pwc-archive/papers-with-abstracts huggingface dataset:
Regularity properties in a state-constrained expected utility maximization problem
Date: 2015-10-11 00:00:00

We consider a stochastic optimal control problem in a market model with
temporary and permanent price impact, which is related to an expected utility
maximization problem under finite fuel constraint. We establish the initial
condition fulfilled by the corresponding value function and show its first
regularity property. Moreover, we can prove the existence and uniqueness of
optimal strategies under rather mild model assumptions. On the one hand, this
result is of independent interest. On the other hand, it will then allow us to
derive further regularity properties of the corresponding value function, in
particular its continuity and partial differentiability. As a consequence of
the continuity of the value function, we will prove the dynamic programming
principle without appealing to the classical measurable selection arguments.
Theory on the mechanism of DNA renaturation: Stochastic nucleation and zipping
Date: 2015-11-22 00:00:00

Renaturation of complementary single strands of DNA is one of the important
processes that requires better understanding in the view of molecular biology
and biological physics. Here we develop a stochastic dynamical model on the DNA
renaturation. According to our model there are at least three steps in the
renaturation process viz. incorrect-contact formation, correct-contact
formation and nucleation, and zipping. Most of the earlier two-state models
combined nucleation with incorrect-contact formation step. In our model we
suggest that it is considerably meaningful when we combine the nucleation with
the zipping since nucleation is the initial step of zipping and the nucleated
and zipping molecules are indistinguishable. Incorrect-contact formation step
is a pure three-dimensional diffusion controlled collision process. Whereas
nucleation involves several rounds of one-dimensional slithering dynamics of
one single strand of DNA on the other complementary strand in the process of
searching for the correct-contact and then initiate nucleation. Upon
nucleation, the stochastic zipping follows to generate a fully renatured double
stranded DNA. It seems that the square-root dependency of the overall
renaturation rate constant on the length of reacting single strands originates
mainly from the geometric constraints in the diffusion controlled
incorrect-contact formation step. Further the inverse scaling of the
renaturation rate on the viscosity of the reaction medium also originates from
the incorrect-contact formation step. On the other hand the inverse scaling of
the renaturation rate with the sequence complexity originates from the
stochastic zipping which involves several rounds of crossing over the
free-energy barrier at microscopic levels.
The demodulated band transform
Date: 2016-01-19 00:00:00
Tasks: Computational Efficiency

Background: Windowed Fourier decompositions (WFD) are widely used in
measuring stationary and non-stationary spectral phenomena and in describing
pairwise relationships among multiple signals. Although a variety of WFDs see
frequent application in electrophysiological research, including the short-time
Fourier transform, continuous wavelets, band-pass filtering and
multitaper-based approaches, each carries certain drawbacks related to
computational efficiency and spectral leakage. This work surveys the advantages
of a WFD not previously applied in electrophysiological settings.
  New Methods: A computationally efficient form of complex demodulation, the
demodulated band transform (DBT), is described.
  Results: DBT is shown to provide an efficient approach to spectral estimation
with minimal susceptibility to spectral leakage. In addition, it lends itself
well to adaptive filtering of non-stationary narrowband noise.
  Comparison with existing methods: A detailed comparison with alternative WFDs
is offered, with an emphasis on the relationship between DBT and Thomson's
multitaper. DBT is shown to perform favorably in combining computational
efficiency with minimal introduction of spectral leakage.
  Conclusion: DBT is ideally suited to efficient estimation of both stationary
and non-stationary spectral and cross-spectral statistics with minimal
susceptibility to spectral leakage. These qualities are broadly desirable in
many settings.
Modelling afferent nerve responses to bladder filling
Date: 2015-10-12 00:00:00

A sensation of fullness in the bladder is a regular experience, yet the
mechanisms that act to generate this sensation remain poorly understood. This
is an important issue because of the clinical problems that can result when
this system does not function properly. The aim of the study group activity was
to develop mathematical models that describe the mechanics of bladder filling,
and how stretch modulates the firing rate of afferent nerves. Several models
were developed, which were qualitatively consistent with experimental data
obtained from a mouse model.
Model reduction for stochastic chemical systems with abundant species
Date: 2015-10-12 00:00:00

