DRAGON KINGS BLACK
SWANS STOCK MARKET AND ELEPHANT MIGRATION PATTERNS AND WALL STREET WARRIORS
SEE ALSO ( OSCILLONS ) ; http://soundofstars.org/oscillons.htm
dragon kings black
swans stock market and Elephant migration patterns and wall street warriors
Wednesday, June 6, 2018 10:53 AM
From:
"Doc Stars" <doc_starz@yahoo.com>
To:
Raw Message Printable View
Elephant migration patterns and wall street warriors
http://drweidinger.tumblr.com/post/44175860711/elephant-migration-patterns-and-wall-street
DRAGON KINGS & BLACK SWANS
https://wikivisually.com/wiki/Dragon_King_Theory
https://zdoc.site/dragon-kings-mechanisms-statistical-methods-and-empirical.html
LOG PERIODIC SCALING, POWER LAWS, Discrete scale invariance and
complex dimensions
https://arxiv.org/pdf/cond-mat/9707012.pdf
Complex Exponents and Log-Periodic Corrections in Frustrated
Systems
Precursors, aftershocks, criticality and self-organized
criticality
Evidence of Intermittent Cascades
from Discrete Hierarchical Dissipation in Turbulence
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.306.3068&rep=rep1&type=pdf
Evidence of log-periodic oscillations and increasing icequake
activity during the breaking-off of large ice masses
On the nature of the stock market : simulations
and experiments
https://open.library.ubc.ca/cIRcle/collections/ubctheses/831/items/1.0085499
Chapter 6. HIERARCHIES, COMPLEX FRACTAL DIMENSIONS, AND
LOG-PERIODICITY
https://muse.jhu.edu/chapter/1134787
Why Stock Markets Crash
Critical Events in Complex Financial Systems
Didier Sornette
With a new preface by the author
https://press.princeton.edu/titles/11001.html
DOWNLOAD : https://muse.jhu.edu/book/31085
INDEX : https://muse.jhu.edu/chapter/1134793
VIDEOS :
https://www.ted.com/talks/didier_sornette_how_we_can_predict_the_next_financial_crisis
"most explanations other than cooperative self-organization
fail to account for the subtle bubbles by which the markets lay the groundwork
for catastrophe."
The scientific study of complex systems has transformed a wide
range of disciplines in recent years, enabling researchers in both the natural
and social sciences to model and predict phenomena as diverse as earthquakes,
global warming, demographic patterns, financial crises, and the failure of
materials. In this book, Didier Sornette boldly applies his varied experience
in these areas to propose a simple, powerful, and general theory of how, why,
and when stock markets crash.
Most attempts to explain market failures seek to pinpoint
triggering mechanisms that occur hours, days, or weeks before the collapse.
Sornette proposes a radically different view: the underlying cause can be
sought months and even years before the abrupt, catastrophic event in the
build-up of cooperative speculation, which often translates into an
accelerating rise of the market price, otherwise known as a "bubble."
Anchoring his sophisticated, step-by-step analysis in leading-edge physical and
statistical modeling techniques, he unearths remarkable insights and some
predictions--among them, that the "end of the growth era" will occur
around 2050.
Power Laws, Log Periodicity utilized for crash protection
" Emergence Detection" stock market
academic articles related to "emergence",
"complex systems", and/or "complexity science
Beating The Market By Running With
Elephants
Kai Petainen, adjunct finance lecturer and trading floor manager
at the University of Michigan's Ross Graduate School of Business, has spent the
past 10 years building a model to predict which stocks institutional investors
are going to find attractive. By anticipating where the elephants of the
investing world are going to run next, Kai’s Marketocracy model portfolio has
averaged over 15% a year for more than 9 years.
Kai Petainen
https://www.forbes.com/sites/kaipetainen/#28089808bb61
https://ahknaten.mytrackrecord.com/?page=04-00-00-001&member=18
Automatic Emergence Detection in Complex Systems
We provide an alternative definition of emergence in complex
systems derived as follows: Given some target variable, we query its state on the subsystem models learned from corresponding
datasets and group their opinions into majority and minority sets. Then we
observe its state at the entire system level. If its true state (observed over
the entire system) is different from the majority opinion given by subsystems,
we consider this situation as emergent. This is like the one given by
predictive approaches in that it “cannot be predicted even by individuals who
possess thorough knowledge of the parts of this system.”
