pwc-archive/papers-with-abstracts huggingface dataset:
One bank problem in the federal funds market
Date: 2016-05-24 00:00:00

The model of this paper gives a convenient strategy that a bank in the
federal funds market can use in order to maximize its profit in a
contemporaneous reserve requirement (CRR) regime. The reserve requirements are
determined by the demand deposit process, modelled as a Brownian motion with
drift. We propose a new model in which the cumulative funds purchases and sales
are discounted at possible different rates. We formulate and solve the problem
of finding the bank's optimal strategy. The model can be extended to involve
the bank's asset size and we obtain that, under some conditions, the optimal
upper barrier for fund sales is a linear function of the asset size. As a
consequence, the bank net purchase amount is linear in the asset size.
Bridge the gap between network-based inference method and global ranking method in personal recommendation
Authors: Liu Xiwei
Date: 2015-07-15 00:00:00

In this paper, we study the relationship between the network-based inference
method and global ranking method in personal recommendation. By some
theoretical analysis, we prove that the recommendation result under the global
ranking method is the limit of applying network-based inference method with
infinity times.
Generalization of neuron network model with delay feedback
Date: 2015-07-16 00:00:00
Tasks: Form, model

We present generalized delayed neural network (DNN) model with positive delay
feedback and neuron history. The local stability analysis around trivial local
equilibria of delayed neural networks has applied and determine the conditions
for the existence of zero root. We develop few innovative delayed neural
network models in different dimensions through transformation and extension of
some existing models. We found that zero root can have multiplicity two under
certain conditions. We further show how the characteristic equation can have
zero root and its multiplicity is dependent on the conditions undertaken.
Finally, we generalize the neural network of $N$ neurons through which we
determine the general form of Jacobian of the linear form and corresponding
characteristic equation of the system.
Insurance makes wealth grow faster
Date: 2017-07-13 00:00:00

Voluntary insurance contracts constitute a puzzle because they increase the
expectation value of one party's wealth, whereas both parties must sign for
such contracts to exist. Classically, the puzzle is resolved by introducing
non-linear utility functions, which encode asymmetric risk preferences; or by
assuming the parties have asymmetric information. Here we show the puzzle goes
away if contracts are evaluated by their effect on the time-average growth rate
of wealth. Our solution assumes only knowledge of wealth dynamics. Time
averages and expectation values differ because wealth changes are non-ergodic.
Our reasoning is generalisable: business happens when both parties grow faster.
Semi-parametric time series modelling with autocopulas
Date: 2015-07-16 00:00:00
Tasks: Time Series, Time Series Analysis

In this paper we present an application of the use of autocopulas for
modelling financial time series showing serial dependencies that are not
necessarily linear. The approach presented here is semi-parametric in that it
is characterized by a non-parametric autocopula and parametric marginals. One
advantage of using autocopulas is that they provide a general representation of
the auto-dependency of the time series, in particular making it possible to
study the interdependence of values of the series at different extremes
separately. The specific time series that is studied here comes from daily cash
flows involving the product of daily natural gas price and daily temperature
deviations from normal levels. Seasonality is captured by using a time
dependent normal inverse Gaussian (NIG) distribution fitted to the raw values.
Tanglegrams: a reduction tool for mathematical phylogenetics
Date: 2015-07-16 00:00:00

Many discrete mathematics problems in phylogenetics are defined in terms of
the relative labeling of pairs of leaf-labeled trees. These relative labelings
are naturally formalized as tanglegrams, which have previously been an object
of study in coevolutionary analysis. Although there has been considerable work
on planar drawings of tanglegrams, they have not been fully explored as
combinatorial objects until recently. In this paper, we describe how many
discrete mathematical questions on trees "factor" through a problem on
tanglegrams, and how understanding that factoring can simplify analysis.
Depending on the problem, it may be useful to consider a unordered version of
tanglegrams, and/or their unrooted counterparts. For all of these definitions,
we show how the isomorphism types of tanglegrams can be understood in terms of
double cosets of the symmetric group, and we investigate their automorphisms.
Understanding tanglegrams better will isolate the distinct problems on
leaf-labeled pairs of trees and reveal natural symmetries of spaces associated
with such problems.
Study of the Effects of High-Energy Proton Beams on Escherichia Coli
Date: 2015-07-17 00:00:00

