pwc-archive/papers-with-abstracts huggingface dataset:
A Langevin model for complex cardiological time series
Date: 2016-02-29 00:00:00
Tasks: model, Time Series, Time Series Analysis

There has been considerable efforts to understand the underlying complex
dynamics in physiological time series. Methods originated from statistical
physics revealed a non-Gaussian statistics and long range correlations in those
signals. This suggests that the regulatory system operates out of equilibrium.
Herein the complex fluctuations in blood pressure time series were successful
described by physiological motivated Langevin equation under a sigmoid
restoring force with multiplicative noise.
Role of short-term dispersal on the dynamics of Zika virus
Date: 2016-03-16 00:00:00

In November 2015, El Salvador reported their first case of Zika virus (Zv)
leading to an explosive outbreak that in just two months had over 6000
suspected cases. Many communities along with national agencies initiated the
process to implement control measures that ranged from vector control and the
use of repellents to the suggestion of avoiding pregnancies for two years, the
latter one, in response to the growing number of microcephaly cases in Brazil.
In our study, we explore the impact of short term mobility between two
idealized interconnected communities where disparities and violence contribute
to the Zv epidemic. Using a Lagrangian modeling approach in a two-patch
setting, it is shown via simulations that short term mobility may be beneficial
in the control of a Zv outbreak when risk is relative low and patch disparities
are not too extreme. However, when the reproductive number is too high, there
seems to be no benefits. This paper is dedicated to the inauguration of the
Centro de Modelamiento Matem\'{a}tico Carlos Castillo-Ch\'{a}vez at Universidad
Francisco Gavidia in San Salvador, El Salvador.
The Kinematics of Plant Nutation Reveals a Simple Relation Between Curvature and the Orientation of Differential Growth
Date: 2016-10-25 00:00:00
Tasks: Relation

Nutation is an oscillatory movement that plants display during their
development. Despite its ubiquity among plants movements, the relation between
the observed movement and the underlying biological mechanisms remains unclear.
Here we show that the kinematics of the full organ in 3D gives a simple picture
of plant nutation, where the orientation of the curvature along the main axis
of the organ aligns with the direction of maximal differential growth. Within
this framework we reexamine the validity of widely used experimental
measurements of the apical tip as markers of growth dynamics. We show that
though this relation is correct under certain conditions, it does not generally
hold, and is not sufficient to uncover the specific role of each mechanism. As
an example we re-interpret previously measured experimental observations using
our model.
Puzzling properties of the historical growth rate of income per capita explained
Date: 2016-04-20 00:00:00

Galor discovered many mysteries of the growth process. He lists them in his
Unified Growth Theory and wonders how they can be explained. Close inspection
of his mysteries reveals that they are of his own creation. They do not exist.
He created them by his habitually distorted presentation of data. One of his
self-created mysteries is the mystery of the alleged sudden spurt in the growth
rate of income per capita. This sudden spurt never happened. In order to
understand the growth rate of income per capita, its mathematical properties
are now explored and explained. The explanation is illustrated using the
historical world economic growth. Galor also wonders about the sudden spurt in
the growth rate of population. We show that this sudden spurt was also created
by the distorted presentation of data. The mechanism of the historical economic
growth and of the growth of human population is yet to be explained but it
would be unproductive to try to explain the non-existing and self-created
mysteries of the growth process described in the scientifically unacceptable
Unified Growth Theory. However, the problem is much deeper than just the
examination of this theory. Demographic Growth Theory is based on the incorrect
but deeply entrenched postulates developed by accretion over many years and now
generally accepted in the economic and demographic research, postulates
revolving around the concept of Malthusian stagnation and around a transition
from stagnation to growth. The study presented here and earlier similar
publications show that these postulates need to be replaced by interpretations
based on the mathematical analysis of data and on the correct understanding of
hyperbolic distributions.
Tipping elements and climate-economic shocks: Pathways toward integrated assessment
Date: 2016-07-11 00:00:00

The literature on the costs of climate change often draws a link between
climatic 'tipping points' and large economic shocks, frequently called
'catastrophes'. The use of the phrase 'tipping points' in this context can be
misleading. In popular and social scientific discourse, 'tipping points'
involve abrupt state changes. For some climatic 'tipping points,' the
commitment to a state change may occur abruptly, but the change itself may be
rate-limited and take centuries or longer to realize. Additionally, the
connection between climatic 'tipping points' and economic losses is tenuous,
though emerging empirical and process-model-based tools provide pathways for
investigating it. We propose terminology to clarify the distinction between
'tipping points' in the popular sense, the critical thresholds exhibited by
climatic and social 'tipping elements,' and 'economic shocks'. The last may be
associated with tipping elements, gradual climate change, or non-climatic
triggers. We illustrate our proposed distinctions by surveying the literature
on climatic tipping elements, climatically sensitive social tipping elements,
and climate-economic shocks, and we propose a research agenda to advance the
integrated assessment of all three.
Proto-Cooperation: group hunting sailfish improve hunting success by alternating attacks on grouping prey
Date: 2016-12-31 00:00:00