Experiments on synthetic datasets show that our proposed method
can detect emergence over extant approaches. We also show that our proposed
algorithm has polynomial time complexity for all three phases of learning,
fusion, and reasoning.
https://www.hindawi.com/journals/complexity/2017/3460919/
Elephant movement closely tracks precipitation-driven vegetation
dynamics in a Kenyan forest-savanna landscape...."elephants respond
quickly to changes in forage and water availability, making migrations in
response to both large and small rainfall events. The elevational migration of
individual elephants closely matched the patterns of greening and senescing of
vegetation in their home range. Elephants occupied lower elevations when
vegetation activity was high, whereas they retreated to the evergreen forest at
higher elevations while vegetation senesced. Elephant home ranges decreased in size, and overlapped less with increasing elevation."
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267703/
On the Returns of Trend-Following Trading
Strategies
http://www.usbe.umu.se/digitalAssets/195/195397_ues948.pdf
Elephants threatened by poachers are evolving to become
nocturnal so they can travel safely at night
Normally elephants forage for food and migrate in daylight and
rest at night
But a rise in illegal hunting has forced elephants in Kenya to
change their habits
Most poaching occurs in the daytime, forcing elephants into
nocturnal patterns
African elephant numbers have fallen by around 111,000 to
415,000 over the past decade due to ivory poachers
PDF]Evidence of
Intermittent Cascades from Discrete Hierarchical ...
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.306.3068&rep=rep1...pdf
by WX Zhou - Cited by 44 - Related articles
Wei-Xing Zhou 1 and Didier Sornette 1,2,3 ... mental
log-periodic undulations, associated with up to 5 levels of the .... In section
3, we present the result of our analysis for different .... 6. For a given NL
and M, we perform the average of the 20 time series
...... A. Arneodo, J.-F. Muzy and H. Saleur, Complex fractal dimensions.
[PDF]Significance of log-periodic precursors to financial
crashes - CiteSeerX
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67.8436&rep=rep1...pdf
by D Sornette - 2001 - Cited by 225 -
Related articles
Didier Sornette1,2 and Anders Johansen3. 1 Institute of ...
market crashes are preceded by specific log-periodic patterns ... Section. 6
clarifies the distinction between unconditional (ensemble ... et al (1995)) who
elaborated on this idea using a hierarchical ...... invariance, complex fractal
dimensions and log-periodic.
Discrete scale invariance and complex dimensions
Abstract: We discuss the concept of discrete scale invariance
and how it leads
to complex critical exponents (or dimensions), i.e. to the
log-periodic corrections to
scaling. After their initial suggestion as formal solutions of
renormalization group
equations in the seventies, complex exponents have been studied
in the eighties in
relation to various problems of physics embedded in hierarchical
systems. Only recently
has it been realized that discrete scale invariance and its
associated complex
exponents may appear “spontaneously” in euclidean systems, i.e.
without the need
for a pre-existing hierarchy. Examples are
diffusion-limited-aggregation clusters, rupture
in heterogeneous systems, earthquakes, animals (a generalization
of percolation)
among many other systems. We review the known mechanisms for the
spontaneous
generation of discrete scale invariance and provide an extensive
list of situations where
complex exponents have been found. This is done in order to
provide a basis for a
better fundamental understanding of discrete scale invariance.
The main motivation
to study discrete scale invariance and its signatures is that it
provides new insights
in the underlying mechanisms of scale invariance. It may also be
very interesting for
prediction purposes.
https://arxiv.org/pdf/cond-mat/9707012.pdf
Complex Exponents and Log-Periodic Corrections in Frustrated
Systems
Abstract
Recently, it has been observed that rupture processes in highly
disordered media and earthquakes exhibit universal log-periodic corrections to
scaling. We argue that such corrections should actually be
present in a wide class of disordered systems and provide a theoretical
framework to handle them. At the naivest level, a natural explanation for
log-periodic corrections is discrete scale invariance, a notion qualitatively similar to the concept of “lacunarity”. However
in nature, any such structure would be largely perturbed by disorder. We therefore
investigate first the effect of disorder on the log-periodic corrections.
Remarkably, we find that they are generally robust. We discuss a variety of
disorder associated effects, like renormalization of the log-periodic
frequencies. We then propose a general explanation based on
the fact that a discrete fractal is actually a fractal with complex
dimension, and then that complex critical exponents should generally be
expected in the field theories that describe geometrical systems, because the
latter are non unitary. We discuss detailed features of non unitary theorie,
and present evidence of complex exponents in lattice animals, a simple
geometrical generalization of percolation, which can be argued to be associated
with rupture. Finally, we extend our discussion to more general frustrated
systems. We reemphasize that the non-unitarity, generated here by the averaging
over disorder, can lead to complex exponents, as were actually
found earlier in some $\epsilon$ expansion approaches. More physically,
since replica symmetry breaking is described by an ultrametric tree, it may
naturally lead to discrete scale invariance, albeit not in real space but in
replica space. We then study a dynamical model describing transitions between
states in a hierarchical system of barriers modelling the energy landscape in
the phase space of meanfield spinglasses, that leads again to log-periodic
corrections. We conclude by mentioning a few physical cases where we think
log-periodic corrections should be observable.