Antibiotic-resistant bacterial infection becomes one of the most serious
risks to public health care today. However, discouragingly, the development of
new antibiotics has been little progressed over the last decade. There is an
urgent need of the alternative approaches to treat the antibiotic-resistant
bacteria. The novel methods, which include photothermal therapy based on gold
nano-materials and ionizing radiation such as X-rays and gamma rays, have been
reported. Studies of the effects of high-energy proton radiation on bacteria
are mainly focused on Bacillus species and its spores. The effect of proton
beams on Escherichia coli (E. coli) has been limitedly reported. The
Escherichia coli is an important biological tool to obtain the metabolic and
genetic information and also a common model microorganism for studying toxicity
and antimicrobial activity. In addition, E. coli is a common bacterium in the
intestinal tract of mammals. Herein, the morphological and physiological
changes of E. coli after proton irradiation were investigated. The diluted
solutions of the cells were used for proton beam radiation. LB agar plates were
used to count the number of colonies formed. The growing profile of the cells
was monitored by optical density at 600 nm. The morphology of the irradiated
cells was analyzed with optical microscope. Microarray analysis was performed
to examine the gene expression changes between irradiated samples and control
samples without irradiation.
Quantile Correlations: Uncovering temporal dependencies in financial time series
Date: 2015-07-17 00:00:00
Tasks: Time Series, Time Series Analysis

We conduct an empirical study using the quantile-based correlation function
to uncover the temporal dependencies in financial time series. The study uses
intraday data for the S\&P 500 stocks from the New York Stock Exchange. After
establishing an empirical overview we compare the quantile-based correlation
function to stochastic processes from the GARCH family and find striking
differences. This motivates us to propose the quantile-based correlation
function as a powerful tool to assess the agreements between stochastic
processes and empirical data.
Molecular geometry of alkaloids present in seeds of mexican prickly poppy
Date: 2015-07-15 00:00:00

The work is a study of the geometry of the molecules via molecular mechanics
of the main alkaloids found in the seeds of Argemone Mexicana Linn, a prickly
poppy, which is considered one of the most important species of plants in
traditional Mexican and Indian medicine system. The seeds have toxic properties
as well as bactericide, hallucinogenic, fungicide, insecticide, in
isoquinolines and sanguinarine alkaloids such as berberine. A computational
study of the molecular geometry of the molecules through molecular mechanics of
the main alkaloids compounds present in plant seeds is described in a computer
simulation. The plant has active ingredients compounds: allocryptopine,
berberine, chelerythrine, copsitine, dihydrosanguinarine, protopine and
sanguinarine. The studied alkaloids form two groups having similar charge
distribution among themselves, which have dipole moments of these two times
higher than in the other group.
Six General Ecosystem Properties are more Intense in Biogeochemical Cycling Networks than Food Webs
Date: 2015-08-27 00:00:00

Network analysis has revealed whole-network properties hypothesized to be
general characteristics of ecosystems including pathway proliferation, and
network non-locality, homogenization, amplification, mutualism, and synergism.
Collectively these properties characterize the impact of indirect interactions
among ecosystem elements. While ecosystem networks generally trace a
thermodynamically conserved unit through the system, there appear to be several
model classes. For example, trophic (TRO) networks are built upon a food web,
usually follow energy or carbon, and are the most abundant in the literature.
Biogeochemical cycling (BGC) networks trace nutrients like nitrogen or
phosphorus and tend to have more recycling than TRO. We tested (1) the
hypothesized generality of the properties in BGC networks and (2) that they
tend to be more strongly expressed in BGC networks than in the TRO networks due
to increased recycling. We compared the properties in 22 BGC and 57 TRO
ecosystem networks from the literature using enaR. The results generally
support the hypotheses. First, five of the properties occurred in all 22 BGC
models, while network mutualism occurred in 86% of the models. Further, these
results were generally robust to a $\pm$50% uncertainty in the model
parameters. Second, the mean network statistics for the six properties were
statistically significantly greater in the BGC models than the TRO models.
These results (1) confirm the general presence of these properties in ecosystem
networks, (2) highlight the significance of model types in determining property
intensities, (3) reinforce the importance of recycling, and (4) provide a set
of indicator benchmarks for future systems comparisons. Further, this work
highlights how indirect effects distributed by network connectivity can
transform whole-ecosystem functioning, and adds to the growing domain of
network ecology.
Pricing American and Asian Options
Date: 2015-08-23 00:00:00

