pwc-archive/papers-with-abstracts huggingface dataset:
Pricing European and American Options under Heston Model using Discontinuous Galerkin Finite Elements
Authors: Sinem Kozpınar, Murat Uzunca, Bülent Karasözen
Date: 2016-05-31 00:00:00

This paper deals with pricing of European and American options, when the underlying asset price follows Heston model, via the interior penalty discontinuous Galerkin finite element method (dGFEM). The advantages of dGFEM space discretization with Rannacher smoothing as time integrator with nonsmooth initial and boundary conditions are illustrated for European vanilla options, digital call and American put options. The convection dominated Heston model for vanishing volatility is efficiently solved utilizing the adaptive dGFEM. For fast solution of the linear complementary problem of the American options, a projected successive over relaxation (PSOR) method is developed with the norm preconditioned dGFEM. We show the efficiency and accuracy of dGFEM for option pricing by conducting comparison analysis with other methods and numerical experiments.
The Apps You Use Bring The Blogs to Follow
Authors: Shi Yue, Zhong Erheng, Rajan Suju, Dong Liang, Tseng Hao-wei, Li Beitao
Date: 2016-06-27 00:00:00

We tackle the blog recommendation problem in Tumblr for mobile users in this
paper. Blog recommendation is challenging since most mobile users would suffer
from the cold start when there are only a limited number of blogs followed by
the user. Specifically to address this problem in the mobile domain, we take
into account mobile apps, which typically provide rich information from the
users. Based on the assumption that the user interests can be reflected from
their app usage patterns, we propose to exploit the app usage data for
improving blog recommendation. Building on the state-of-the-art recommendation
framework, Factorization Machines (FM), we implement app-based FM that
integrates app usage data with the user-blog follow relations. In this approach
the blog recommendation is generated not only based on the blogs that the user
followed before, but also the apps that the user has often used. We demonstrate
in a series of experiments that app-based FM can outperform other alternative
approaches to a significant extent. Our experimental results also show that
exploiting app usage information is particularly effective for improving blog
recommendation quality for cold start users.
Event Identification in Social Networks
Authors: Zarrinkalam Fattane, Bagheri Ebrahim
Date: 2016-06-28 00:00:00
Tasks: Event Detection

Social networks enable users to freely communicate with each other and share
their recent news, ongoing activities or views about different topics. As a
result, they can be seen as a potentially viable source of information to
understand the current emerging topics/events. The ability to model emerging
topics is a substantial step to monitor and summarize the information
originating from social sources. Applying traditional methods for event
detection which are often proposed for processing large, formal and structured
documents, are less effective, due to the short length, noisiness and
informality of the social posts. Recent event detection techniques address
these challenges by exploiting the opportunities behind abundant information
available in social networks. This article provides an overview of the state of
the art in event detection from social networks.
Static Ranking of Scholarly Papers using Article-Level Eigenfactor (ALEF)
Authors: Wesley-Smith Ian, Bergstrom Carl T., West Jevin D.
Date: 2016-06-28 00:00:00
Tasks: Articles

Microsoft Research hosted the 2016 WSDM Cup Challenge based on the Microsoft
Academic Graph. The goal was to provide static rankings for the articles that
make up the graph, with the rankings to be evaluated against those of human
judges. While the Microsoft Academic Graph provided metadata about many aspects
of each scholarly document, we focused more narrowly on citation data and used
this contest as an opportunity to test the Article Level Eigenfactor (ALEF), a
novel citation-based ranking algorithm, and evaluate its performance against
competing algorithms that drew upon multiple facets of the data from a large,
real world dataset (122M papers and 757M citations). Our final submission to
this contest was scored at 0.676, earning second place.
On the mathematical consequences of binning spike trains
Date: 2016-06-28 00:00:00

We initiate a mathematical analysis of hidden effects induced by binning
spike trains of neurons. Assuming that the original spike train has been
generated by a discrete Markov process, we show that binning generates a
stochastic process which is not Markov any more, but is instead a Variable
Length Markov Chain (VLMC) with unbounded memory. We also show that the law of
the binned raster is a Gibbs measure in the DLR (Dobrushin-Lanford-Ruelle)
sense coined in mathematical statistical mechanics. This allows the derivation
of several important consequences on statistical properties of binned spike
trains. In particular, we introduce the DLR framework as a natural setting to
mathematically formalize anticipation, i.e. to tell "how good" our nervous
system is at making predictions. In a probabilistic sense, this corresponds to
condition a process by its future and we discuss how binning may affect our
conclusions on this ability. We finally comment what could be the consequences
of binning in the detection of spurious phase transitions or in the detection
of wrong evidences of criticality.
Reanalyzing variable directionality of gene expression in transgenerational epigenetic inheritance
Date: 2016-06-28 00:00:00