Complex Exponents and Log-Periodic... (PDF Download Available).
Available from: https://www.researchgate.net/publication/45245120_Complex_Exponents_and_Log-Periodic_Corrections_in_Frustrated_Systems [accessed
Jun 06 2018].
Lacunarity is a counterpart to the fractal dimension that
describes the texture of a fractal. It has to do with the size distribution of
the holes. Roughly speaking, if a fractal has large gaps or holes, it has high
lacunarity; on the other hand, if a fractal is almost translationally
invariant, it has low lacunarity.
An Introduction to Lacunarity
groups.csail.mit.edu/mac/users/rauch/lacunarity/lacunarity.html
Feedback
About this result
Lacunarity - Wikipedia
https://en.wikipedia.org/wiki/Lacunarity
Lacunarity, from the Latin lacuna meaning "gap" or
"lake", is a specialized term in geometry referring to a measure of
how patterns, especially fractals, fill space, where patterns having more or larger gaps generally have higher lacunarity.
Measuring lacunarity · Box counting lacunarity
Research on Spin Glasses:
http://www.physics.emory.edu/faculty/boettcher/Research/spinglasses.htm
https://www.worldscientific.com/worldscibooks/10.1142/0271
https://www.amazon.com/gp/product/0521447771/103-1447978-4883852?v=glance&n=283155
https://pubs.acs.org/doi/abs/10.1021%2Fcm200281z
Spin glass - Wikipedia
https://en.wikipedia.org/wiki/Spin_glass
A spin glass is a disordered magnet, where the magnetic spins of
the component atoms (the orientation of the north and south magnetic poles in
three-dimensional space) are not aligned in a regular pattern. ... They may
also create situations where more than one geometric arrangement of atoms is
stable.
Introduction to the Theory of Spin Glasses
https://www.brandeis.edu/igert/pdfs/dasguptanotes.pdf
Publications on Quantum Algorithms:
http://www.physics.emory.edu/faculty/boettcher/Publications/publications.htm#SG
dragon kings black
swans stock market and Elephant migration patterns and wall street warriors
Wednesday, June 6, 2018 10:53 AM
From:
"Doc Stars" <doc_starz@yahoo.com>
To:
Raw Message Printable View
Elephant migration patterns and wall street warriors
http://drweidinger.tumblr.com/post/44175860711/elephant-migration-patterns-and-wall-street
DRAGON KINGS & BLACK SWANS
https://wikivisually.com/wiki/Dragon_King_Theory
https://zdoc.site/dragon-kings-mechanisms-statistical-methods-and-empirical.html
LOG PERIODIC SCALING, POWER LAWS, Discrete scale invariance and
complex dimensions
https://arxiv.org/pdf/cond-mat/9707012.pdf
Complex Exponents and Log-Periodic Corrections in Frustrated
Systems
Precursors, aftershocks, criticality and self-organized
criticality
Evidence of Intermittent Cascades
from Discrete Hierarchical Dissipation in Turbulence
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.306.3068&rep=rep1&type=pdf
Evidence of log-periodic oscillations and increasing icequake
activity during the breaking-off of large ice masses
On the nature of the stock market :
simulations and experiments
https://open.library.ubc.ca/cIRcle/collections/ubctheses/831/items/1.0085499
Chapter 6. HIERARCHIES, COMPLEX FRACTAL DIMENSIONS, AND
LOG-PERIODICITY
https://muse.jhu.edu/chapter/1134787
Why Stock Markets Crash
Critical Events in Complex Financial Systems
Didier Sornette
With a new preface by the author
https://press.princeton.edu/titles/11001.html
DOWNLOAD : https://muse.jhu.edu/book/31085
INDEX : https://muse.jhu.edu/chapter/1134793
VIDEOS :
https://www.ted.com/talks/didier_sornette_how_we_can_predict_the_next_financial_crisis
"most explanations other than cooperative self-organization
fail to account for the subtle bubbles by which the markets lay the groundwork
for catastrophe."
The scientific study of complex systems has transformed a wide
range of disciplines in recent years, enabling researchers in both the natural
and social sciences to model and predict phenomena as diverse as earthquakes,
global warming, demographic patterns, financial crises, and the failure of
materials. In this book, Didier Sornette boldly applies his varied experience
in these areas to propose a simple, powerful, and general theory of how, why,
and when stock markets crash.