An analytic method for pricing American call options is provided; followed by
an empirical method for pricing Asian call options. The methodology is the
pricing theory presented in "A Modern Theory of Random Variation", by Patrick
Muldowney, 2012.
Towards Understanding User Preferences from User Tagging Behavior for Personalization
Authors: Nwana Amandianeze O., Chen Tshuan
Date: 2015-11-20 00:00:00
Tasks: TAG

Personalizing image tags is a relatively new and growing area of research,
and in order to advance this research community, we must review and challenge
the de-facto standard of defining tag importance. We believe that for greater
progress to be made, we must go beyond tags that merely describe objects that
are visually represented in the image, towards more user-centric and subjective
notions such as emotion, sentiment, and preferences.
  We focus on the notion of user preferences and show that the order that users
list tags on images is correlated to the order of preference over the tags that
they provided for the image. While this observation is not completely
surprising, to our knowledge, we are the first to explore this aspect of user
tagging behavior systematically and report empirical results to support this
observation. We argue that this observation can be exploited to help advance
the image tagging (and related) communities.
  Our contributions include: 1.) conducting a user study demonstrating this
observation, 2.) collecting a dataset with user tag preferences explicitly
collected.
Stochastic model of financial markets reproducing scaling and memory in volatility return intervals
Date: 2016-10-25 00:00:00

We investigate the volatility return intervals in the NYSE and FOREX markets.
We explain previous empirical findings using a model based on the interacting
agent hypothesis instead of the widely-used efficient market hypothesis. We
derive macroscopic equations based on the microscopic herding interactions of
agents and find that they are able to reproduce various stylized facts of
different markets and different assets with the same set of model parameters.
We show that the power-law properties and the scaling of return intervals and
other financial variables have a similar origin and could be a result of a
general class of non-linear stochastic differential equations derived from a
master equation of an agent system that is coupled by herding interactions.
Specifically, we find that this approach enables us to recover the volatility
return interval statistics as well as volatility probability and spectral
densities for the NYSE and FOREX markets, for different assets, and for
different time-scales. We find also that the historical S\&P500 monthly series
exhibits the same volatility return interval properties recovered by our
proposed model. Our statistical results suggest that human herding is so strong
that it persists even when other evolving fluctuations perturbate the financial
system.
A tree metric using structure and length to capture distinct phylogenetic signals
Date: 2015-09-11 00:00:00

Phylogenetic trees are a central tool in understanding evolution. They are
typically inferred from sequence data, and capture evolutionary relationships
through time. It is essential to be able to compare trees from different data
sources (e.g. several genes from the same organisms) and different inference
methods. We propose a new metric for robust, quantitative comparison of rooted,
labeled trees. It enables clear visualizations of tree space, gives meaningful
comparisons between trees, and can detect distinct islands of tree topologies
in posterior distributions of trees. This makes it possible to select
well-supported summary trees. We demonstrate our approach on Dengue fever
phylogenies.
On the Application of Link Analysis Algorithms for Ranking Bipartite Graphs
Authors: Korba Antonia
Date: 2015-07-18 00:00:00
Tasks: Information Retrieval, Retrieval

