pwc-archive/papers-with-abstracts huggingface dataset:
Scenario-based Risk Evaluation
Authors: Ruodu Wang, Johanna F. Ziegel
Date: 2018-08-22 00:00:00
Tasks: Management

Risk measures such as Expected Shortfall (ES) and Value-at-Risk (VaR) have been prominent in banking regulation and financial risk management. Motivated by practical considerations in the assessment and management of risks, including tractability, scenario relevance and robustness, we consider theoretical properties of scenario-based risk evaluation. We propose several novel scenario-based risk measures, including various versions of Max-ES and Max-VaR, and study their properties. We establish axiomatic characterizations of scenario-based risk measures that are comonotonic-additive or coherent and an ES-based representation result is obtained. These results provide a theoretical foundation for the recent Basel III & IV market risk calculation formulas. We illustrate the theory with financial data examples.
HAC Analysis to Explore Clusters within Chronic Comorbid Inpatient Visits
Date: 2018-08-20 00:00:00
Tasks: Clustering

Multimorbidities are associated with significant burden on the healthcare
system and the lack of accurate and pertinent statistical exploratory
techniques have often limited their analysis. Here we employ exploratory
hierarchal agglomerative clustering (HAC) of multimorbidities in the inpatient
population in the state of Ohio. The examination exposed the presence of ten
discrete, clinically pertinent groups of multimorbidities within the Ohio
inpatient population. This method offers an assessable empirical exploration of
the multimorbidities present in a specific geographic populace.
Fitness potentials and qualitative properties of the Wright-Fisher dynamics
Date: 2018-08-22 00:00:00

We present a mechanistic formalism for the study of evolutionary dynamics
models based on the diffusion approximation described by the Kimura Equation.
In this formalism, the central component is the fitness potential, from which
we obtain an expression for the amount of work necessary for a given type to
reach fixation. In particular, within this interpretation, we develop a
graphical analysis --- similar to the one used in classical mechanics ---
providing the basic tool for a simple heuristic that describes both the short
and long term dynamics. As a by-product, we provide a new definition of an
evolutionary stable state in finite populations that includes the case of mixed
populations. We finish by showing that our theory -- rigorous for two types
evolution without mutations-- is also consistent with the multi-type case, and
with the inclusion of rare mutations.
Coprime Sensing via Chinese Remaindering over Quadratic Fields, Part I: Array Designs
Date: 2019-04-29 00:00:00

A coprime antenna array consists of two or more sparse subarrays featuring
enhanced degrees of freedom (DOF) and reduced mutual coupling. This paper
introduces a new class of planar coprime arrays, based on the theory of ideal
lattices. In quadratic number fields, a splitting prime $p$ can be decomposed
into the product of two distinct prime ideals, which give rise to the two
sparse subarrays. Their virtual difference coarray enjoys a quadratic gain in
DOF, thanks to the generalized Chinese Remainder Theorem (CRT). To enlarge the
contiguous aperture of the coarray, we present hole-free symmetric CRT arrays
with simple closed-form expressions. The ring of Gaussian integers and the ring
of Eisenstein integers are considered as examples to demonstrate the procedure
of designing coprime arrays. With Eisenstein integers, our design yields a
difference coarray that is a subset of the hexagonal lattice, offering a
significant gain in DOF over the rectangular lattice, given the same physical
areas.
Coprime Sensing via Chinese Remaindering over Quadratic Fields, Part II: Generalizations and Applications
Date: 2019-04-29 00:00:00

