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The Portfolio Theorists

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Cover of 'The Portfolio Theorists'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 A Roadmap to Resolve the Big Question
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    Chapter 3 The Early Years of John von Neumann and Oskar Morgenstern
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    Chapter 4 The Times and the Beginning of an Era
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    Chapter 5 The Theory of von Neumann and Morgenstern
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    Chapter 6 Applications and Elaborations of the von Neumann-Morgenstern Model
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    Chapter 7 The Later Life and Legacy of von Neumann and Morgenstern
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    Chapter 8 The Early Years
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    Chapter 9 Friedman and Savage’s Times
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    Chapter 10 The Theory of Friedman and Savage
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    Chapter 11 Applications of the Concept of Subjective Probabilities
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    Chapter 12 Life and Legacy
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    Chapter 13 The Early Years
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    Chapter 14 The Times
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    Chapter 15 Arrow’s Great Idea
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    Chapter 16 Applications of the Contingent Claims Model
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    Chapter 17 Life, Legacy, and the Nobel Prize
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    Chapter 18 The Early Years
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    Chapter 19 The Times and a New Paradigm in Personal Finance
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    Chapter 20 The Theory of an Efficient Portfolio
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    Chapter 21 Applications of Portfolio Theory
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    Chapter 22 Life, Legacy, and the Nobel Prize
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    Chapter 23 Combined Contributions in Portfolio Theory
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    Chapter 24 Conclusions
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Citations

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Title
The Portfolio Theorists
Published by
Springer, December 2011
DOI 10.1057/9780230362307
ISBNs
978-0-230-36230-7, 978-1-349-32431-6
Authors

Colin Read, Read, Colin

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 3 21%
Student > Master 2 14%
Student > Ph. D. Student 2 14%
Lecturer 1 7%
Professor 1 7%
Other 0 0%
Unknown 5 36%
Readers by discipline Count As %
Economics, Econometrics and Finance 4 29%
Chemical Engineering 1 7%
Business, Management and Accounting 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Computer Science 1 7%
Other 1 7%
Unknown 5 36%