Most attempts to explain market failures seek to pinpoint
triggering mechanisms that occur hours, days, or weeks before the collapse.
Sornette proposes a radically different view: the underlying cause can be
sought months and even years before the abrupt, catastrophic event in the
build-up of cooperative speculation, which often translates into an
accelerating rise of the market price, otherwise known as a "bubble."
Anchoring his sophisticated, step-by-step analysis in leading-edge physical and
statistical modeling techniques, he unearths remarkable insights and some
predictions--among them, that the "end of the growth era" will occur
around 2050.
Power Laws, Log Periodicity utilized for crash protection
" Emergence Detection" stock market
academic articles related to "emergence",
"complex systems", and/or "complexity science
Beating The Market By Running With
Elephants
Kai Petainen, adjunct finance lecturer and trading floor manager
at the University of Michigan's Ross Graduate School of Business, has spent the
past 10 years building a model to predict which stocks institutional investors
are going to find attractive. By anticipating where the elephants of the
investing world are going to run next, Kai’s Marketocracy model portfolio has
averaged over 15% a year for more than 9 years.
Kai Petainen
https://www.forbes.com/sites/kaipetainen/#28089808bb61
https://ahknaten.mytrackrecord.com/?page=04-00-00-001&member=18
Automatic Emergence Detection in Complex Systems
We provide an alternative definition of emergence in complex
systems derived as follows: Given some target variable, we query its state on the subsystem models learned from corresponding
datasets and group their opinions into majority and minority sets. Then we
observe its state at the entire system level. If its true state (observed over
the entire system) is different from the majority opinion given by subsystems,
we consider this situation as emergent. This is like the one given by
predictive approaches in that it “cannot be predicted even by individuals who
possess thorough knowledge of the parts of this system.”
Experiments on synthetic datasets show that our proposed method
can detect emergence over extant approaches. We also show that our proposed
algorithm has polynomial time complexity for all three phases of learning,
fusion, and reasoning.
https://www.hindawi.com/journals/complexity/2017/3460919/
Elephant movement closely tracks precipitation-driven vegetation
dynamics in a Kenyan forest-savanna landscape...."elephants respond
quickly to changes in forage and water availability, making migrations in
response to both large and small rainfall events. The elevational migration of
individual elephants closely matched the patterns of greening and senescing of
vegetation in their home range. Elephants occupied lower elevations when
vegetation activity was high, whereas they retreated to the evergreen forest at
higher elevations while vegetation senesced. Elephant home ranges decreased in size, and overlapped less with increasing elevation."
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267703/
On the Returns of Trend-Following Trading
Strategies
http://www.usbe.umu.se/digitalAssets/195/195397_ues948.pdf
Elephants threatened by poachers are evolving to become
nocturnal so they can travel safely at night
Normally elephants forage for food and migrate in daylight and
rest at night
But a rise in illegal hunting has forced elephants in Kenya to
change their habits
Most poaching occurs in the daytime, forcing elephants into
nocturnal patterns
African elephant numbers have fallen by around 111,000 to
415,000 over the past decade due to ivory poachers
PDF]Evidence of
Intermittent Cascades from Discrete Hierarchical ...
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.306.3068&rep=rep1...pdf
by WX Zhou - Cited by 44 - Related articles
Wei-Xing Zhou 1 and Didier Sornette 1,2,3 ... mental log-periodic
undulations, associated with up to 5 levels of the .... In section 3, we
present the result of our analysis for different .... 6. For a given NL and M,
we perform the average of the 20 time series ...... A.
Arneodo, J.-F. Muzy and H. Saleur, Complex fractal dimensions.
[PDF]Significance of log-periodic precursors to financial
crashes - CiteSeerX
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.67.8436&rep=rep1...pdf
by D Sornette - 2001 - Cited by 225 -
Related articles
Didier Sornette1,2 and Anders Johansen3. 1 Institute of ...
market crashes are preceded by specific log-periodic patterns ... Section. 6
clarifies the distinction between unconditional (ensemble ... et al (1995)) who
elaborated on this idea using a hierarchical ...... invariance, complex fractal
dimensions and log-periodic.
