitz Versus Samuelson: Background
    4. Glide-Path Strategies and Their Rationales
    5. Relative Risk Aversion
    6. The GuidedSavings Utility Function
    7. The Well-Funded Case
    8. A Game-of-Life Utility Function
12. Chapter 10. Portfolio Selection as a Social Choice
    1. Introduction
    2. Arrow’s Paradox
    3. The Goodman and Markowitz (1952) (GM) Theorems
    4. Social Ordering for RDMs
    5. Hildreth’s Proposal
    6. Markowitz and Blay (MB) Axioms
    7. Arithmetic Versus Geometric Mean Utility
    8. Symmetry Revisited
    9. Rescaling Ploys
    10. Voting Blocks
    11. The Luce, Raiffa, and Nash (LRN) Choice Rule
    12. Nash Symmetry
    13. A Proposal
    14. Liberté, Égalité, Prospérité
13. Chapter 11. Judgment and Approximation
    1. Introduction
    2. EU Maximization: Exact, Approximate; Explicit, Implicit
    3. The Household as Investor
    4. The Markowitz and van Dijk Methodology
    5. The Blay-Markowitz NPV Analysis
    6. The TCPA Process
    7. Estimating PV Means, Variances, and Covariances
    8. Displaying the Efficient Frontier
    9. Resampled AC/LOC Portfolios
    10. TCPA 1.0 Assumptions
    11. Beyond Markowitz
    12. “Buckets”: A Brief Literature Review
    13. The “Answer Game”
    14. First the Question, Then the Answer
14. Chapter 12. The Future
    1. Introduction
    2. JSSPG
    3. Proposals
    4. Current Practice
    5. Agenda
    6. Level 6
    7. SIMSCRIPT Facilities
    8. IBM EAS-E Features
    9. Like the Phoenix
    10. Level 7
    11. SIMSCRIPT M Enhancements
    12. Computing: Past, Present, and Future
    13. Von Neumann (1958): The Computer and the Brain
    14. The Computer and the Brain, Revisited
    15. Emulation, Not Replication
    16. Event Invocation of a Third Kind
    17. Processes That Process Processes
    18. Easily Parallelized Processes (EPPs)
    19. Local Resource Groups
    20. Micro Versus Macro Parallelization
    21. Epilogue
15. Notes
16. References
17. Index