Recently bipartite graphs have been widely used to represent the relationship
two sets of items for information retrieval applications. The Web offers a wide
range of data which can be represented by bipartite graphs, such us movies and
reviewers in recomender systems, queries and URLs in search engines, users and
posts in social networks. The size and the dynamic nature of such graphs
generate the need for more efficient ranking methods.
  In this thesis, at first we present the fundamental mathematical backround
that we use subsequently and we describe the basic principles of the
Perron-Frobebius theory for non negative matrices as well as the the basic
principles of the Markov chain theory. Then, we propose a novel algorithm named
BipartiteRank, which is suitable to rank scenarios, that can be represented as
a bipartite graph. This algorithm is based on the random surfer model and
inherits the basic mathematical characteristics of PageRank. What makes it
different, is the fact that it introduces an alternative type of teleportation,
based on the block structure of the bipartite graph in order to achieve more
efficient ranking. Finally, we support this opinion with mathematical arguments
and then we confirm it experimentally through a series of tests on real data.
Diversity improves performance in excitable networks
Date: 2015-07-19 00:00:00
Tasks: Diversity

As few real systems comprise indistinguishable units, diversity is a hallmark
of nature. Diversity among interacting units shapes properties of collective
behavior such as synchronization and information transmission. However, the
benefits of diversity on information processing at the edge of a phase
transition, ordinarily assumed to emerge from identical elements, remain
largely unexplored. Analyzing a general model of excitable systems with
heterogeneous excitability, we find that diversity can greatly enhance optimal
performance (by two orders of magnitude) when distinguishing incoming inputs.
Heterogeneous systems possess a subset of specialized elements whose capability
greatly exceeds that of the nonspecialized elements. Nonetheless, the behavior
of the whole network can outperform all subgroups. We also find that diversity
can yield multiple percolation, with performance optimized at tricriticality.
Our results are robust in specific and more realistic neuronal systems
comprising a combination of excitatory and inhibitory units, and indicate that
diversity-induced amplification can be harnessed by neuronal systems for
evaluating stimulus intensities.
Dynamical system theory of periodically collapsing bubbles
Date: 2015-07-19 00:00:00

We propose a reduced form set of two coupled continuous time equations
linking the price of a representative asset and the price of a bond, the later
quantifying the cost of borrowing. The feedbacks between asset prices and bonds
are mediated by the dependence of their "fundamental values" on past asset
prices and bond themselves. The obtained nonlinear self-referencing price
dynamics can induce, in a completely objective deterministic way, the
appearance of periodically exploding bubbles ending in crashes. Technically,
the periodically explosive bubbles arise due to the proximity of two types of
bifurcations as a function of the two key control parameters $b$ and $g$, which
represent, respectively, the sensitivity of the fundamental asset price on past
asset and bond prices and of the fundamental bond price on past asset prices.
One is a Hopf bifurcation, when a stable focus transforms into an unstable
focus and a limit cycle appears. The other is a rather unusual bifurcation,
when a stable node and a saddle merge together and disappear, while an unstable
focus survives and a limit cycle develops. The lines, where the periodic
bubbles arise, are analogous to the critical lines of phase transitions in
statistical physics. The amplitude of bubbles and waiting times between them
respectively diverge with the critical exponents $\gamma = 1$ and $\nu = 1/2$,
as the critical lines are approached.
The geometry of coexistence in large ecosystems
Date: 2016-06-14 00:00:00

The role of species interactions in controlling the interplay between the
stability of an ecosystem and its biodiversity is still not well understood.
The ability of ecological communities to recover after a small perturbation of
the species abundances (local asymptotic stability) has been well studied,
whereas the likelihood of a community to persist when the interactions are
altered (structural stability) has received much less attention. Our goal is to
understand the effects of diversity, interaction strenghts and ecological
network structure on the volume of parameter space leading to feasible
equilibria, i.e., ones in which all populations have positive abundances. We
develop a geometrical framework to study the range of conditions necessary for
feasible coexistence in both mutualistic and consumer-resource systems. Using
analytical and numerical methods, we show that feasibility is determined by
just a handful of quantities describing the interactions, yielding a nontrivial
complexity-feasibility relationship. Analyzing more than 100 empirical
networks, we show that the range of coexistence conditions in mutualistic
systems can be analytically predicted by means of a null model of random
interactions, whereas food webs are characterized by smaller coexistence
domains than those expected by chance. Finally, we characterize the geometric
shape of the feasibility domain, thereby identifying the direction of
perturbations that are more likely to cause extinctions. Interestingly, the
structure of mutualistic interactions leads to very heterogeneous responses to
perturbations, making those systems more fragile than expected by chance.
Rapidly evolving in humans topologically associating domains
Date: 2015-07-20 00:00:00