The practical application of a new class of coprime arrays based on the
Chinese remainder theorem (CRT) over quadratic fields is presented in this
paper. The proposed CRT arrays are constructed by ideal lattices embedded from
coprime quadratic integers. The geometrical constructions and theoretical
foundations were discussed in the accompanying paper in great detail, while
this paper focuses on aspects of the application of the proposed arrays in
two-dimensional (2D) remote sensing. A generalization of CRT arrays based on
two or more pairwise coprime ideal lattices is proposed with closed-form
expressions on sensor locations, the total number of sensors and the achievable
DOF. The issues pertaining to the coprimality of any two quadratic integers are
also addressed to explore all possible ideal lattices. Exploiting the symmetry
of lattices, sensor reduction methods are discussed with the coarray remaining
intact for economic maximization. In order to extend conventional angle
estimation techniques based on uniformly distributed arrays to the method that
can exploit any coarray configurations based on lattices, this paper introduces
a hexagon-to-rectangular transformation to 2D spatial smoothing, providing the
possibility of finding more compact sensor arrays. Examples are provided to
verify the feasibility of the proposed methods.
Transcriptional Activation of Elephant Shark Mineralocorticoid Receptor by Corticosteroids, Progesterone and Spironolactone
Date: 2018-08-22 00:00:00

We report the analysis of activation by corticosteroids and progesterone of
full-length mineralocorticoid receptor (MR) from elephant shark, a
cartilaginous fish belonging to the oldest group of jawed vertebrates. Based on
their measured activities, aldosterone, cortisol, 11-deoxycorticosterone,
corticosterone, 11-deoxcortisol, progesterone and 19-norprogesterone are
potential physiological mineralocorticoids. However, aldosterone, the
physiological mineralocorticoid in humans and other terrestrial vertebrates, is
not found in cartilaginous or ray-finned fishes. Because progesterone is a
precursor for corticosteroids that activate elephant shark MR, we propose that
progesterone was an ancestral ligand for elephant shark MR. Although
progesterone activates ray-finned fish MRs, progesterone does not activate
human, amphibian or alligator MRs, suggesting that during the transition to
terrestrial vertebrates, progesterone lost the ability to activate the MR.
Comparison of RNA-sequence analysis of elephant shark MR with that of human MR
suggests that MR expression in the human brain, heart, ovary, testis and other
non-epithelial tissues evolved in cartilaginous fishes. Together, these data
suggest that progesterone-activated MR may have unappreciated functions in
elephant shark ovary and testis.
The multistationarity structure of networks with intermediates and a binomial core network
Date: 2019-08-23 00:00:00

This work addresses whether a reaction network, taken with mass-action
kinetics, is multistationary, that is, admits more than one positive steady
state in some stoichiometric compatibility class. We build on previous work on
the effect that removing or adding intermediates has on multistationarity, and
also on methods to detect multistationarity for networks with a binomial steady
state ideal. In particular, we provide a new determinant criterion to decide
whether a network is multistationary, which applies when the network obtained
by removing intermediates has a binomial steady state ideal. We apply this
method to easily characterize which subsets of complexes are responsible for
multistationarity; this is what we call the \emph{multistationarity structure}
of the network. We use our approach to compute the multistationarity structure
of the $n$-site sequential distributive phosphorylation cycle for arbitrary n.
Generalizations of the 'Linear Chain Trick': Incorporating more flexible dwell time distributions into mean field ODE models
Date: 2018-08-22 00:00:00

Mathematical modelers have long known of a "rule of thumb" referred to as the
Linear Chain Trick (LCT; aka the Gamma Chain Trick): a technique used to
construct mean field ODE models from continuous-time stochastic state
transition models where the time an individual spends in a given state (i.e.,
the dwell time) is Erlang distributed (i.e., gamma distributed with integer
shape parameter). Despite the LCT's widespread use, we lack general theory to
facilitate the easy application of this technique, especially for complex
models. This has forced modelers to choose between constructing ODE models
using heuristics with oversimplified dwell time assumptions, using time
consuming derivations from first principles, or to instead use non-ODE models
(like integro-differential equations or delay differential equations) which can
be cumbersome to derive and analyze. Here, we provide analytical results that
enable modelers to more efficiently construct ODE models using the LCT or
related extensions. Specifically, we 1) provide novel extensions of the LCT to
various scenarios found in applications; 2) provide formulations of the LCT and
it's extensions that bypass the need to derive ODEs from integral or stochastic
model equations; and 3) introduce a novel Generalized Linear Chain Trick (GLCT)
framework that extends the LCT to a much broader family of distributions,
including the flexible phase-type distributions which can approximate
distributions on $\mathbb{R}^+$ and be fit to data. These results give modelers
more flexibility to incorporate appropriate dwell time assumptions into mean
field ODEs, including conditional dwell time distributions, and these results
help clarify connections between individual-level stochastic model assumptions
and the structure of corresponding mean field ODEs.
Analysis of Malaria Control Measures Effectiveness Using Multi-Stage Vector Model
Date: 2018-08-22 00:00:00

