pwc-archive/papers-with-abstracts huggingface dataset:
Nonlinear PDEs risen when solving some optimization problems in finance, and their solutions
Date: 2015-10-16 00:00:00

We consider a specific type of nonlinear partial differential equations (PDE)
that appear in mathematical finance as the result of solving some optimization
problems. We review some existing in the literature examples of such problems,
and discuss the properties of these PDEs. We also demonstrate how to solve them
numerically in a general case, and analytically in some particular case.
Detrended cross-correlations between returns, volatility, trading activity, and volume traded for the stock market companies
Date: 2015-11-10 00:00:00

We consider a few quantities that characterize trading on a stock market in a
fixed time interval: logarithmic returns, volatility, trading activity (i.e.,
the number of transactions), and volume traded. We search for the power-law
cross-correlations among these quantities aggregated over different time units
from 1 min to 10 min. Our study is based on empirical data from the American
stock market consisting of tick-by-tick recordings of 31 stocks listed in Dow
Jones Industrial Average during the years 2008-2011. Since all the considered
quantities except the returns show strong daily patterns related to the
variable trading activity in different parts of a day, which are the best
evident in the autocorrelation function, we remove these patterns by detrending
before we proceed further with our study. We apply the multifractal detrended
cross-correlation analysis with sign preserving (MFCCA) and show that the
strongest power-law cross-correlations exist between trading activity and
volume traded, while the weakest ones exist (or even do not exist) between the
returns and the remaining quantities. We also show that the strongest
cross-correlations are carried by those parts of the signals that are
characterized by large and medium variance. Our observation that the most
convincing power-law cross-correlations occur between trading activity and
volume traded reveals the existence of strong fractal-like coupling between
these quantities.
Optimal Investment in a Dual Risk Model
Authors: Arash Fahim, Lingjiong Zhu
Date: 2015-10-16 00:00:00
Tasks: model

Dual risk models are popular for modeling a venture capital or high tech company, for which the running cost is deterministic and the profits arrive stochastically over time. Most of the existing literature on dual risk models concentrated on the optimal dividend strategies. In this paper, we propose to study the optimal investment strategy on research and development for the dual risk models to minimize the ruin probability of the underlying company. We will also study the optimization problem when in addition the investment in a risky asset is allowed.
Multifractal Flexibly Detrended Fluctuation Analysis
Date: 2015-10-17 00:00:00
Tasks: Time Series, Time Series Analysis

Multifractal time series analysis is a approach that shows the possible
complexity of the system. Nowadays, one of the most popular and the best
methods for determining multifractal characteristics is Multifractal Detrended
Fluctuation Analysis (MFDFA). However, it has some drawback. One of its core
elements is detrending of the series. In the classical MFDFA a trend is
estimated by fitting a polynomial of degree $m$ where $m=const$. We propose
that the degree $m$ of a polynomial was not constant ($m\neq const$) and its
selection was ruled by an established criterion. Taking into account the above
amendment, we examine the multifractal spectra both for artificial and
real-world mono- and the multifractal time series. Unlike classical MFDFA
method, obtained singularity spectra almost perfectly reflects the theoretical
results and for real time series we observe a significant right side shift of
the spectrum.
Bibliometric-Enhanced Information Retrieval: 3rd International BIR Workshop
Authors: Mayr Philipp, Frommholz Ingo, Cabanac Guillaume
Date: 2015-12-18 00:00:00
Tasks: Information Retrieval, Retrieval