Discrete scale invariance and complex dimensions
Abstract: We discuss the concept of discrete scale invariance
and how it leads
to complex critical exponents (or dimensions), i.e. to the
log-periodic corrections to
scaling. After their initial suggestion as formal solutions of
renormalization group
equations in the seventies, complex exponents have been studied
in the eighties in
relation to various problems of physics embedded in hierarchical
systems. Only recently
has it been realized that discrete scale invariance and its
associated complex
exponents may appear “spontaneously” in euclidean systems, i.e.
without the need
for a pre-existing hierarchy. Examples are
diffusion-limited-aggregation clusters, rupture
in heterogeneous systems, earthquakes, animals (a generalization
of percolation)
among many other systems. We review the known mechanisms for the
spontaneous
generation of discrete scale invariance and provide an extensive
list of situations where
complex exponents have been found. This is done in order to
provide a basis for a
better fundamental understanding of discrete scale invariance.
The main motivation
to study discrete scale invariance and its signatures is that it
provides new insights
in the underlying mechanisms of scale invariance. It may also be
very interesting for
prediction purposes.
https://arxiv.org/pdf/cond-mat/9707012.pdf
Complex Exponents and Log-Periodic Corrections in Frustrated
Systems
Abstract
Recently, it has been observed that rupture processes in highly
disordered media and earthquakes exhibit universal log-periodic corrections to
scaling. We argue that such corrections should actually be
present in a wide class of disordered systems and provide a theoretical
framework to handle them. At the naivest level, a natural explanation for
log-periodic corrections is discrete scale invariance, a notion qualitatively similar to the concept of “lacunarity”. However
in nature, any such structure would be largely perturbed by disorder. We
therefore investigate first the effect of disorder on the log-periodic
corrections. Remarkably, we find that they are generally robust. We discuss a
variety of disorder associated effects, like renormalization of the
log-periodic frequencies. We then propose a general explanation based on the fact that a discrete fractal is actually a
fractal with complex dimension, and then that complex critical exponents should
generally be expected in the field theories that describe geometrical systems,
because the latter are non unitary. We discuss detailed features of non unitary
theorie, and present evidence of complex exponents in lattice animals, a simple
geometrical generalization of percolation, which can be argued to be associated
with rupture. Finally, we extend our discussion to more general frustrated
systems. We reemphasize that the non-unitarity, generated here by the averaging
over disorder, can lead to complex exponents, as were actually
found earlier in some $\epsilon$ expansion approaches. More physically,
since replica symmetry breaking is described by an ultrametric tree, it may
naturally lead to discrete scale invariance, albeit not in real space but in
replica space. We then study a dynamical model describing transitions between
states in a hierarchical system of barriers modelling the energy landscape in
the phase space of meanfield spinglasses, that leads again to log-periodic
corrections. We conclude by mentioning a few physical cases where we think
log-periodic corrections should be observable.
Complex Exponents and Log-Periodic... (PDF Download Available).
Available from: https://www.researchgate.net/publication/45245120_Complex_Exponents_and_Log-Periodic_Corrections_in_Frustrated_Systems [accessed
Jun 06 2018].
Lacunarity is a counterpart to the fractal dimension that
describes the texture of a fractal. It has to do with the size distribution of
the holes. Roughly speaking, if a fractal has large gaps or holes, it has high
lacunarity; on the other hand, if a fractal is almost translationally
invariant, it has low lacunarity.
An Introduction to Lacunarity
groups.csail.mit.edu/mac/users/rauch/lacunarity/lacunarity.html
Feedback
About this result
Lacunarity - Wikipedia
https://en.wikipedia.org/wiki/Lacunarity
Lacunarity, from the Latin lacuna meaning "gap" or
"lake", is a specialized term in geometry referring to a measure of
how patterns, especially fractals, fill space, where patterns having more or larger gaps generally have higher lacunarity.
Measuring lacunarity · Box counting lacunarity
Research on Spin Glasses:
http://www.physics.emory.edu/faculty/boettcher/Research/spinglasses.htm
https://www.worldscientific.com/worldscibooks/10.1142/0271
https://www.amazon.com/gp/product/0521447771/103-1447978-4883852?v=glance&n=283155
https://pubs.acs.org/doi/abs/10.1021%2Fcm200281z
Spin glass - Wikipedia
https://en.wikipedia.org/wiki/Spin_glass
A spin glass is a disordered magnet, where the magnetic spins of
the component atoms (the orientation of the north and south magnetic poles in
three-dimensional space) are not aligned in a regular pattern. ... They may
also create situations where more than one geometric arrangement of atoms is
stable.
Introduction to the Theory of Spin Glasses
https://www.brandeis.edu/igert/pdfs/dasguptanotes.pdf
Publications on Quantum Algorithms:
http://www.physics.emory.edu/faculty/boettcher/Publications/publications.htm#SG