We present evidence of a novel form of group hunting. Individual sailfish
(Istiophorus platypterus) alternate attacks with other group members on their
schooling prey (Sardinella aurita). While only 24% of attacks result in prey
capture, multiple prey are injured in 95% of attacks, resulting in an increase
of injured fish in the school with the number of attacks. How quickly prey are
captured is positively correlated with the level of injury of the school,
suggesting that hunters can benefit from other conspecifics' attacks on the
prey. To explore this, we built a mathematical model capturing the dynamics of
the hunt. We show that group hunting provides major efficiency gains (prey
caught per unit time) for individuals in groups of up to 70 members. We also
demonstrate that a free riding strategy, where some individuals wait until the
prey are sufficiently injured before attacking, is only beneficial if the cost
of attacking is high, and only then when waiting times are short. Our findings
provide evidence that cooperative benefits can be realised through the
facilitative effects of individuals' hunting actions without spatial
coordination of attacks. Such "proto-cooperation" may be the pre-cursor to more
complex group-hunting strategies.
The Graph of Our Mind
Date: 2020-03-17 00:00:00
Tasks: Diffusion  MRI, Sociology

Graph theory in the last two decades penetrated sociology, molecular biology,
genetics, chemistry, computer engineering, and numerous other fields of
science. One of the more recent areas of its applications is the study of the
connections of the human brain. By the development of diffusion magnetic
resonance imaging (diffusion MRI), it is possible today to map the connections
between the 1-1.5 cm$^2$ regions of the gray matter of the human brain. These
connections can be viewed as a graph: the vertices are the anatomically
identified regions of the gray matter, and two vertices are connected by an
edge if the diffusion MRI-based workflow finds neuronal fiber tracts between
these areas. This way we can compute 1015-vertex graphs with tens of thousands
of edges. In a previous work, we have analyzed the male and female braingraphs
graph-theoretically, and we have found statistically significant differences in
numerous parameters between the sexes: the female braingraphs are better
expanders, have more edges, larger bipartition widths, and larger vertex cover
than the braingraphs of the male subjects. Our previous study has applied the
data of 96 subjects; here we present a much larger study of 426 subjects. Our
data source is an NIH-founded project, the "Human Connectome Project (HCP)"
public data release. As a service to the community, we have also made all of
the braingraphs computed by us from the HCP data publicly available at the
\url{http://braingraph.org} for independent validation and further
investigations.
Exploring group theory and topology for analyzing the structure of biology
Date: 2020-11-16 00:00:00

The concepts of population and species play a fundamental role in biology.
The existence and precise definition of higher-order hierarchies, such as
division into species, is open to debate among biologists. First, we seek to
show a fractal structure of species. We are able to define a species as a
$p$-Sylow subgroup of a particular community in a single niche, confirmed by
topological analysis. We named this model the patch with zeta dominance (PzDom)
model. Next, the topological nature of the system is carefully examined and for
testing purposes, species density data are used in conjunction with data
derived from liquid-chromatography mass spectrometry of proteins. We confirm
the induction of hierarchy and time through a one-dimensional probability space
with certain topologies. For further clarification of induced fractals
including the relation to renormalization in physics, a theoretical development
is proposed based on a newly identified fact, namely that scaling parameters
for magnetization exactly correspond to imaginary parts of the Riemann zeta
function's nontrivial zeros. A master torus and a Lagrangian/Hamiltonian are
derived expressing fractal structures as a solution for diminishing divergent
terms in renormalization. We will also focus on an application of our developed
model. We extend current PzDom model to the so-called exPzDom model to qualify
population dynamics as a topological matter as a whole, not focusing on
hierarchy. The indicators in the exPzDom model adhere well to the empirical
dynamics of SARS-CoV-2 infected people and align appropriately with actual
policies instituted by the Japanese government. In our patch with zeta
dominance (PzDom) model or its extended version (exPzDom), calculations only
require knowledge of the density of individuals over time.
David vs Goliath (You against the Markets), A Dynamic Programming Approach to Separate the Impact and Timing of Trading Costs
Authors: Ravi Kashyap
Date: 2016-03-03 00:00:00