We analyze an epidemiological model to evaluate the effectiveness of multiple
means of control in malaria-endemic areas. The mathematical model consists of a
system of several ordinary differential equations, and is based on a
multicompartment representation of the system. The model takes into account the
mutliple resting-questing stages undergone by adult female mosquitos during the
period in which they function as disease vectors. We compute the basic
reproduction number $\mathcal R_0$, and show that that if $\mathcal R_0<1$, the
disease free equilibrium (DFE) is globally asymptotically stable (GAS) on the
non-negative orthant. If $\mathcal R_0>1$, the system admits a unique endemic
equilibrium (EE) that is GAS. We perform a sensitivity analysis of the
dependence of $\mathcal R_0$ and the EE on parameters related to control
measures, such as killing effectiveness and bite prevention. Finally, we
discuss the implications for a comprehensive, cost-effective strategy for
malaria control.
Multiple Sequence Alignment is not a Solved Problem
Date: 2018-08-23 00:00:00
Tasks: Multiple Sequence Alignment

Multiple sequence alignment is a basic procedure in molecular biology, and it
is often treated as being essentially a solved computational problem. However,
this is not so, and here I review the evidence for this claim, and outline the
requirements for a solution. The goal of alignment is often stated to be to
juxtapose nucleotides (or their derivatives, such as amino acids) that have
been inherited from a common ancestral nucleotide (although other goals are
also possible). Unfortunately, this is not an operational definition, because
homology (in this sense) refers to unique and unobservable historical events,
and so there can be no objective mathematical function to optimize.
Consequently, almost all algorithms developed for multiple sequence alignment
are based on optimizing some sort of compositional similarity (similarity =
homology + analogy). As a result, many, if not most, practitioners either
manually modify computer-produced alignments or they perform de novo manual
alignment, especially in the field of phylogenetics. So, if homology is the
goal, then multiple sequence alignment is not yet a solved computational
problem. Several criteria have been developed by biologists to help them
identify potential homologies (compositional, ontogenetic, topographical and
functional similarity, plus conjunction and congruence), and these criteria can
be applied to molecular data, in principle. Current computer programs do
implement one (or occasionally two) of these criteria, but no program
implements them all. What is needed is a program that evaluates all of the
evidence for the sequence homologies, optimizes their combination, and thus
produces the best hypotheses of homology. This is basically an inference
problem not an optimization problem.
Tunable Eight-Element MIMO Antenna Based on the Antenna Cluster Concept
Date: 2018-08-21 00:00:00

Realizing capacity demands of future wireless communications requires
improved spectral efficiency in the sub-6-GHz frequency bands. This paper
proposes a novel eight-element multiple-input multiple-output (MIMO) antenna
that can be tuned from 1.7 to 6 GHz. The design is based on the antenna cluster
concept, where weighted feeding of multiple antenna elements is used to modify
the operating frequency. This paper extends the theory of the concept to
account for multiple separate clusters, thus enabling it to be used for MIMO.
The proposed antenna achieves over 60% efficiency at frequencies above 3 GHz,
and the system exceeds the ergodic capacity of the ideal 7x7 MIMO in that band.
Inter-state switching in stochastic gene expression: Exact solution, an adiabatic limit and oscillations in molecular distributions
Authors: K. G. Petrosyan
Date: 2018-08-23 00:00:00
Tasks: Gaussian Processes