The BIR workshop brings together experts in Bibliometrics and Information
Retrieval. While sometimes perceived as rather loosely related, these research
areas share various interests and face similar challenges. Our motivation as
organizers of the BIR workshop stemmed from a twofold observation. First, both
communities only partly overlap, albeit sharing various interests. Second, it
will be profitable for both sides to tackle some of the emerging problems that
scholars face today when they have to identify relevant and high quality
literature in the fast growing number of electronic publications available
worldwide. Bibliometric techniques are not yet used widely to enhance retrieval
processes in digital libraries, although they offer value-added effects for
users. Information professionals working in libraries and archives, however,
are increasingly confronted with applying bibliometric techniques in their
services. The first BIR workshop in 2014 set the research agenda by introducing
each group to the other, illustrating state-of-the-art methods, reporting on
current research problems, and brainstorming about common interests. The second
workshop in 2015 further elaborated these themes. This third BIR workshop aims
to foster a common ground for the incorporation of bibliometric-enhanced
services into scholarly search engine interfaces. In particular we will address
specific communities, as well as studies on large, cross-domain collections
like Mendeley and ResearchGate. This third BIR workshop addresses explicitly
both scholarly and industrial researchers.
Optimal growth trajectories with finite carrying capacity
Date: 2016-06-20 00:00:00

We consider the problem of finding optimal strategies that maximize the
average growth-rate of multiplicative stochastic processes. For a geometric
Brownian motion the problem is solved through the so-called Kelly criterion,
according to which the optimal growth rate is achieved by investing a constant
given fraction of resources at any step of the dynamics. We generalize these
finding to the case of dynamical equations with finite carrying capacity, which
can find applications in biology, mathematical ecology, and finance. We
formulate the problem in terms of a stochastic process with multiplicative
noise and a non-linear drift term that is determined by the specific functional
form of carrying capacity. We solve the stochastic equation for two classes of
carrying capacity functions (power laws and logarithmic), and in both cases
compute optimal trajectories of the control parameter. We further test the
validity of our analytical results using numerical simulations.
Viral epidemiology of the adult Apis Mellifera infested by the Varroa destructor mite
Date: 2016-04-30 00:00:00
Tasks: Epidemiology

The ectoparasitic mite Varroa destructor has become one of the major
worldwide threats for apiculture. Varroa destructor attacks the honey bee Apis
mellifera weakening its host by sucking hemolymph. However, the damage to bee
colonies is not strictly related to the parasitic action of the mite but it
derives, above all, from its action as vector increasing the trasmission of
many viral diseases such as acute paralysis (ABPV) and deformed wing viruses
(DWV), that are considered among the main causes of CCD (Colony Collapse
Disorder). In this work we discuss an SI model that describes how the presence
of the mite affects the epidemiology of these viruses on adult bees. We
characterize the system behavior, establishing that ultimately either only
healthy bees survive, or the disease becomes endemic and mites are wiped out.
Another dangerous alternative is the Varroa invasion scenario with the
extinction of healthy bees. The final possible configuration is the coexistence
equilibrium in which honey bees share their infected hive with mites. The
analysis is in line with some observed facts in natural honey bee colonies.
Namely, these diseases are endemic. Further, if the mite population is present,
necessarily the viral infection occurs. The findings of this study indicate
that a low horizontal transmission rate of the virus among honey bees in
beehives will help in protecting bee colonies from Varroa infestation and viral
epidemics.
On the characterization of flowering curves using Gaussian mixture models
Date: 2016-04-18 00:00:00

In this paper, we develop a statistical methodology applied to the
characterization of flowering curves using Gaussian mixture models. Our study
relies on a set of rosebushes flowering data, and Gaussian mixture models are
mainly used to quantify the reblooming properties of each one. In this regard,
we also suggest our own selection criterion to take into account the lack of
symmetry of most of the flowering curves. Three classes are created on the
basis of a principal component analysis conducted on a set of reblooming
indicators, and a subclassification is made using a longitudinal $k$--means
algorithm which also highlights the role played by the precocity of the
flowering. In this way, we obtain an overview of the correlations between the
features we decided to retain on each curve. In particular, results suggest the
lack of correlation between reblooming and flowering precocity. The pertinent
indicators obtained in this study will be a first step towards the
comprehension of the environmental and genetic control of these biological
processes.
Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence
Date: 2016-01-20 00:00:00

