Risk-Return Analysis: Volume 2
Risk Return Analysis: Volume 2 picks up where the first volume left off, with Markowitz’s personal reflections and current strategies. It focuses on the relationship between single-period choices and longer-run goals. Written with both the academic and the practitioner in mind, this richly illustrated volume provides investors, economists, and financial advisors with a refined look at MPT, highlighting the rational decision-making and probability beliefs that are essential to creating and maintaining a successful portfolio today.
Table of Contents
Cover Page
Title Page
Copyright Page
Addendum to Volume I
Contents
Preface
Acknowledgments
Chapter 6. The Portfolio Selection Context
Introduction
Temporal Structure and Today’s Choice
Stakeholders Versus “the Investor”
Investor Roles
Diversification Needs and Opportunities: Recognized and Unrecognized
Agenda: Analysis, Judgment, and Decision Support Systems
Chapter 7. Modeling Dynamic Systems
Introduction
Definitions
The EAS-E Worldview
The Modeling Process
An EAS Example
Graphical Depiction of Attributes
Graphical Depiction of Sets
Further Specifications
Describing Time
Simultaneity
Endogenous Events Versus Endogenous Phenomena
JLMSim Events
Simplicity, Complexity, Reality
The SIMSCRIPT Advantage
GuidedChoice and the Game of Life
The GC DSS Database
Simulator Versus DSS Modeling
Issues and Alternatives
The SIMSCRIPTs
The Process View
Subsidiary Entities
SIMSCRIPT III Features
Continued in Chapter 12
Chapter 8. Game Theory and Dynamic Programming
Introduction
PRWSim (a Possible Real-World Simulator)
Concepts from Game Theory
Non-“Theory of Games” Games
Randomized Strategies
The Utility of a Many-Period Game
Dynamic Programming
Solving Tic-Tac-Toe
Conditional Expected Value: An Example
Generalization
Partitions, Information, and DP Choice: An Example
Generalization: Two Types of Games
The Curse of Dimensionality
Factorization, Simplification, Exploration, and Approximation
Chapter 9. The Mossin-Samuelson Model
Introduction
The MS Model and Its Solution
Markowitz Versus Samuelson: Background
Glide-Path Strategies and Their Rationales
Relative Risk Aversion
The GuidedSavings Utility Function
The Well-Funded Case
A Game-of-Life Utility Function
Chapter 10. Portfolio Selection as a Social Choice
Introduction
Arrow’s Paradox
The Goodman and Markowitz (1952) (GM) Theorems
Social Ordering for RDMs
Hildreth’s Proposal
Markowitz and Blay (MB) Axioms
Arithmetic Versus Geometric Mean Utility
Symmetry Revisited
Rescaling Ploys
Voting Blocks
The Luce, Raiffa, and Nash (LRN) Choice Rule
Nash Symmetry
A Proposal
Liberté, Égalité, Prospérité
Chapter 11. Judgment and Approximation
Introduction
EU Maximization: Exact, Approximate; Explicit, Implicit
The Household as Investor
The Markowitz and van Dijk Methodology
The Blay-Markowitz NPV Analysis
The TCPA Process
Estimating PV Means, Variances, and Covariances
Displaying the Efficient Frontier
Resampled AC/LOC Portfolios
TCPA 1.0 Assumptions
Beyond Markowitz
“Buckets”: A Brief Literature Review
The “Answer Game”
First the Question, Then the Answer
Chapter 12. The Future
Introduction
JSSPG
Proposals
Current Practice
Agenda
Level 6
SIMSCRIPT Facilities
IBM EAS-E Features
Like the Phoenix
Level 7
SIMSCRIPT M Enhancements
Computing: Past, Present, and Future
Von Neumann (1958): The Computer and the Brain
The Computer and the Brain, Revisited
Emulation, Not Replication
Event Invocation of a Third Kind
Processes That Process Processes
Easily Parallelized Processes (EPPs)
Local Resource Groups
Micro Versus Macro Parallelization
Epilogue
Notes
References