Biochemical processes typically involve many chemical species, some in
abundance and some in low molecule numbers. Here we first identify the rate
constant limits under which the concentrations of a given set of species will
tend to infinity (the abundant species) while the concentrations of all other
species remains constant (the non-abundant species). Subsequently we prove that
in this limit, the fluctuations in the molecule numbers of non-abundant species
are accurately described by a hybrid stochastic description consisting of a
chemical master equation coupled to deterministic rate equations. This is a
reduced description when compared to the conventional chemical master equation
which describes the fluctuations in both abundant and non-abundant species. We
show that the reduced master equation can be solved exactly for a number of
biochemical networks involving gene expression and enzyme catalysis, whose
conventional chemical master equation description is analytically impenetrable.
We use the linear noise approximation to obtain approximate expressions for the
difference between the variance of fluctuations in the non-abundant species as
predicted by the hybrid approach and by the conventional chemical master
equation. Furthermore we show that surprisingly, irrespective of any separation
in the mean molecule numbers of various species, the conventional and hybrid
master equations exactly agree for a class of chemical systems.
Price response in correlated financial markets: empirical results
Date: 2016-03-16 00:00:00

Previous studies of the stock price response to individual trades focused on
single stocks. We empirically investigate the price response of one stock to
the trades of other stocks. 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. Performing different averages, we
distinguish active and passive responses. The two average responses show
different characteristic dependences on the time lag. The passive response
exhibits a shorter response period with sizeable volatilities, and the active
response a longer period. We also study the response for a given stock with
respect to different sectors and to the whole market. Furthermore, we compare
the self-response with the various cross-responses. The correlation of the
trade signs is a short-memory process for a pair of stocks, but it turns into a
long-memory process when averaged over different pairs of stocks.
Hedging with Temporary Price Impact
Date: 2016-07-26 00:00:00

We consider the problem of hedging a European contingent claim in a Bachelier
model with transient price impact as proposed by Almgren and Chriss. Following
the approach of Rogers and Singh and Naujokat and Westray, the hedging problem
can be regarded as a cost optimal tracking problem of the frictionless hedging
strategy. We solve this problem explicitly for general predictable target
hedging strategies. It turns out that, rather than towards the current target
position, the optimal policy trades towards a weighted average of expected
future target positions. This generalizes an observation of Garleanu and
Pedersen from their homogenous Markovian optimal investment problem to a
general hedging problem. Our findings complement a number of previous studies
in the literature on optimal strategies in illiquid markets where the
frictionless strategy is confined to diffusions. The consideration of general
predictable reference strategies is made possible by the use of a convex
analysis approach instead of the more common dynamic programming methods.
Coevolutionary landscape inference and the context-dependence of mutations in beta-lactamase TEM-1
Date: 2015-10-12 00:00:00

The quantitative characterization of mutational landscapes is a task of
outstanding importance in evolutionary and medical biology: It is, e.g., of
central importance for our understanding of the phenotypic effect of mutations
related to disease and antibiotic drug resistance. Here we develop a novel
inference scheme for mutational landscapes, which is based on the statistical
analysis of large alignments of homologs of the protein of interest. Our method
is able to capture epistatic couplings between residues, and therefore to
assess the dependence of mutational effects on the sequence context where they
appear. Compared to recent large-scale mutagenesis data of the beta-lactamase
TEM-1, a protein providing resistance against beta-lactam antibiotics, our
method leads to an increase of about 40% in explicative power as compared to
approaches neglecting epistasis. We find that the informative sequence context
extends to residues at native distances of about 20{\AA} from the mutated site,
reaching thus far beyond residues in direct physical contact.
Hopf-type neurons increase input-sensitivity by forming forcing-coupled ensembles
Date: 2015-10-12 00:00:00
Tasks: Sensitivity, Vocal Bursts Type Prediction

Astounding properties of biological sensors can often be mapped onto a
dynamical system in the vicinity a bifurcation. For mammalian hearing, a Hopf
bifurcation description has been shown to work across a whole range of scales,
from individual hair bundles to whole regions of the cochlea. We reveal here
the origin of this scale-invariance, from a general level, applicable to all
neuronal dynamics in the vicinity of a Hopf bifurcation (embracing, e.g.,
Hodgkin-Huxley equations). When coupled by natural 'force-coupling', ensembles
of Hopf oscillators below bifurcation threshold exhibit a collective Hopf
bifurcation. This collective Hopf bifurcation occurs substantially below where
the average of the individual oscillators would bifurcate, with a frequency
profile that is sharpened if compared to the individual oscillators.
Further Theoretical Study of Distribution Separation Method for Information Retrieval
Authors: Zhang Peng, Yu Qian, Hou Yuexian, Song Dawei, Li Jingfei, Hu Bin
Date: 2015-10-16 00:00:00
Tasks: Information Retrieval, Retrieval

Recently, a Distribution Separation Method (DSM) is proposed for relevant
feedback in information retrieval, which aims to approximate the true relevance
distribution by separating a seed irrelevance distribution from the mixture
one. While DSM achieved a promising empirical performance, theoretical analysis
of DSM is still need further study and comparison with other relative retrieval
model. In this article, we first generalize DSM's theoretical property, by
proving that its minimum correlation assumption is equivalent to the maximum
(original and symmetrized) KL-Divergence assumption. Second, we also
analytically show that the EM algorithm in a well-known Mixture Model is
essentially a distribution separation process and can be simplified using the
linear separation algorithm in DSM. Some empirical results are also presented
to support our theoretical analysis.
Optimal ETF Selection for Passive Investing
Date: 2015-11-28 00:00:00
Tasks: Variable Selection

