pwc-archive/papers-with-abstracts huggingface dataset:
Asymptotic analysis of forward performance processes in incomplete markets and their ill-posed HJB equations
Date: 2015-09-24 00:00:00

We consider the problem of optimal portfolio selection under forward
investment performance criteria in an incomplete market. The dynamics of the
prices of the traded assets depend on a pair of stochastic factors, namely, a
slow factor (e.g. a macroeconomic indicator) and a fast factor (e.g. stochastic
volatility). We analyze the associated forward performance SPDE and provide
explicit formulae for the leading order and first order correction terms for
the forward investment process and the optimal feedback portfolios. They both
depend on the investor's initial preferences and the dynamically changing
investment opportunities. The leading order terms resemble their time-monotone
counterparts, but with the appropriate stochastic time changes resulting from
averaging phenomena. The first-order terms compile the reaction of the investor
to both the changes in the market input and his recent performance. Our
analysis is based on an expansion of the underlying ill-posed HJB equation, and
it is justified by means of an appropriate remainder estimate.
Economic inequality and mobility in kinetic models for social sciences
Date: 2015-01-27 00:00:00

Statistical evaluations of the economic mobility of a society are more
difficult than measurements of the income distribution, because they require to
follow the evolution of the individuals' income for at least one or two
generations. In micro-to-macro theoretical models of economic exchanges based
on kinetic equations, the income distribution depends only on the asymptotic
equilibrium solutions, while mobility estimates also involve the detailed
structure of the transition probabilities of the model, and are thus an
important tool for assessing its validity. Empirical data show a remarkably
general negative correlation between economic inequality and mobility, whose
explanation is still unclear. It is therefore particularly interesting to study
this correlation in analytical models. In previous work we investigated the
behavior of the Gini inequality index in kinetic models in dependence on
several parameters which define the binary interactions and the taxation and
redistribution processes: saving propensity, taxation rates gap, tax evasion
rate, welfare means-testing etc. Here, we check the correlation of mobility
with inequality by analyzing the mobility dependence from the same parameters.
According to several numerical solutions, the correlation is confirmed to be
negative.
Polynomial term structure models
Date: 2015-04-13 00:00:00

In this article, we explore a class of tractable interest rate models that have the property that the price of a zero-coupon bond can be expressed as a polynomial of a state diffusion process. Our results include a classification of all such time-homogeneous single-factor models in the spirit of Filipovic's maximal degree theorem for exponential polynomial models, as well as an explicit characterisation of the set of feasible parameters in the case when the factor process is bounded. Extensions to time-inhomogeneous and multi-factor polynomial models are also considered.
Analytical tools for single-molecule fluorescence imaging in cellulo
Date: 2015-04-14 00:00:00

Recent technological advances in cutting-edge ultrasensitive fluorescence
microscopy have allowed single-molecule imaging experiments in living cells
across all three domains of life to become commonplace. Single-molecule
live-cell data is typically obtained in a low signal-to-noise ratio (SNR)
regime sometimes only marginally in excess of 1, in which a combination of
detector shot noise, sub-optimal probe photophysics, native cell
autofluorescence and intrinsically underlying stochastic of molecules result in
highly noisy datasets for which underlying true molecular behaviour is
non-trivial to discern. The ability to elucidate real molecular phenomena is
essential in relating experimental single-molecule observations to both the
biological system under study as well as offering insight into the fine details
of the physical and chemical environments of the living cell. To confront this
problem of faithful signal extraction and analysis in a noise-dominated regime,
the needle in a haystack challenge, such experiments benefit enormously from a
suite of objective, automated, high-throughput analysis tools that can home in
on the underlying molecular signature and generate meaningful statistics across
a large population of individual cells and molecules. Here, I discuss the
development and application of several analytical methods applied to real case
studies, including objective methods of segmenting cellular images from light
microscopy data, tools to robustly localize and track single
fluorescently-labelled molecules, algorithms to objectively interpret molecular
mobility, analysis protocols to reliably estimate molecular stoichiometry and
turnover, and methods to objectively render distributions of molecular
parameters
Superresolution imaging of single DNA molecules using stochastic photoblinking of minor groove and intercalating dyes
Date: 2015-04-14 00:00:00