Genome-wide proximity placement analysis of 10,598 HSGRL within the context
of the principal regulatory structures of the interphase chromatin, namely
topologically-associating domains (TADs) and specific sub-TAD structures termed
super-enhancer domains (SEDs) revealed that 0.8%-10.3% of TADs contain more
than half of HSGRL. Of the 3,127 TADs in the hESC genome, 24 (0.8%); 53 (1.7%);
259 (8.3%); and 322 (10.3%) harbor 1,110 (52.4%); 1,936 (50.9%); 1,151 (59.6%);
and 1,601 (58.3%) HSGRL sequences from four distinct families, respectively.
TADs that are enriched for HSGRL and termed rapidly-evolving in humans TADs
(revTADs) manifest distinct correlation patterns between HSGRL placements and
recombination rates. There are significant enrichment within revTAD boundaries
of hESC-enhancers, primate-specific CTCF-binding sites, human-specific
RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific
enrichment at TSS in prefrontal cortex neurons (p < 0.0001 in all instances).
In hESC genome, 331 of 504 (66%) of SE-harboring TADs contain HSGRL and 68% of
SEs co-localize with HSGRL, suggesting that HSGRL rewired SE-driven GRNs within
revTADs by inserting novel and/or erasing existing regulatory sequences.
Consequently, markedly distinct features of chromatin structures evolved in
hESC compared to mouse: the SE quantity is 3-fold higher and the median SE size
is significantly larger; concomitantly, the TAD number is increased by 42%
while the median TAD size is decreased (p=9.11E-37). Present analyses revealed
a global role for HSGRL in increasing both quantity and size of SEs and
increasing the number and size reduction of TADs, which may facilitate a
convergence of TAD and SED architectures of interphase chromatin and define a
trend of increasing regulatory complexity during evolution of GRNs.
Endogenous Derivation and Forecast of Lifetime PDs
Authors: Volodymyr Perederiy
Date: 2015-07-20 00:00:00

This paper proposes a simple technical approach for the analytical derivation of Point-in-Time PD (probability of default) forecasts, with minimal data requirements. The inputs required are the current and future Through-the-Cycle PDs of the obligors, their last known default rates, and a measurement of the systematic dependence of the obligors. Technically, the forecasts are made from within a classical asset-based credit portfolio model, with the additional assumption of a simple (first/second order) autoregressive process for the systematic factor. This paper elaborates in detail on the practical issues of implementation, especially on the parametrization alternatives. We also show how the approach can be naturally extended to low-default portfolios with volatile default rates, using Bayesian methodology. Furthermore, expert judgments on the current macroeconomic state, although not necessary for the forecasts, can be embedded into the model using the Bayesian technique. The resulting PD forecasts can be used for the derivation of expected lifetime credit losses as required by the newly adopted accounting standard IFRS 9. In doing so, the presented approach is endogenous, as it does not require any exogenous macroeconomic forecasts, which are notoriously unreliable and often subjective. Also, it does not require any dependency modeling between PDs and macroeconomic variables, which often proves to be cumbersome and unstable.
Muckenhoupt's $(A_p)$ condition and the existence of the optimal martingale measure
Date: 2015-07-21 00:00:00

In the problem of optimal investment with utility function defined on
$(0,\infty)$, we formulate sufficient conditions for the dual optimizer to be a
uniformly integrable martingale. Our key requirement consists of the existence
of a martingale measure whose density process satisfies the probabilistic
Muckenhoupt $(A_p)$ condition for the power $p=1/(1-a)$, where $a\in (0,1)$ is
a lower bound on the relative risk-aversion of the utility function. We
construct a counterexample showing that this $(A_p)$ condition is sharp.