This paper considers the problem of isolating a small number of exchange
traded funds (ETFs) that suffice to capture the fundamental dimensions of
variation in U.S. financial markets. First, the data is fit to a vector-valued
Bayesian regression model, which is a matrix-variate generalization of the well
known stochastic search variable selection (SSVS) of George and McCulloch
(1993). ETF selection is then performed using the decoupled shrinkage and
selection (DSS) procedure described in Hahn and Carvalho (2015), adapted in two
ways: to the vector-response setting and to incorporate stochastic covariates.
The selected set of ETFs is obtained under a number of different penalty and
modeling choices. Optimal portfolios are constructed from selected ETFs by
maximizing the Sharpe ratio posterior mean, and they are compared to the
(unknown) optimal portfolio based on the full Bayesian model. We compare our
selection results to popular ETF advisor Wealthfront.com. Additionally, we
consider selecting ETFs by modeling a large set of mutual funds.
Certain amplified genomic-DNA fragments (AGFs) may be involved in cell cycle progression and chloroquine is found to induce the production of cell-cycle-associated AGFs (CAGFs) in Plasmodium falciparum
Date: 2015-11-19 00:00:00

It is well known that cyclins are a family of proteins that control
cell-cycle progression by activating cyclin-dependent kinase. Based on our
experimental results, we propose here a novel hypothesis that certain amplified
genomic-DNA fragments (AGFs) may also be required for the cell cycle
progression of eukaryotic cells and thus can be named as cell-cycle-associated
AGFs (CAGFs). Like fluctuation in cyclin levels during cell cycle progression,
these CAGFs are amplified and degraded at different points of the cell cycle.
The functions of CAGFs are unknown, but we speculate that CAGFs might be
involved in regulation of gene expression, genome protection, and formation of
certain macromolecular complexes required for the dynamic genome architecture
during cell cycle progression. Our experimental results also show that
chloroquine induces the production of CAGFs in Plasmodium falciparum,
suggesting that targeting cell cycle progression can be the primary mechanism
of chloroquine's antimalarial, anticancer, and immunomodulatory actions.
Viscosity properties with singularities in a state-constrained expected utility maximization problem
Date: 2015-10-13 00:00:00

We consider the value function originating from an expected utility
maximization problem with finite fuel constraint and show its close relation to
a nonlinear parabolic degenerated Hamilton-Jacobi-Bellman (HJB) equation with
singularity. On one hand, we give a so-called verification argument based on
the dynamic programming principle, which allows us to derive conditions under
which a classical solution of the HJB equation coincides with our value
function (provided that it is smooth enough). On the other hand, we establish a
comparison principle, which allows us to characterize our value function as the
unique viscosity solution of the HJB equation.
Performance analysis of the optimal strategy under partial information
Date: 2015-10-13 00:00:00

The question addressed in this paper is the performance of the optimal
strategy, and the impact of partial information. The setting we consider is
that of a stochastic asset price model where the trend follows an unobservable
Ornstein-Uhlenbeck process. We focus on the optimal strategy with a logarithmic
utility function under full or partial information. For both cases, we provide
the asymptotic expectation and variance of the logarithmic return as functions
of the signal-to-noise ratio and of the trend mean reversion speed. Finally, we
compare the asymptotic Sharpe ratios of these strategies in order to quantify
the loss of performance due to partial information.
Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices
Date: 2015-10-10 00:00:00
Tasks: Time Series, Time Series Analysis

How an investor invests in the market is largely influenced by the market
efficiency because if a market is efficient, it is extremely difficult to make
excessive returns because in an efficient market there will be no undervalued
securities i.e. securities whose value is less than its assumed intrinsic
value, which offer returns that are higher than the deserved expected returns,
given their risk. However, there is a possibility of making excessive returns
if the market is not efficient. This article analyses the five popular stock
indices of BSE. This would not only test the efficiency of the Indian Stock
Market but also test the random walk nature of the stock market. The study
undertaken in this paper has provided strong evidence in favor of the
inefficient form of the Indian Stock Market. The series of stock indices in the
Indian Stock Market are found to be biased random time series and the random
walk model can't be applied in the Indian Stock Market. This study confirms
that there is a drift in market efficiency and investors can capitalize on this
by correctly choosing the securities that are undervalued.
A State-Dependent Dual Risk Model
Authors: Lingjiong Zhu
Date: 2015-10-13 00:00:00
Tasks: model

