pwc-archive/papers-with-abstracts huggingface dataset:
Methodological thoughts on expected loss estimates for IFRS 9 impairment: hidden reserves, cyclical loss predictions and LGD backtesting
Date: 2015-08-11 00:00:00

After the release of the final accounting standards for impairment in July
2014 by the IASB, banks will face the next significant methodological challenge
after Basel 2. In this paper, first methodological thoughts are presented, and
ways how to approach underlying questions are proposed. It starts with a
detailed discussion of the structural conservatism in the final standard. The
exposure value iACV(c) (idealized Amortized Cost Value), as originally
introduced in the Exposure Draft 2009 (ED 2009), will be interpreted as
economic value under amortized cost accounting and provides the valuation
benchmark under IFRS 9. Consequently, iACV(c) can be used to quantify
conservatism (ie potential hidden reserves) in the actual implementation of the
final standard and to separate operational side-effects caused by the local
implementation from actual credit risk impacts. The second part continues with
a quantification of expected credit losses based on Impact of Risk(c) instead
of traditional cost of risk measures. An objective framework is suggested which
allows for improved testing of forward looking credit risk estimates during
credit cycles. This framework will prove useful to mitigate overly pro-cyclical
provisioning and to reduce earnings volatility. Finally, an LGD monitoring and
backtesting approach, applicable under regulatory requirements and accounting
standards as well, is proposed. On basis of the NPL Dashboard, part of the
Impact of Risk(c) framework, specific key risk indicators are introduced that
allow for a detailed assessment of collections performance versus LGD in in NPL
portfolio (bucket 3).
Individuality and universality in the growth-division laws of single E. coli cells
Date: 2015-12-26 00:00:00

The mean size of exponentially dividing E. coli cells cultured in different
nutrient conditions is known to depend on the mean growth rate only. However,
the joint fluctuations relating cell size, doubling time and individual growth
rate are only starting to be characterized. Recent studies in bacteria (i)
revealed the near constancy of the size extension in a single cell cycle (adder
mechanism), and (ii) reported a universal trend where the spread in both size
and doubling times is a linear function of the population means of these
variables. Here, we combine experiments and theory and use scaling concepts to
elucidate the constraints posed by the second observation on the division
control mechanism and on the joint fluctuations of sizes and doubling times. We
found that scaling relations based on the means both collapse size and
doubling-time distributions across different conditions, and explain how the
shape of their joint fluctuations deviates from the means. Our data on these
joint fluctuations highlight the importance of cell individuality: single cells
do not follow the dependence observed for the means between size and either
growth rate or inverse doubling time. Our calculations show that these results
emerge from a broad class of division control mechanisms (including the adder
mechanism as a particular case) requiring a certain scaling form of the
so-called "division hazard rate function", which defines the probability rate
of dividing as a function of measurable parameters. This gives a rationale for
the universal body-size distributions observed in microbial ecosystems across
many microbial species, presumably dividing with multiple mechanisms.
Additionally, our experiments show a crossover between fast and slow growth in
the relation between individual-cell growth rate and division time, which can
be understood in terms of different regimes of genome replication control.
The Intrinsic Bounds on the Risk Premium of Markovian Pricing Kernels
Date: 2015-09-28 00:00:00

The risk premium is one of main concepts in mathematical finance. It is a
measure of the trade-offs investors make between return and risk and is defined
by the excess return relative to the risk-free interest rate that is earned
from an asset per one unit of risk. The purpose of this article is to determine
upper and lower bounds on the risk premium of an asset based on the market
prices of options. One of the key assumptions to achieve this goal is that the
market is Markovian. Under this assumption, we can transform the problem of
finding the bounds into a second-order differential equation. We then obtain
upper and lower bounds on the risk premium by analyzing the differential
equation.
A Coupled Stochastic Model Explains Differences in Circadian Behavior of Cry1 and Cry2 Knockouts
Date: 2015-02-22 00:00:00