We consider the stochastic gene expression process with inter-state flip-flops. An exact steady-state solution to the master equation is calculated. One of the main goals in this paper is to investigate whether the probability distribution of gene copies contains even-odd number oscillations. A master equation previously derived in the adiabatic limit of fast switching by Kepler and Elston \cite{kepler} suggests that the oscillations should be present. However our analysis demonstrates that the oscillations do not happen not only in the adiabatic case but they are entirely absent. We discuss the adiabatic approximation in detail. The other goal is to establish the master equation that takes into account external fluctuations that is similar to the master equation in the adiabatic approximation. The equation allows even-odd oscillations. The reason the behaviour occurs is an underlying interference of Poisson and Gaussian processes. The master equation contains an extra term that describes the gene copy number unconventional diffusion and is responsible for the oscillations. We also point out to a similar phenomenon in quantum physics.
Persistence and extinction for stochastic ecological models with internal and external variables
Date: 2019-03-26 00:00:00

The dynamics of species' densities depend both on internal and external
variables. Internal variables include frequencies of individuals exhibiting
different phenotypes or living in different spatial locations. External
variables include abiotic factors or non-focal species. These internal or
external variables may fluctuate due to stochastic fluctuations in
environmental conditions. We prove theorems for stochastic persistence and
exclusion for stochastic ecological difference equations accounting for
internal and external variables. Specifically, we use a stochastic analog of
average Lyapunov functions to develop sufficient and necessary conditions for
(i) all population densities spending little time at low densities, and (ii)
population trajectories asymptotically approaching the extinction set with
positive probability. For (i) and (ii), respectively, we provide quantitative
estimates on the fraction of time that the system is near the extinction set,
and the probability of asymptotic extinction as a function of the initial state
of the system. Furthermore, we provide lower bounds for the expected time to
escape neighborhoods of the extinction set. To illustrate the applicability of
our results, we analyze stochastic models of evolutionary games, Lotka-Volterra
dynamics, trait evolution, and spatially structured disease dynamics. Our
analysis of these models demonstrates environmental stochasticity facilitates
coexistence of strategies in the hawk-dove game, but inhibits coexistence in
the rock-paper-scissors game and a Lotka-Volterra predator-prey model.
Furthermore, environmental fluctuations with positive auto-correlations can
promote persistence of evolving populations and persistence of diseases in
patchy landscapes. While our results help close the gap between the persistence
theories for deterministic and stochastic systems, we highlight challenges for
future research.
On the Normality of Negative Interest Rates
Date: 2018-08-23 00:00:00

We argue that a negative interest rate policy (NIRP) can be an effect tool
for macroeconomic stabilization. We first discuss how implementing negative
rates on reserves held at a central bank does not pose any theoretical
difficulty, with a reduction in rates operating in exactly the same way when
rates are positive or negative, and show that this is compatible with an
endogenous money point of view. We then propose a simplified stock-flow
consistent macroeconomic model where rates are allowed to become arbitrarily
negative and present simulation evidence for their stabilizing effects. In
practice, the existence of physical cash imposes a lower bound for interest
rates, which in our view is the main reason for the lack of effectiveness of
negative interest rates in the countries that adopted them as part of their
monetary policy. We conclude by discussing alternative ways to overcome this
lower bound , in particular the use of central bank digital currencies.
The Structure of Equilibria in Trading Networks with Frictions
Date: 2020-06-30 00:00:00

Several structural results for the set of competitive equilibria in trading
networks with frictions are established: The lattice theorem, the rural
hospitals theorem, the existence of side-optimal equilibria, and a
group-incentive-compatibility result hold with imperfectly transferable utility
and in the presence of frictions. While our results are developed in a trading
network model, they also imply analogous (and new) results for exchange
economies with combinatorial demand and for two-sided matching markets with
transfers.
A Closed-Form Approximation of the Gaussian Noise Model in the Presence of Inter-Channel Stimulated Raman Scattering
Date: 2018-08-27 00:00:00
Tasks: Form, Numerical Integration