A previous report claimed no evidence of transgenerational epigenetic
inheritance in a mouse model of in utero environmental exposure, based on the
observation that gene expression changes observed in the germ cells of G1 and
G2 male fetus were not in the same direction. A subsequent data reanalysis
however showed a statistically significant overlap between G1 and G2 genes
irrespective of direction, leading to the suggestion that, as phenotypic
variability in epigenetic transmission has been observed in several other
examples also, the above report provided evidence in favor of, not against,
transgenerational inheritance. This criticism has recently been questioned.
Here, it is shown that the questions raised are based not only on incorrect
statistical calculations but also on wrong premise that gene expression changes
do not constitute a phenotype.
Weak Nanoscale Chaos And Anomalous Relaxation in DNA
Date: 2017-06-23 00:00:00

Anomalous non-exponential relaxation in hydrated biomolecules is commonly
attributed to the complexity of the free-energy landscapes, similarly to
polymers and glasses. It was found recently that the hydrogen-bond breathing of
terminal DNA base pairs exhibits a slow power-law relaxation attributable to
weak Hamiltonian chaos, with parameters similar to experimental data. Here, the
relationship is studied between this motion and spectroscopic signals measured
in DNA with a small molecular photoprobe inserted into the base-pair stack. To
this end, the earlier computational approach in combination with an analytical
theory is applied to the experimental DNA fragment. It is found that the
intensity of breathing dynamics is strongly increased in the internal base
pairs that flank the photoprobe, with anomalous relaxation quantitatively close
to that in terminal base pairs. A physical mechanism is proposed to explain the
coupling between the relaxation of base-pair breathing and the experimental
response signal. It is concluded that the algebraic relaxation observed
experimentally is very likely a manifestation of weakly chaotic dynamics of
hydrogen-bond breathing in the base pairs stacked to the photoprobe, and that
the weak nanoscale chaos can represent an ubiquitous hidden source of
non-exponential relaxation in ultrafast spectroscopy.
Replica approach to mean-variance portfolio optimization
Date: 2016-06-28 00:00:00
Tasks: Portfolio Optimization, Time Series, Time Series Analysis

We consider the problem of mean-variance portfolio optimization for a generic
covariance matrix subject to the budget constraint and the constraint for the
expected return, with the application of the replica method borrowed from the
statistical physics of disordered systems. We find that the replica symmetry of
the solution does not need to be assumed, but emerges as the unique solution of
the optimization problem. We also check the stability of this solution and find
that the eigenvalues of the Hessian are positive for $r=N/T<1$, where $N$ is
the dimension of the portfolio and $T$ the length of the time series used to
estimate the covariance matrix. At the critical point $r=1$ a phase transition
is taking place. The out of sample estimation error blows up at this point as
$1/(1-r)$, independently of the covariance matrix or the expected return,
displaying the universality not only of the critical index, but also the
critical point. As a conspicuous illustration of the dangers of in-sample
estimates, the optimal in-sample variance is found to vanish at the critical
point inversely proportional to the divergent estimation error.
The Capacity of Symmetric Private Information Retrieval
Authors: Sun Hua, Jafar Syed A.
Date: 2017-07-15 00:00:00
Tasks: Information Retrieval, Retrieval

Private information retrieval (PIR) is the problem of retrieving as
efficiently as possible, one out of $K$ messages from $N$ non-communicating
replicated databases (each holds all $K$ messages) while keeping the identity
of the desired message index a secret from each individual database. Symmetric
PIR (SPIR) is a generalization of PIR to include the requirement that beyond
the desired message, the user learns nothing about the other $K-1$ messages.
The information theoretic capacity of SPIR (equivalently, the reciprocal of
minimum download cost) is the maximum number of bits of desired information
that can be privately retrieved per bit of downloaded information. We show that
the capacity of SPIR is $1-1/N$ regardless of the number of messages $K$, if
the databases have access to common randomness (not available to the user) that
is independent of the messages, in the amount that is at least $1/(N-1)$ bits
per desired message bit, and zero otherwise. Extensions to the capacity region
of SPIR and the capacity of finite length SPIR are provided.
Structure-based prediction of protein-folding transition paths
Date: 2016-07-27 00:00:00
Tasks: Prediction, Protein Folding