Many of the observed species interactions embedded in ecological communities
are not permanent, but are characterized by temporal changes that are observed
along with abiotic and biotic variations. While work has been done describing
and quantifying these changes, little is known about their consequences for
species coexistence. Here, we investigate the extent to which changes of
species composition impacts the likelihood of persistence of the predator-prey
community in the highly seasonal Bialowieza Primeval Forest (NE Poland), and
the extent to which seasonal changes of species interactions (predator diet)
modulate the expected impact. This likelihood is estimated extending recent
developments on the study of structural stability in ecological communities. We
find that the observed species turnover strongly varies the likelihood of
community persistence between summer and winter. Importantly, we demonstrate
that the observed seasonal interaction changes minimize the variation in the
likelihood of persistence associated with species turnover across the year. We
find that these community dynamics can be explained as the coupling of
individual species to their environment by minimizing both the variation in
persistence conditions and the interaction changes between seasons. Our results
provide a homeostatic explanation for seasonal species interactions, and
suggest that monitoring the association of interactions changes with the level
of variation in community dynamics can provide a good indicator of the response
of species to environmental pressures.
Social Media Analysis for Product Safety using Text Mining and Sentiment Analysis
Authors: Isah Haruna, Neagu Daniel, Trundle Paul
Date: 2015-10-18 00:00:00
Tasks: BIG-bench Machine Learning, Sentiment Analysis

The growing incidents of counterfeiting and associated economic and health
consequences necessitate the development of active surveillance systems capable
of producing timely and reliable information for all stake holders in the
anti-counterfeiting fight. User generated content from social media platforms
can provide early clues about product allergies, adverse events and product
counterfeiting. This paper reports a work in progresswith contributions
including: the development of a framework for gathering and analyzing the views
and experiences of users of drug and cosmetic products using machine learning,
text mining and sentiment analysis, the application of the proposed framework
on Facebook comments and data from Twitter for brand analysis, and the
description of how to develop a product safety lexicon and training data for
modeling a machine learning classifier for drug and cosmetic product sentiment
prediction. The initial brand and product comparison results signify the
usefulness of text mining and sentiment analysis on social media data while the
use of machine learning classifier for predicting the sentiment orientation
provides a useful tool for users, product manufacturers, regulatory and
enforcement agencies to monitor brand or product sentiment trends in order to
act in the event of sudden or significant rise in negative sentiment.
EdgeCentric: Anomaly Detection in Edge-Attributed Networks
Authors: Shah Neil, Beutel Alex, Hooi Bryan, Akoglu Leman, Gunnemann Stephan, Makhija Disha, Kumar Mohit, Faloutsos Christos
Date: 2015-11-18 00:00:00
Tasks: Anomaly Detection

Given a network with attributed edges, how can we identify anomalous
behavior? Networks with edge attributes are commonplace in the real world. For
example, edges in e-commerce networks often indicate how users rated products
and services in terms of number of stars, and edges in online social and
phonecall networks contain temporal information about when friendships were
formed and when users communicated with each other -- in such cases, edge
attributes capture information about how the adjacent nodes interact with other
entities in the network. In this paper, we aim to utilize exactly this
information to discern suspicious from typical node behavior. Our work has a
number of notable contributions, including (a) formulation: while most other
graph-based anomaly detection works use structural graph connectivity or node
information, we focus on the new problem of leveraging edge information, (b)
methodology: we introduce EdgeCentric, an intuitive and scalable
compression-based approach for detecting edge-attributed graph anomalies, and
(c) practicality: we show that EdgeCentric successfully spots numerous such
anomalies in several large, edge-attributed real-world graphs, including the
Flipkart e-commerce graph with over 3 million product reviews between 1.1
million users and 545 thousand products, where it achieved 0.87 precision over
the top 100 results.
A Supermartingale Relation for Multivariate Risk Measures
Date: 2018-01-31 00:00:00
Tasks: Relation

