Redefining Risk & Return: The Economic Red Phone Explained

165 Pages·2017·2.13 MB·English

by  Jesper Lyng Jensen

REDEFINING
RISK & RETURN
The Economic Red Phone Explained
Jesper Lyng Jensen
Co-author: Susanne Sublett
Redefining Risk & Return
Jesper Lyng Jensen • Susanne Sublett
Redefining Risk &
Return
The Economic Red Phone Explained
Jesper Lyng Jensen Susanne Sublett
Kirke Hyllinge, Denmark Hørve, Denmark
ISBN 978-3-319-41368-6 ISBN 978-3-319-41369-3 (eBook)
DOI 10.1007/978-3-319-41369-3
Library of Congress Control Number: 2016962052
© The Editor(s) (if applicable) and The Author(s) 2017
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It is extremely advantageous to be able to bring a number of investigations
under the formula of a single problem. For in this manner, we not only
facilitate our own labour, inasmuch as we define it clearly to ourselves, but
also make it easier for others to decide whether we have done justice to our
undertaking.
Emmanuel Kant, 1781, Critique of Pure Reason
Preface
The journey from experiment to book has taken nine years. It has been
an interesting journey, and it has been a privilege to receive the assistance
of a great many fantastic people in the process.
Claus Due Ponsaing and Jens B. A. Winther have been invaluable
partners in the work of writing this book and the scientific publications.
I owe both of you my deepest gratitude.
Special thanks go to Niels Thygesen and Mogens Lykketoft for having admi-
rably furthered the work of writing this book. You have opened many doors,
participated in discussions, and frequently given your professional input.
Many people have contributed to the writing of this book. During the
five years I have taken to write the book, friends, family, and people from
my network have helped with proofreading, commented on the contents,
or put me in touch with people who were able to help in different ways,
and I would like to thank them all. I should like to thank in particu-
lar Susanne Sublett, Gitte Harbo Vanderhaegen, Thomas Iversen, Sune
Kliborg Lynge, Mettelene Jellinggaard, and Christian Wichers.
I should also like to thank Jan Als Johansen for his helpfulness and
excellent linguistic consulting services.
Finally, I should like to thank my family, Dorte, Asger, and Amanda,
for being so patient with me and for believing in me over the years when
I have worked on the book and the research during my spare time.
vii
viii Preface
Jesper Lyng Jensen Holding Jesper Lyng Jensen
Kirke Hyllinge, Denmark
[email protected]
IBM Susanne Sublett
Hørve, Denmark
[email protected]
Contents
1 Introduction 1
2 How to Read a Monte Carlo Simulation Graph 9
3 Introduction to the Cost of Running
Out of Capital 15
4 Risk and Uncertainty 19
5 The Cost of Running Out of Capital 29
6 Capital 53
7 Insurance 71
8 The Different Costs of Risk 95
9 Stock Taking 99
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x Contents
10 Macroeconomics 107
11 Self-Chosen Risk and Government Intervention 127
12 The Top Ten Most Important Realisations
Regarding Structural Risk 135
13 The Cost of Structural Risk Management in Liberalism 141
14 How Is This Book to Be Understood and What
Kind of Society Does It Wish to Create? 147
Bibliography 151
Index 155
List of Figures
Fig. 1.1 The book “Redefining Risk & Return” contributes to the
description of economic risk, demonstrating how the
theory fits in with a number of interfaces of the existing
regimen of theories and with society. Accordingly, the
book should be seen as an argument to support our claim
that we have actually found an important, previously
missing piece in our understanding of how risk is included in
decisions to optimize conditions for social economic growth 5
Fig. 2.1 Graphical representation of a ten-sided die 11
Fig. 2.2 This graph shows the result of a Monte Carlo simulation
of a 10% risk of a DKK 200,000 cost. The graph has two
gray frequency columns. As can be seen, one is much taller
than the other. The tall column is at the 0 point on the
X-axis, while the short column is at the interval on the
X-axis that goes from DKK 192,000 to DKK 200,000.
The dotted graph is the accumulated probability graph.
The dotted line is generated by taking the observations at a
given value on the X-axis and dividing this figure by the
number of all observations, while multiplying it by 100
to get the result as a percentage 12
Fig. 2.3 A Monte Carlo simulation of a risk owner’s risk situation as
described in Table 2.1 A total of 5,000 simulations were made.
The graph shows the result of these simulations in the form of the
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