We propose a general theory to describe the distribution of protein-folding
transition paths. We show that transition paths follow a predictable sequence
of high-free-energy transient states that are separated by free-energy
barriers. Each transient state corresponds to the assembly of one or more
discrete, cooperative units, which are determined directly from the native
structure. We show that the transition state on a folding pathway is reached
when a small number of critical contacts are formed between a specific set of
substructures, after which folding proceeds downhill in free energy. This
approach suggests a natural resolution for distinguishing parallel folding
pathways and provides a simple means to predict the rate-limiting step in a
folding reaction. Our theory identifies a common folding mechanism for proteins
with diverse native structures and establishes general principles for the
self-assembly of polymers with specific interactions.
A tractable method for describing complex couplings between neurons and population rate
Date: 2016-06-28 00:00:00

Neurons within a population are strongly correlated, but how to simply
capture these correlations is still a matter of debate. Recent studies have
shown that the activity of each cell is influenced by the population rate,
defined as the summed activity of all neurons in the population. However, an
explicit, tractable model for these interactions is still lacking. Here we
build a probabilistic model of population activity that reproduces the firing
rate of each cell, the distribution of the population rate, and the linear
coupling between them. This model is tractable, meaning that its parameters can
be learned in a few seconds on a standard computer even for large population
recordings. We inferred our model for a population of 160 neurons in the
salamander retina. In this population, single-cell firing rates depended in
unexpected ways on the population rate. In particular, some cells had a
preferred population rate at which they were most likely to fire. These complex
dependencies could not be explained by a linear coupling between the cell and
the population rate. We designed a more general, still tractable model that
could fully account for these non-linear dependencies. We thus provide a simple
and computationally tractable way to learn models that reproduce the dependence
of each neuron on the population rate.
Curvature-driven molecular flows on membrane surfaces
Date: 2016-06-28 00:00:00

Morphological change of bilayer membrane in vivo is not a spontaneous
procedure but modulated by various types of proteins in general. Most of these
modulations are associated with the localization of related proteins in the
crowded lipid environment in bilayer membrane. This work presents an
mathematical model for the localization of multiple species of diffusion
molecules on membrane surfaces. We start with the energetic description of the
distributions of molecules on curved membrane surface, by assembling the
bending energy of bilayer membrane and the entropic energy of diffusive
molecules. We introduce the spontaneous curvature of molecules in membrane, and
define the spontaneous curvature of bilayer membrane as a function of the
molecule concentrations on membrane surfaces. This connection gives rise to a
drift-diffusion equation to govern the gradient flows of the surface molecule
concentrations. We recast the energetic formulation and the related governing
equations in the Eulerian framework by using a phase field function that
defines the membrane morphology. Computational simulations with the proposed
mathematical model and related numerical techniques predict the molecular
localization on membrane surfaces at locations with preferred mean curvature.
Enhancing power of rare variant association test by Zoom-Focus Algorithm (ZFA) to locate optimal testing region
Date: 2016-06-29 00:00:00

Motivation: Exome or targeted sequencing data exerts analytical challenge to
test single nucleotide polymorphisms (SNPs) with extremely small minor allele
frequency (MAF). Various rare variant tests were proposed to increase power by
aggregating SNPs within a fixed genomic region, such as a gene or pathway.
However, a gene could contain from several to thousands of markers, and not all
of them may be related to the phenotype. Combining functional and
non-functional SNPs in arbitrary genomic region could impair the testing power.
Results: We propose a Zoom-Focus algorithm (ZFA) to locate the optimal testing
region within a given genomic region, as a wrapper function to be applied in
conjunction with rare variant association tests. In the first Zooming step, a
given genomic region is partitioned by order of two, and the best partition is
located within all partition levels. In the next Focusing step, boundaries of
the zoomed region are refined. Simulation studies showed that ZFA substantially
enhanced the statistical power of rare variant tests by over 10 folds,
including the WSS, SKAT and W-test. The algorithm is applied on real exome
sequencing data of hypertensive disorder, and identified biologically relevant
genetic markers to metabolic disorder that are undiscoverable by testing using
full gene. The proposed algorithm is an efficient and powerful tool to increase
the effectiveness of rare variant association tests for exome sequencing
datasets of complex disorder.
The rotating normal form of braids is regular
Authors: Jean Fromentin
Date: 2016-06-29 00:00:00
Tasks: Form

Defined on Birman-Ko-Lee monoids, the rotating normal form has strong connections with the Dehornoy's braid ordering. It can be seen as a process for selecting between all the representative words of a Birman-Ko-Lee braid a particular one, called rotating word. In this paper we construct, for all n 2, a finite-state automaton which recognizes rotating words on n strands, proving that the rotating normal form is regular. As a consequence we obtain the regularity of a $\sigma$-definite normal form defined on the whole braid group.
Optimal Consumption, Investment and Housing with Means-tested Public Pension in Retirement
Date: 2016-06-29 00:00:00