As proof-of-principle for generating superresolution structural information
from DNA we applied a method of localization microscopy utilizing photoblinking
comparing intercalating dye YOYO-1 against minor groove binding dye SYTO-13,
using a bespoke multicolor single-molecule fluorescence microscope. We used a
full-length ~49 kbp {\lambda} DNA construct possessing oligo inserts at either
terminus allowing conjugation of digoxigenin and biotin at opposite ends for
tethering to a glass coverslip surface and paramagnetic microsphere
respectively. We observed stochastic DNA-bound dye photoactivity consistent
with dye photoblinking as opposed to binding/unbinding events, evidenced
through both discrete simulations and continuum kinetics analysis. We analyzed
dye photoblinking images of immobilized DNA molecules using superresolution
reconstruction software from two existing packages, rainSTORM and QuickPALM,
and compared the results against our own novel home-written software called
ADEMS code. ADEMS code generated lateral localization precision values of 30-40
nm and 60-70 nm for YOYO-1 and SYTO-13 respectively at video-rate sampling,
similar to rainSTORM, running more slowly than rainSTORM and QuickPALM
algorithms but having a complementary capability over both in generating
automated centroid distribution and cluster analyses. Our imaging system allows
us to observe dynamic topological changes to single molecules of DNA in
real-time, such as rapid molecular snapping events. This will facilitate
visualization of fluorescently-labeled DNA molecules conjugated to a magnetic
bead in future experiments involving newly developed magneto-optical tweezers
combined with superresolution microscopy.
Probing DNA interactions with proteins using a single-molecule toolbox: inside the cell, in a test tube, and in a computer
Date: 2015-04-14 00:00:00

DNA-interacting proteins have roles multiple processes, many operating as
molecular machines which undergo dynamic metastable transitions to bring about
their biological function. To fully understand this molecular heterogeneity,
DNA and the proteins that bind to it must ideally be interrogated at a single
molecule level in their native in vivo environments, in a time-resolved manner
fast to sample the molecular transitions across the free energy landscape.
Progress has been made over the past decade in utilising cutting-edge tools of
the physical sciences to address challenging biological questions concerning
the function and modes of action of several different proteins which bind to
DNA. These physiologically relevant assays are technically challenging, but can
be complemented by powerful and often more tractable in vitro experiments which
confer advantages of the chemical environment with enhanced detection
single-to-noise of molecular signatures and transition events. Here, we discuss
a range of techniques we have developed to monitor DNA-protein interactions in
vivo, in vitro and in silico. These include bespoke single-molecule
fluorescence microscopy techniques to elucidate the architecture and dynamics
of the bacterial replisome and the structural maintenance of bacterial
chromosomes, as well as new computational tools to extract single-molecule
molecular signatures from live cells to monitor stoichiometry, spatial
localization and mobility in living cells. We also discuss recent developments
from our lab made in vitro, complementing these in vivo studies, which combine
optical and magnetic tweezers to manipulate and image single molecules of DNA,
with and without bound protein, in a new superresolution fluorescence
microscope.
Systemic trade-risk of critical resources
Date: 2015-04-14 00:00:00
Tasks: Management

In the wake of the 2008 financial crisis the role of strongly interconnected
markets in fostering systemic instability has been increasingly acknowledged.
Trade networks of commodities are susceptible to deleterious cascades of supply
shocks that increase systemic trade-risks and pose a threat to geopolitical
stability. On a global and a regional level we show that supply risk, scarcity,
and price volatility of non-fuel mineral resources are intricately connected
with the structure of the world-trade network of or spanned by these resources.
On the global level we demonstrate that the scarcity of a resource, as measured
by its trade volume compared to extractable reserves, is closely related to the
susceptibility of the trade network with respect to cascading shocks. On the
regional level we find that to some extent the region-specific price volatility
and supply risk can be understood by centrality measures that capture systemic
trade-risk. The resources associated with the highest systemic trade-risk
indicators are often those that are produced as byproducts of major metals. We
identify significant shortcomings in the management of systemic trade-risk, in
particular in the EU.
Random Time Forward Starting Options
Date: 2015-04-14 00:00:00