The equivalence between multiportfolio time consistency of a dynamic
multivariate risk measure and a supermartingale property is proven.
Furthermore, the dual variables under which this set-valued supermartingale is
a martingale are characterized as the worst-case dual variables in the dual
representation of the risk measure. Examples of multivariate risk measures
satisfying the supermartingale property are given. Crucial for obtaining the
results are dual representations of scalarizations of set-valued dynamic risk
measures, which are of independent interest in the fast growing literature on
multivariate risks.
The site frequency spectrum for general coalescents
Date: 2016-02-11 00:00:00

General genealogical processes such as $\Lambda$- and $\Xi$-coalescents,
which respectively model multiple and simultaneous mergers, have important
applications in studying marine species, strong positive selection, recurrent
selective sweeps, strong bottlenecks, large sample sizes, and so on. Recently,
there has been significant progress in developing useful inference tools for
such general models. In particular, inference methods based on the site
frequency spectrum (SFS) have received noticeable attention. Here, we derive a
new formula for the expected SFS for general $\Lambda$- and $\Xi$-coalescents,
which leads to an efficient algorithm. For time-homogeneous coalescents, the
runtime of our algorithm for computing the expected SFS is $O(n^2)$, where $n$
is the sample size. This is a factor of $n^2$ faster than the state-of-the-art
method. Furthermore, in contrast to existing methods, our method generalizes to
time-inhomogeneous $\Lambda$- and $\Xi$-coalescents with measures that
factorize as $\Lambda(dx)/\zeta(t)$ and $\Xi(dx)/\zeta(t)$, respectively, where
$\zeta$ denotes a strictly positive function of time. The runtime of our
algorithm in this setting is $O(n^3)$. We also obtain general theoretical
results for the identifiability of the $\Lambda$ measure when $\zeta$ is a
constant function, as well as for the identifiability of the function $\zeta$
under a fixed $\Xi$ measure.
The Impact of Environmental Fluctuations on Evolutionary Fitness Functions
Date: 2015-10-19 00:00:00

The concept of fitness as a measure for a species's success in natural
selection is central to the theory of evolution. We here investigate how
reproduction rates which are not constant but vary in response to environmental
fluctuations, influence a species' prosperity and thereby its fitness.
Interestingly, we find that not only larger growth rates but also reduced
sensitivities to environmental changes substantially increase the fitness.
Thereby, depending on the noise level of the environment, it might be an
evolutionary successful strategy to minimize this sensitivity rather than to
optimize the reproduction speed. Also for neutral evolution, where species with
exactly the same properties compete, variability in the growth rates plays a
crucial role. The time for one species to fixate is strongly reduced in the
presence of environmental noise. Hence, environmental fluctuations constitute a
possible explanation for effective population sizes inferred from genetic data
that often are much smaller than the census population size.
Basic industrial funds of cargo motor transport enterprises: problems of effective use
Date: 2015-10-13 00:00:00
Tasks: Management

This work investigates the structure of basic industrial funds of cargo motor
transport enterprises and peculiarities of the processes of their reproduction
in the conditions of social and economic relations transformation. On the basis
of statistic data of cargo-motor transport enterprises of Ivano-Frankivsk, Lviv
and Ternopil regions the author investigates the effect of production factors
on the level of capital productivity of the basic funds, he determines reserves
of its increase. The author motivates the necessity of adaptive qualitative
changes in the management and realization of industrial potential and
innovations activization in the sphere of cargo motor transportations,
scientiffically grounded recommendations for efficiency increase of the usage
of basic industrial funds of cargo motor transportation enterprises in modern
economic conditions are provided in this work.
Local dynamics of the coffee rust disease and the potential effect of shade
Date: 2015-10-20 00:00:00
Tasks: Management