In a dual risk model, the premiums are considered as the costs and the claims are regarded as the profits. The surplus can be interpreted as the wealth of a venture capital, whose profits depend on research and development. In most of the existing literature of dual risk models, the profits follow the compound Poisson model and the cost is constant. In this paper, we develop a state-dependent dual risk model, in which the arrival rate of the profits and the costs depend on the current state of the wealth process. Ruin probabilities are obtained in closed-forms. Further properties and results will also be discussed.
Snowball: Strain aware gene assembly of Metagenomes
Date: 2015-10-13 00:00:00

Gene assembly is an important step in functional analysis of shotgun
metagenomic data. Nonetheless, strain aware assembly remains a challenging
task, as current assembly tools often fail to distinguish among strain variants
or require closely related reference genomes of the studied species to be
available. We have developed Snowball, a novel strain aware and reference-free
gene assembler for shotgun metagenomic data. It uses profile hidden Markov
models (HMMs) of gene domains of interest to guide the assembly. Our assembler
performs gene assembly of individual gene domains based on read overlaps and
error correction using read quality scores at the same time, which result in
very low per-base error rates. The software runs on a user-defined number of
processor cores in parallel, runs on a standard laptop and is freely available
for installation under Linux or OS X on:
https://github.com/algbioi/snowball/wiki
On the Efficient Market Hypothesis of Stock Market Indexes: The Role of Non-synchronous Trading and Portfolio Effects
Date: 2015-10-13 00:00:00

In this article, the long-term behavior of the stock market index of the New
York Stock Exchange is studied, for the period 1950 to 2013. Specifically, the
CRSP Value-Weighted and CRSP Equal-Weighted index are analyzed in terms of
market efficiency, using the standard ratio variance test, considering over
1600 one week rolling windows. For the equally weighted index, the null
hypothesis of random walk is rejected in the whole period, while for the
weighted market value index, the null hypothesis start to be accepted from the
1990s. In order to explain this difference, we raised the hypothesis that this
behavior can be explained by the joint action of portfolios and non-synchronous
trading effects. To check the feasibility of the above assumption, we performed
a simulation of both effects, on two- and six-asset portfolios. The results
showed that it is possible to explain the empirical difference between the two
index, almost entirely by the joint effects of portfolio and non-synchronous
trading.
Pathway Tools version 28.0: Integrated Software for Pathway/Genome Informatics and Systems Biology
Authors: Peter D. Karp, Suzanne M. Paley, Markus Krummenacker, Anamika Kothari, Peter E. Midford, Pallavi Subhraveti, Austin Swart, Lisa Moore, Ron Caspi
Date: 2015-10-14 00:00:00

Pathway Tools is a bioinformatics software environment with a broad set of capabilities. The software provides genome-informatics tools such as a genome browser, sequence alignments, a genome-variant analyzer, and comparative-genomics operations. It offers metabolic-informatics tools, such as metabolic reconstruction, quantitative metabolic modeling, prediction of reaction atom mappings, and metabolic route search. Pathway Tools also provides regulatory-informatics tools, such as the ability to represent and visualize a wide range of regulatory interactions. The software creates and manages a type of organism-specific database called a Pathway/Genome Database (PGDB), which the software enables database curators to interactively edit. It supports web publishing of PGDBs and provides a large number of query, visualization, and omics-data analysis tools. Scientists around the world have created more than 45,000 PGDBs by using Pathway Tools, many of which are curated databases for important model organisms. Those PGDBs can be exchanged using a peer-to-peer database-sharing system called the PGDB Registry.
Insights into the variability of nucleated amyloid polymerization by a minimalistic model of stochastic protein assembly
Date: 2015-10-14 00:00:00

Self-assembly of proteins into amyloid aggregates is an important biological
phenomenon associated with human diseases such as Alzheimer's disease. Amyloid
fibrils also have potential applications in nano-engineering of biomaterials.
The kinetics of amyloid assembly show an exponential growth phase preceded by a
lag phase, variable in duration as seen in bulk experiments and experiments
that mimic the small volumes of cells. Here, to investigate the origins and the
properties of the observed variability in the lag phase of amyloid assembly
currently not accounted for by deterministic nucleation dependent mechanisms,
we formulate a new stochastic minimal model that is capable of describing the
characteristics of amyloid growth curves despite its simplicity. We then solve
the stochastic differential equations of our model and give mathematical proof
of a central limit theorem for the sample growth trajectories of the nucleated
aggregation process. These results give an asymptotic description for our
simple model, from which closed form analytical results capable of describing
and predicting the variability of nucleated amyloid assembly were derived. We
also demonstrate the application of our results to inform experiments in a
conceptually friendly and clear fashion. Our model offers a new perspective and
paves the way for a new and efficient approach on extracting vital information
regarding the key initial events of amyloid formation.