An accurate, closed-form expression evaluating the nonlinear interference
(NLI) power in coherent optical transmission systems in the presence of
inter-channel stimulated Raman scattering (ISRS) is derived. The analytical
result enables a rapid estimate of the signal-to-noise ratio (SNR) and avoids
the need for integral evaluations and split-step simulations. The formula also
provides new insight into the underlying parameter dependence of ISRS on the
NLI. The proposed result is applicable for dispersion unmanaged, ultra-wideband
transmission systems that use optical bandwidths of up to 15 THz. The accuracy
of the closed-form expression is compared to numerical integration of the ISRS
Gaussian Noise model and split-step simulations in a point-to-point
transmission, as well as in a mesh optical network scenario.
Black Magic Investigation Made Simple: Monte Carlo Simulations and Historical Back Testing of Momentum Cross-Over Strategies Using FRACTI Patterns
Date: 2018-08-23 00:00:00

To promote economic stability, finance should be studied as a hard science,
where scientific methods apply. When a trading strategy is proposed, the
underlying model should be transparent and defined robustly to allow other
researchers to understand and examine it thoroughly. Like any hard sciences,
results must be repeatable to allow researchers to collaborate, and build upon
each other's results. Large-scale collaboration, when applying the steps of
scientific investigation, is an efficient way to leverage "crowd science" to
accelerate research in finance. In this paper, we demonstrate how a real world
problem in economics, an old problem still subject to a lot of debate, can be
solved by the application of a crowd-powered, collaborative scientific
computational framework, fully supporting the process of investigation dictated
by the modern scientific method. This paper provides a real end-to-end example
of investigation to illustrate the use of the framework. We intentionally
selected an example that is self-contained, complete, simple, accessible, and
of constant debate in both academia and the industry: the performance of a
trading strategy used commonly in technical analysis. Claims of efficiency in
technical analysis, referred derisively by some sources as "Black Magic", are
of widespread use in mainstream media and usually met with a lot of
controversy. In this paper we show that different researchers assess this
strategy differently, and the subsequent debate is due more to the lack of
method than purpose. Most results reported are not repeatable by other
researchers. This is not satisfactory if we intend to approach finance as a
hard science. To counterweight the status quo, we demonstrate what one could do
by using collaborative and investigative features of contributions and
leveraging the power of crowds.
Supporting Crowd-Powered Science in Economics: FRACTI, a Conceptual Framework for Large-Scale Collaboration and Transparent Investigation in Financial Markets
Date: 2018-08-23 00:00:00

Modern investigation in economics and in other sciences requires the ability
to store, share, and replicate results and methods of experiments that are
often multidisciplinary and yield a massive amount of data. Given the
increasing complexity and growing interaction across diverse bodies of
knowledge it is becoming imperative to define a platform to properly support
collaborative research and track origin, accuracy and use of data. This paper
starts by defining a set of methods leveraging scientific principles and
advocating the importance of those methods in multidisciplinary, computer
intensive fields like computational finance. The next part of this paper
defines a class of systems called scientific support systems, vis-a-vis usages
in other research fields such as bioinformatics, physics and engineering. We
outline a basic set of fundamental concepts, and list our goals and motivation
for leveraging such systems to enable large-scale investigation, "crowd powered
science", in economics. The core of this paper provides an outline of FRACTI in
five steps. First we present definitions related to scientific support systems
intrinsic to finance and describe common characteristics of financial use
cases. The second step concentrates on what can be exchanged through the
definition of shareable entities called contributions. The third step is the
description of a classification system for building blocks of the conceptual
framework, called facets. The fourth step introduces the meta-model that will
enable provenance tracking and representation of data fragments and simulation.
Finally we describe intended cases of use to highlight main strengths of
FRACTI: application of the scientific method for investigation in computational
finance, large-scale collaboration and simulation.
Deep demosaicking for multispectral filter arrays
Date: 2018-10-22 00:00:00
Tasks: Demosaicking

We propose a novel demosaicking method for multispectral filter arrays based
on a deep convolutional neural network. The proposed method first interpolates
mosaicked multispectral images utilizing a bilinear approach, then applies a
residual network to initial demosaicked images. The residual network consists
of various three-dimensional convolutional layers and a rectified linear unit
for describing the features of a multispectral data cube. Experimental results
reveal that the proposed method outperforms conventional demosaicking methods.