In this paper we present a mode that incorporates two levels of dynamic
structuring of the coffee rust disease (caused by the rust fungus, Hemileia
vastatrix). First, two distinct spatial scales of transmission dynamics are
interrogated with respect to the resultant structure of catastrophic
transitions of epidemics. Second the effect of management style, especially the
well-known issue of shade management, is added to the base-line model. The
final structure includes a simple one-to-one functional structure of disease
incidence as a function as well as a classical critical transition structure,
and finally a hysteretic loop. These qualitative structures accord well with
the recent history of the coffee rust disease.
Discrete gene replication events drive coupling between the cell cycle and circadian clocks
Date: 2015-10-20 00:00:00

Many organisms possess both a cell cycle to control DNA replication and a
circadian clock to anticipate changes between day and night. In some cases,
these two rhythmic systems are known to be coupled by specific,
cross-regulatory interactions. Here, we use mathematical modeling to show that,
additionally, the cell cycle generically influences circadian clocks in a
non-specific fashion: The regular, discrete jumps in gene-copy number arising
from DNA replication during the cell cycle cause a periodic driving of the
circadian clock, which can dramatically alter its behavior and impair its
function. A clock built on negative transcriptional feedback either phase locks
to the cell cycle, so that the clock period tracks the cell division time, or
exhibits erratic behavior. We argue that the cyanobacterium Synechococcus
elongatus has evolved two features that protect its clock from such
disturbances, both of which are needed to fully insulate it from the cell cycle
and give it its observed robustness: a phosphorylation-based protein
modification oscillator, together with its accompanying push-pull read-out
circuit that responds primarily to the ratios of the different phosphoforms,
makes the clock less susceptible to perturbations in protein synthesis; and the
presence of multiple, asynchronously replicating copies of the same chromosome
diminishes the effect of replicating any single copy of a gene.
Estimating the Impact of Wind Generation in the UK
Date: 2015-11-13 00:00:00

This paper studies the impact of wind generation on market prices and system
costs in the UK between 2013 and 2014. The wider effects and implications of
wind generation is of direct relevance and importance to policy makers, as well
as the grid operator and market traders. We compare electricity generation from
Coal, Gas and wind, on both the wholesale and imbalance market. We calculate
the system cost of wind generation (government subsidies and curtailment costs)
and the total energy costs. For the first time in the UK, we calculate the
Merit Order Effect on spot price due to the wind component and show a $1.67\%$
price decrease for every percentage point of wind generation (compared to the
``zero-wind'' price). The net result of total costs and price savings is
roughly zero (slight positive gain). We also consider the effect of not having
either an onshore or an offshore wind component. We show that the Merit-Order
Effect savings are heavily reduced, leading to an outgoing cost of wind
generation in both cases. It is therefore important to have a significant total
percentage of wind generation, from both onshore and offshore farms.
A martingale representation theorem and valuation of defaultable securities
Date: 2018-05-29 00:00:00

We consider a market model where there are two levels of information. The
public information generated by the financial assets, and a larger flow of
information that contains additional knowledge about a random time. This random
time can represent many economic and financial settings, such as the default
time of a firm for credit risk, and the death time of an insured for life
insurance. By using the expansion of filtration, the random time uncertainty
and its entailed risk are fully considered without any mathematical
restriction. In this context with no model's specification for the random time,
the main challenge lies in finding the dynamics and the structures for the
value processes of defaultable or mortality and/or longevity securities which
are vital for the insurance securitization. To overcome this obstacle, we
elaborate our optional martingale representation results, which state that any
martingale in the large filtration stopped at the random time can be decomposed
into precise and unique orthogonal local martingales (i.e. local martingales
whose product remains a local martingale). This constitutes our first and
probably the principal contribution. Even though the driving motivation for
this representation resides in credit risk theory, our results are applicable
to several other financial and economics contexts, such as life insurance and
financial markets with random horizon. Thanks to this optional representation,
we decompose any defaultable or mortality and/or longevity liability into the
sum of "non-correlated" risks using a risk basis. This constitutes our second
contribution.