In this paper, we develop an expected utility model for the retirement
behavior in the decumulation phase of Australian retirees with sequential
family status subject to consumption, housing, investment, bequest and
government provided means-tested Age Pension. We account for mortality risk and
risky investment assets, and introduce a health proxy to capture the decreasing
level of consumption for older retirees. Then we find optimal housing at
retirement, and optimal consumption and optimal risky asset allocation
depending on age and wealth. The model is solved numerically as a stochastic
control problem, and is calibrated using the maximum likelihood method on
empirical data of consumption and housing from the Australian Bureau of
Statistics 2009-2010 Survey. The model fits the characteristics of the data
well to explain the behavior of Australian retirees. The key findings are the
following: First, the optimal policy is highly sensitive to means-tested Age
Pension early in retirement but this sensitivity fades with age. Secondly, the
allocation to risky assets shows a complex relationship with the means-tested
Age Pension that disappears once minimum withdrawal rules are enforced. As a
general rule, when wealth decreases the proportion allocated to risky assets
increases, due to the Age Pension working as a buffer against investment
losses. Finally, couples can be more aggressive with risky allocations due to
their longer life expectancy compared with singles.
Asymptotic analysis of noisy fitness maximization, applied to metabolism and growth
Date: 2016-10-27 00:00:00

We consider a population dynamics model coupling cell growth to a diffusion
in the space of metabolic phenotypes as it can be obtained from realistic
constraints-based modelling. In the asymptotic regime of slow diffusion, that
coincides with the relevant experimental range, the resulting non-linear
Fokker-Planck equation is solved for the steady state in the WKB approximation
that maps it into the ground state of a quantum particle in an Airy potential
plus a centrifugal term. We retrieve scaling laws for growth rate fluctuations
and time response with respect to the distance from the maximum growth rate
suggesting that suboptimal populations can have a faster response to
perturbations.
Influence of initial fixation position in scene viewing
Date: 2016-07-13 00:00:00
Tasks: Position

During scene perception our eyes generate complex sequences of fixations.
Predictors of fixation locations are bottom-up factors like luminance contrast,
top-down factors like viewing instruction, and systematic biases like the
tendency to place fixations near the center of an image. However, comparatively
little is known about the dynamics of scanpaths after experimental manipulation
of specific fixation locations. Here we investigate the influence of initial
fixation position on subsequent eye-movement behavior on an image. We presented
64 colored photographs to participants who started their scanpaths from one of
two experimentally controlled positions in the right or left part of an image.
Additionally, we computed the images' saliency maps and classified them as
balanced images or images with high saliency values on either the left or right
side of a picture. As a result of the starting point manipulation, we found
long transients of mean fixation position and a tendency to overshoot to the
image side opposite to the starting position. Possible mechanisms for the
generation of this overshoot were investigated using numerical simulations of
statistical and dynamical models. We conclude that inhibitory tagging is a
viable mechanism for dynamical planning of scanpaths.
Cognitive Control in the Controllable Connectome
Date: 2016-06-29 00:00:00

Cognition is supported by neurophysiological processes that occur both in
local anatomical neighborhoods and in distributed large-scale circuits. Recent
evidence from network control theory suggests that white matter pathways
linking large-scale brain regions provide a critical substrate constraining the
ability of single areas to affect control on those processes. Yet, no direct
evidence exists for a relationship between brain network controllability and
cognitive control performance. Here, we address this gap by constructing
structural brain networks from diffusion tensor imaging data acquired in 125
healthy adult individuals. We define a simplified model of brain dynamics and
simulate network control to quantify modal and boundary controllability, which
together describe complementary features of a region's theoretically predicted
preference to drive the brain into different cognitive states. We observe that
individual differences in these control features derived from structural
connectivity are significantly correlated with individual differences in
cognitive control performance, as measured by a continuous performance
attention test, a color/shape switching task, the Stroop inhibition task, and a
spatial n-back working memory task. Indeed, control hubs like anterior
cingulate are distinguished from default mode and frontal association areas in
terms of the relationship between their control properties and individual
differences in cognitive function. These results provide the first empirical
evidence that network control forms a fundamental mechanism of cognitive
control.
A multilayer approach for price dynamics in financial markets
Date: 2016-06-29 00:00:00

We introduce a new Self-Organized Criticality (SOC) model for simulating
price evolution in an artificial financial market, based on a multilayer
network of traders. The model also implements, in a quite realistic way with
respect to previous studies, the order book dy- namics, by considering two
assets with variable fundamental prices. Fat tails in the probability
distributions of normalized returns are observed, together with other features
of real financial markets.