In the mammalian suprachiasmatic nucleus (SCN), a population of noisy
cell-autonomous oscillators synchronizes to generate robust circadian rhythms
at the organism-level. Within these cells two isoforms of Cryptochrome, Cry1
and Cry2, participate in a negative feedback loop driving circadian
rhythmicity. Previous work has shown that single, dissociated SCN neurons
respond differently to Cry1 and Cry2 knockouts: Cry1 knockouts are arrhythmic
while Cry2 knockouts display more regular rhythms. These differences have led
to speculation that CRY1 and CRY2 may play different functional roles in the
oscillator. To address this proposition, we have developed a new coupled,
stochastic model focused on the Period (Per) and Cry feedback loop, and
incorporating intercellular coupling via vasoactive intestinal peptide (VIP).
Due to the stochastic nature of molecular oscillations, we demonstrate that
single-cell Cry1 knockout oscillations display partially rhythmic behavior, and
cannot be classified as simply rhythmic or arrhythmic. Our model demonstrates
that intrinsic molecular noise and differences in relative abundance, rather
than differing functions, are sufficient to explain the range of rhythmicity
encountered in Cry knockouts in the SCN. Our results further highlight the
essential role of stochastic behavior in understanding and accurately modeling
the circadian network and its response to perturbation.
Deep Brain Stimulation for Parkinson's Disease: a survey of experiences perceived by recipients and carers
Date: 2015-08-10 00:00:00

Perceived outcomes from DBS for PD were sampled for 52 cases by surveying 46
DBS recipients and 45 carers. Post-DBS experience ranged from 10-129 months.
There were significant variations in perceived outcomes over time. In some
cases extreme variations were experienced as a consequence of hardware and
other problems requiring additional surgery. Nevertheless most in this group
went on to ultimately report good outcomes. Holistic assessments of experiences
were largely positive, but in some cases there were significant differences in
the assessments by recipients and carers. For assessments valid at the time of
interview 26 recipients and 17 carers commented that the outcome was good. A
second group of 11 recipients and 12 carers reported mixed results but overall
a positive experience. A third group of 6 recipients and 8 carers reported
negatively about the outcomes. Many considered overall quality of life much
better following DBS, more so recipients than carers. Post-DBS experiences of
both motor and non-motor symptoms varied greatly between cases. When
considering the average of participant responses, tremor and dyskinesias were
considered better or much better following DBS, with benefits sustained with
time. 12 months after DBS many symptoms were on average considered the same or
better after DBS, but for many, some decline in benefits was apparent over this
period. Some symptoms were reported to show no improvement, or be worse
following DBS. 12 months after the procedure the average of participant
responses indicated that symptoms including speech, postural stability,
swallowing, handwriting, cognitive function and incontinence were worse.
Dynamic Defaultable Term Structure Modelling beyond the Intensity Paradigm
Date: 2015-07-12 00:00:00

The two main approaches in credit risk are the structural approach pioneered
in Merton (1974) and the reduced-form framework proposed in Jarrow & Turnbull
(1995) and in Artzner & Delbaen (1995). The goal of this article is to provide
a unified view on both approaches. This is achieved by studying reduced-form
approaches under weak assumptions. In particular we do not assume the global
existence of a default intensity and allow default at fixed or predictable
times with positive probability, such as coupon payment dates.
  In this generalized framework we study dynamic term structures prone to
default risk following the forward-rate approach proposed in
Heath-Jarrow-Morton (1992). It turns out, that previously considered models
lead to arbitrage possibilities when default may happen at a predictable time
with positive probability. A suitable generalization of the forward-rate
approach contains an additional stochastic integral with atoms at predictable
times and necessary and sufficient conditions for a suitable no-arbitrage
condition (NAFL) are given. In the view of efficient implementations we develop
a new class of affine models which do not satisfy the standard assumption of
stochastic continuity.
  The chosen approach is intimately related to the theory of enlargement of
filtrations, to which we provide a small example by means of filtering theory
where the Azema supermartingale contains upward and downward jumps, both at
predictable and totally inaccessible stopping times.
Optimal Mean Reversion Trading with Transaction Costs and Stop-Loss Exit
Date: 2015-05-14 00:00:00