We develop a fundamentally different stochastic dynamic programming model of trading costs. Built on a strong theoretical foundation, our model provides insights to market participants by splitting the overall move of the security price during the duration of an order into the Market Impact (price move caused by their actions) and Market Timing (price move caused by everyone else) components. We derive formulations of this model under different laws of motion of the security prices, starting with a simple benchmark scenario and extending this to include multiple sources of uncertainty, liquidity constraints due to volume curve shifts and relating trading costs to the spread. We develop a numerical framework that can be used to obtain optimal executions under any law of motion of prices and demonstrate the tremendous practical applicability of our theoretical methodology including the powerful numerical techniques to implement them. Our decomposition of trading costs into Market Impact and Market Timing allows us to deduce the zero sum game nature of trading costs. It holds numerous lessons for dealing with complex systems, wherein reducing the complexity by splitting the many sources of uncertainty can lead to better insights in the decision process.
Securities Lending Strategies: Exclusive Valuations and Auction Bids
Authors: Ravi Kashyap
Date: 2016-03-03 00:00:00
Tasks: Asset Management, Management

We derive valuations of a portfolio of financial instruments from a securities lending perspective, under different assumptions, and show a weighting scheme that converges to the true valuation. We illustrate conditions under which our alternative weighting scheme converges faster to the true valuation when compared to the minimum variance weighting. This weighting scheme is applicable in any situation where multiple forecasts are made and we need a methodology to combine them. Our valuations can be useful either to derive a bidding strategy for an exclusive auction or to design an appropriate auction mechanism, depending on which side of the fence a participant sits (whether the interest is to procure the rights to use a portfolio for making stock loans such as for a lending desk, or, to obtain additional revenue from a portfolio such as from the point of view of a long only asset management firm). Lastly, we run simulations to establish numerical examples for the set of valuations and for various bidding strategies corresponding to different auction settings.
A stochastic model for speciation by mating preferences
Date: 2017-04-18 00:00:00
Tasks: model

Mechanisms leading to speciation are a major focus in evolutionary biology.
In this paper, we present and study a stochastic model of population where
individuals, with type a or A, are equivalent from ecological, demographical
and spatial points of view, and differ only by their mating preference: two
individuals with the same genotype have a higher probability to mate and
produce a viable offspring. The population is subdivided in several patches and
individuals may migrate between them. We show that mating preferences by
themselves, even if they are very small, are enough to entail reproductive
isolation between patches, and we provide the time needed for this isolation to
occur as a function of the population size. Our results rely on a fine study of
the stochastic process and of its deterministic limit in large population,
which is given by a system of coupled nonlinear differential equations.
Besides, we propose several generalisations of our model, and prove that our
findings are robust for those generalisations.
Option spanning beyond $L_p$-models
Date: 2016-09-29 00:00:00

\begin{abstract} The aim of this paper is to study the spanning power of
options in a static financial market that allows non-integrable assets. Our
findings extend and unify the results in [8,9,18] for $L_p$-models. We also
apply the spanning power properties to the pricing problem. In particular, we
show that prices on call and put options of a limited liability asset can be
uniquely extended by arbitrage to all marketed contingent claims written on the
asset.
Hong Kong -- Shanghai Connect / Hong Kong -- Beijing Disconnect (?): Scaling the Great Wall of Chinese Securities Trading Costs
Authors: Ravi Kashyap
Date: 2016-03-04 00:00:00

We utilize a fundamentally different model of trading costs to look at the effect of the opening of the Hong Kong Shanghai Connect that links the stock exchanges in the two cities, arguably the biggest event in international business and finance since Christopher Columbus set sail for India. We design a novel methodology that compensates for the lack of data on trading costs in China. We estimate trading costs across similar positions on the dual listed set of securities in Hong Kong and China, hoping to provide useful pieces of information to help scale 'The Great Wall of Chinese Securities Trading Costs'. We then compare actual and estimated trading costs on a sample of real orders across the Hong Kong securities in the dual listed pair to establish the accuracy of our measurements. The primary question we seek to address is 'Which market would be better to trade to gain exposure to the same (or similar) set of securities or sectors?' We find that trading costs on Shanghai, which might have been lower than Hong Kong, might have become higher leading up to the Connect. What remains to be seen is whether this increase in trading costs is a temporary equilibrium due to the frenzy to gain exposure to Chinese securities or whether this phenomenon will persist once the two markets start becoming more and more tightly coupled. It would be interesting to see if this pioneering policy will lead to securities exchanges across the globe linking up one another, creating a trade anything, anywhere and anytime marketplace. Looking beyond mere trading costs, such studies can be used to gather some evidence on what effect the mode of governance and other aspects of life in one country have on another country, once they start joining up their financial markets.
Cross-response in correlated financial markets: individual stocks
Date: 2016-04-25 00:00:00