We introduce a natural generalization of the forward-starting options, first
discussed by M. Rubinstein. The main feature of the contract presented here is
that the strike-determination time is not fixed ex-ante, but allowed to be
random, usually related to the occurrence of some event, either of financial
nature or not. We will call these options {\bf Random Time Forward Starting
(RTFS)}. We show that, under an appropriate "martingale preserving" hypothesis,
we can exhibit arbitrage free prices, which can be explicitly computed in many
classical market models, at least under independence between the random time
and the assets' prices. Practical implementations of the pricing methodologies
are also provided. Finally a credit value adjustment formula for these OTC
options is computed for the unilateral counterparty credit risk.
PrAGMATiC: a Probabilistic and Generative Model of Areas Tiling the Cortex
Date: 2015-04-14 00:00:00

Much of the human cortex seems to be organized into topographic cortical
maps. Yet few quantitative methods exist for characterizing these maps. To
address this issue we developed a modeling framework that can reveal
group-level cortical maps based on neuroimaging data. PrAGMATiC, a
probabilistic and generative model of areas tiling the cortex, is a
hierarchical Bayesian generative model of cortical maps. This model assumes
that the cortical map in each individual subject is a sample from a single
underlying probability distribution. Learning the parameters of this
distribution reveals the properties of a cortical map that are common across a
group of subjects while avoiding the potentially lossy step of co-registering
each subject into a group anatomical space. In this report we give a
mathematical description of PrAGMATiC, describe approximations that make it
practical to use, show preliminary results from its application to a real
dataset, and describe a number of possible future extensions.
Trade-offs in delayed information transmission in biochemical networks
Date: 2015-04-14 00:00:00

In order to transmit biochemical signals, biological regulatory systems
dissipate energy with concomitant entropy production. Additionally, signaling
often takes place in challenging environmental conditions. In a simple model
regulatory circuit given by an input and a delayed output, we explore the
trade-offs between information transmission and the system's energetic
efficiency. We determine the maximally informative network, given a fixed
amount of entropy production and delayed response, exploring both the case with
and without feedback. We find that feedback allows the circuit to overcome
energy constraints and transmit close to the maximum available information even
in the dissipationless limit. Negative feedback loops, characteristic of shock
responses, are optimal at high dissipation. Close to equilibrium positive
feedback loops, known for their stability, become more informative. Asking how
the signaling network should be constructed to best function in the worst
possible environment, rather than an optimally tuned one or in steady state, we
discover that at large dissipation the same universal motif is optimal in all
of these conditions.
Pathwise super-replication via Vovk's outer measure
Date: 2016-07-13 00:00:00

Since Hobson's seminal paper [D. Hobson: Robust hedging of the lookback
option. In: Finance Stoch. (1998)] the connection between model-independent
pricing and the Skorokhod embedding problem has been a driving force in robust
finance. We establish a general pricing-hedging duality for financial
derivatives which are susceptible to the Skorokhod approach.
  Using Vovk's approach to mathematical finance we derive a model-independent
super-replication theorem in continuous time, given information on finitely
many marginals. Our result covers a broad range of exotic derivatives,
including lookback options, discretely monitored Asian options, and options on
realized variance.
First-principles data set of 45,892 isolated and cation-coordinated conformers of 20 proteinogenic amino acids
Date: 2016-01-10 00:00:00