Previous studies of the stock price response to trades focused on the
dynamics of single stocks, i.e. they addressed the self-response. We
empirically investigate the price response of one stock to the trades of other
stocks in a correlated market, i.e. the cross-responses. How large is the
impact of one stock on others and vice versa? -- This impact of trades on the
price change across stocks appears to be transient instead of permanent as we
discuss from the viewpoint of market efficiency. Furthermore, we compare the
self-responses on different scales and the self- and cross-responses on the
same scale. We also find that the cross-correlation of the trade signs turns
out to be a short-memory process.
Mathematical analysis of historical income per capita distributions
Date: 2016-04-29 00:00:00

Data describing historical growth of income per capita [Gross Domestic
Product per capita (GDP/cap)] for the world economic growth and for the growth
in Western Europe, Eastern Europe, Asia, former USSR, Africa and Latin America
are analysed. They follow closely the linearly-modulated hyperbolic
distributions represented by the ratios of hyperbolic distributions obtained by
fitting the GDP and population data. Results of this analysis demonstrate that
income per capita was increasing monotonically. There was no stagnation and
there were no transitions from stagnation to growth. The usually postulated
dramatic escapes from the Malthusian trap never happened because there was no
trap. Unified Growth Theory is fundamentally incorrect because its central
postulates are contradicted repeatedly by data, which were used but never
analysed during the formulation of this theory. The large body of
readily-available data opens new avenues for the economic and demographic
research. They show that certain fundamental postulates revolving around the
concept of Malthusian stagnation need to be replaced by the evidence-based
interpretations. Within the range of analysable data, which for the growth of
population extends down to 10,000 BC, growth of human population and economic
growth were hyperbolic. There was no Malthusian stagnation and there were no
transitions to distinctly faster trajectories. Industrial Revolution had no
impact on changing growth trajectories.
Identifying and Improving Dataset References in Social Sciences Full Texts
Authors: Ghavimi Behnam, Mayr Philipp, Vahdati Sahar, Lange Christoph
Date: 2016-03-29 00:00:00

Scientific full text papers are usually stored in separate places than their
underlying research datasets. Authors typically make references to datasets by
mentioning them for example by using their titles and the year of publication.
However, in most cases explicit links that would provide readers with direct
access to referenced datasets are missing. Manually detecting references to
datasets in papers is time consuming and requires an expert in the domain of
the paper. In order to make explicit all links to datasets in papers that have
been published already, we suggest and evaluate a semi-automatic approach for
finding references to datasets in social sciences papers. Our approach does not
need a corpus of papers (no cold start problem) and it performs well on a small
test corpus (gold standard). Our approach achieved an F-measure of 0.84 for
identifying references in full texts and an F-measure of 0.83 for finding
correct matches of detected references in the da|ra dataset registry.
Optimal sequence memory in driven random networks
Date: 2017-09-22 00:00:00

Autonomous randomly coupled neural networks display a transition to chaos at
a critical coupling strength. We here investigate the effect of a time-varying
input on the onset of chaos and the resulting consequences for information
processing. Dynamic mean-field theory yields the statistics of the activity,
the maximum Lyapunov exponent, and the memory capacity of the network. We find
an exact condition that determines the transition from stable to chaotic
dynamics and the sequential memory capacity in closed form. The input
suppresses chaos by a dynamic mechanism, shifting the transition to
significantly larger coupling strengths than predicted by local stability
analysis. Beyond linear stability, a regime of coexistent locally expansive,
but non-chaotic dynamics emerges that optimizes the capacity of the network to
store sequential input.
Emergence and Maintenance of Excitability: Kinetics over Structure
Date: 2016-03-18 00:00:00

Emergence and maintenance of excitability is often phrased in terms of
arriving at and remaining about a manifold of 'solutions' embedded in a high
dimensional parameter space. Alongside studies that extend traditional focus on
control-based regulation of structural parameters (channel densities), there is
a budding interest in self-organization of kinetic parameters. In this picture,
ionic channels are continually forced by activity in-and-out of a large pool of
states not available for the mechanism of excitability. The process, acting on
expressed structure, provides a bed for generation of a spectrum of
excitability modes. Driven by microscopic fluctuations over a broad range of
temporal scales, self-organization of kinetic parameters extends the metaphors
and tools used in the study of development of excitability.