We present a structural data set of the 20 proteinogenic amino acids and
their amino-methylated and acetylated (capped) dipeptides. Different
protonation states of the backbone (uncharged and zwitterionic) were considered
for the amino acids as well as varied side chain protonation states.
Furthermore, we studied amino acids and dipeptides in complex with divalent
cations (Ca2+, Ba2+, Sr2+, Cd2+, Pb2+, and Hg2+). The database covers the
conformational hierarchies of 280 systems in a wide relative energy range of up
to 4 eV (390 kJ/mol), summing up to an overall of 45,892 stationary points on
the respective potential-energy surfaces. All systems were calculated on equal
first-principles footing, applying density-functional theory in the generalized
gradient approximation corrected for long-range van der Waals interactions. We
show good agreement to available experimental data for gas-phase ion
affinities. Our curated data can be utilized, for example, for a wide
comparison across chemical space of the building blocks of life, for the
parametrization of protein force fields, and for the calculation of reference
spectra for biophysical applications.
Detecting Sponsored Recommendations
Authors: Krishnasamy Subhashini, Sen Rajat, Oh Sewoong, Shakkottai Sanjay
Date: 2015-04-14 00:00:00
Tasks: Recommendation Systems

With a vast number of items, web-pages, and news to choose from, online
services and the customers both benefit tremendously from personalized
recommender systems. Such systems however provide great opportunities for
targeted advertisements, by displaying ads alongside genuine recommendations.
We consider a biased recommendation system where such ads are displayed without
any tags (disguised as genuine recommendations), rendering them
indistinguishable to a single user. We ask whether it is possible for a small
subset of collaborating users to detect such a bias. We propose an algorithm
that can detect such a bias through statistical analysis on the collaborating
users' feedback. The algorithm requires only binary information indicating
whether a user was satisfied with each of the recommended item or not. This
makes the algorithm widely appealing to real world issues such as
identification of search engine bias and pharmaceutical lobbying. We prove that
the proposed algorithm detects the bias with high probability for a broad class
of recommendation systems when sufficient number of users provide feedback on
sufficient number of recommendations. We provide extensive simulations with
real data sets and practical recommender systems, which confirm the trade offs
in the theoretical guarantees.
A sparse reformulation of the Green's function formalism allows efficient simulations of partial differential equations on tree graphs
Date: 2015-09-16 00:00:00

We prove that when a class of partial differential equations, generalized
from the cable equation, is defined on tree graphs, and when the inputs are
restricted to a spatially discrete, well chosen set of points, the Green's
function (GF) formalism can be rewritten to scale as $O(n)$ with the number $n$
of input locations, contrary to the previously reported $O(n^2)$ scaling. We
show that the linear scaling can be combined with an expansion of the remaining
kernels as sums of exponentials, to allow efficient simulations of equations
from the aforementioned class. We furthermore validate this simulation paradigm
on models of nerve cells and explore its relation with more traditional finite
difference approaches. Situations in which a gain in computational performance
is expected, are discussed.
M\'as all\'a del GWAS: alternativas para localizar QTLs
Date: 2015-04-15 00:00:00
Tasks: All

Beyond GWAS: alternatives to localize QTLs in farm animals. Two methods that
could be used for QTL mapping as alternatives to standard GWAS are presented.
The first relies on the differential frequency of runs of homozygosity (ROH) in
groups of animals (e.g. cases and controls), while the second stems from
resampling techniques used for the prediction of carriers of a mutation, and is
based on the frequency of inclusion of polymorphisms (SNP) in the predictive
model. ROH were applied to the detection of reproductive diseases in
Holstein-Friesian cattle, while resampling was applied to the detection of
carriers of the BH2 haplotype in Brown Swiss cattle. These alternative
approaches may complement GWAS analyses in localizing more accurately QTLs for
traits of interest in livestock.
Fisher information and quantum mechanical models for finance
Date: 2015-04-15 00:00:00

The probability distribution function (PDF) for prices on financial markets
is derived by extremization of Fisher information. It is shown how on that
basis the quantum-like description for financial markets arises and different
financial market models are mapped by quantum mechanical ones.
Most undirected random graphs are amplifiers of selection for Birth-death dynamics, but suppressors of selection for death-Birth dynamics
Date: 2016-10-26 00:00:00

We analyze evolutionary dynamics on graphs, where the nodes represent
individuals of a population. The links of a node describe which other
individuals can be displaced by the offspring of the individual on that node.
Amplifiers of selection are graphs for which the fixation probability is
increased for advantageous mutants and decreased for disadvantageous mutants. A
few examples of such amplifiers have been developed, but so far it is unclear
how many such structures exist and how to construct them. Here, we show that
almost any undirected random graph is an amplifier of selection for Birth-death
updating, where an individual is selected to reproduce with probability
proportional to its fitness and one of its neighbors is replaced by that
offspring at random. If we instead focus on death-Birth updating, in which a
random individual is removed and its neighbors compete for the empty spot, then
the same ensemble of graphs consists of almost only suppressors of selection
for which the fixation probability is decreased for advantageous mutants and
increased for disadvantageous mutants. Thus, the impact of population structure
on evolutionary dynamics is a subtle issue that will depend on seemingly minor
details of the underlying evolutionary process.
Computational reconstruction of mitochondria-encoded mammal ancestral proteins
Date: 2015-04-15 00:00:00

A method based on mapping a symbolic sequence into a set of patterns (strings
resulting from the sequence parsing) is proposed as a tool for the
reconstruction of ancestral sequences. The set union of patterns comprises all
the patterns present in the family of related proteins sequences of an extant
species. The set of most frequent patterns among protein sequences is selected
and concatenated. The resulting sequence of amino acids is supposed to be the
ancestral protein of the family. No sequences alignment and phylogenetic tree
of the species family are necessary. The method is used for inferring the
ancestral amino acid sequences of thirteen mitochondria-encoded protein
families of mammal species. Statistical distribution of the similarity between
extant and ancestral sequences exhibits some structures related to
environmental changes in the past.
A versatile clearing agent for multi-modal brain imaging
Date: 2015-04-16 00:00:00
Tasks: Hippocampus

Extensive mapping of neuronal connections in the central nervous system
requires high-throughput um-scale imaging of large volumes. In recent years,
different approaches have been developed to overcome the limitations due to
tissue light scattering. These methods are generally developed to improve the
performance of a specific imaging modality, thus limiting comprehensive
neuroanatomical exploration by multimodal optical techniques. Here, we
introduce a versatile brain clearing agent (2,2'-thiodiethanol; TDE) suitable
for various applications and imaging techniques. TDE is cost-efficient,
water-soluble and low-viscous and, more importantly, it preserves fluorescence,
is compatible with immunostaining and does not cause deformations at
sub-cellular level. We demonstrate the effectiveness of this method in
different applications: in fixed samples by imaging a whole mouse hippocampus
with serial two-photon tomography; in combination with CLARITY by
reconstructing an entire mouse brain with light sheet microscopy and in
translational research by imaging immunostained human dysplastic brain tissue.
Graph representation of balance sheets: from exogenous to endogenous money
Date: 2018-01-30 00:00:00

The nature of monetary arrangements is often discussed without any reference
to its detailed construction. We present a graph representation that allows for
a clear understanding of modern monetary systems. First, we show that systems
based on commodity money are incompatible with credit. We then study the
current chartalist systems based on pure fiat money, and we discuss the
consolidation of the central bank with the Treasury. We obtain a visual
explanation about how commercial banks are responsible for endogenous money
creation whereas the Treasury and the central bank are in charge of the total
amount of net money. Finally we draw an analogy between systems based on gold
convertibility and currency pegs to show that fixed exchange rates can never be
maintained.
Forecasting trends with asset prices
Date: 2015-04-20 00:00:00
Tasks: Time Series, Time Series Analysis

In this paper, we consider a stochastic asset price model where the trend is
an unobservable Ornstein Uhlenbeck process. We first review some classical
results from Kalman filtering. Expectedly, the choice of the parameters is
crucial to put it into practice. For this purpose, we obtain the likelihood in
closed form, and provide two on-line computations of this function. Then, we
investigate the asymptotic behaviour of statistical estimators. Finally, we
quantify the effect of a bad calibration with the continuous time mis-specified
Kalman filter. Numerical examples illustrate the difficulty of trend
forecasting in financial time series.