Motivated by the industry practice of pairs trading, we study the optimal
timing strategies for trading a mean-reverting price spread. An optimal double
stopping problem is formulated to analyze the timing to start and subsequently
liquidate the position subject to transaction costs. Modeling the price spread
by an Ornstein-Uhlenbeck process, we apply a probabilistic methodology and
rigorously derive the optimal price intervals for market entry and exit. As an
extension, we incorporate a stop-loss constraint to limit the maximum loss. We
show that the entry region is characterized by a bounded price interval that
lies strictly above the stop-loss level. As for the exit timing, a higher
stop-loss level always implies a lower optimal take-profit level. Both
analytical and numerical results are provided to illustrate the dependence of
timing strategies on model parameters such as transaction cost and stop-loss
level.
Identification and Estimation of Multidimensional Screening
Authors: Gaurab Aryal, Federico Zincenko
Date: 2014-11-23 00:00:00
Tasks: Attribute

We study the identification and estimation of a multidimensional screening model, where a monopolist sells a multi-attribute product to consumers with private information about their multidimensional preferences. Under optimal screening, the seller designs product and payment rules that exclude "low-type" consumers, bunches the "medium types" at "medium-quality" products, and perfectly screens the "high types." We determine sufficient conditions to identify the joint distribution of preferences and the marginal costs from data on optimal individual choices and payments. Then, we propose estimators for these objects, establish their asymptotic properties, and assess their small-sample performance using Monte Carlo experiments.
The Complexity of Genetic Diversity
Date: 2015-10-22 00:00:00
Tasks: Diversity

A key question in biological systems is whether genetic diversity persists in
the long run under evolutionary competition or whether a single dominant
genotype emerges. Classic work by Kalmus in 1945 has established that even in
simple diploid species (species with two chromosomes) diversity can be
guaranteed as long as the heterozygote individuals enjoy a selective advantage.
Despite the classic nature of the problem, as we move towards increasingly
polymorphic traits (e.g. human blood types) predicting diversity and
understanding its implications is still not fully understood. Our key
contribution is to establish complexity theoretic hardness results implying
that even in the textbook case of single locus diploid models predicting
whether diversity survives or not given its fitness landscape is
algorithmically intractable. We complement our results by establishing that
under randomly chosen fitness landscapes diversity survives with significant
probability. Our results are structurally robust along several dimensions
(e.g., choice of parameter distribution, different definitions of
stability/persistence, restriction to typical subclasses of fitness
landscapes). Technically, our results exploit connections between game theory,
nonlinear dynamical systems, complexity theory and biology and establish
hardness results for predicting the evolution of a deterministic variant of the
well known multiplicative weights update algorithm in symmetric coordination
games which could be of independent interest.
On Trading American Put Options with Interactive Volatility
Date: 2017-03-27 00:00:00

We introduce a simple stochastic volatility model, whose novelty consists in
taking into account hitting times of the asset price, and study the optimal
stopping problem corresponding to a put option whose time horizon (after the
asset price hits a certain level) is exponentially distributed. We obtain
explicit optimal stopping rules in various cases one of which is interestingly
complex because of an unexpected disconnected continuation region. Finally, we
discuss in detail how these stopping rules could be used for trading an
American put when the trader expects a market drop in the near future.
Single cell visualization of transcription kinetics variance of highly mobile identical genes using 3D nanoimaging
Date: 2015-03-19 00:00:00

Both multi-cell biochemical assays and single cell fluorescence measurements
have revealed that the elongation rate of Polymerase II (PolII) in eukaryotes
varies largely across different cell types and genes. However, there is not yet
a consensus whether intrinsic factors such as the position, local mobility or
the engagement by an active molecular mechanism of a genetic locus could be the
determinants of the observed heterogeneity. Employing high-speed 3D
fluorescence nanoimaging we resolve here at the single cell level multiple,
distinct regions of mRNA synthesis within a labeled transgene array. By
employing phasor analysis, a fluorescence fluctuation spectroscopy technique,
we demonstrate that these regions are active transcription sites that release
mRNA molecules in the nucleoplasm, and we extract the local PolII elongation
rate. While we detect a range of 10-100 bp/s for PolII elongation from cell to
cell, we are now also able to measure up to a four-fold variation in the
average elongation between identical copies of the same gene measured
simultaneously within the same cell. Furthermore, we are able to visualize
changes of PolII elongation as a function of time. We observe a correlation
between the average elongation rate measured in a locus and its local mobility.
Finally, by cross-correlating the transcriptional activity with the nm-sized
movements of the active loci, we provide evidence of an active molecular
mechanism determining displacements of the transcription sites concomitant to
increases in transcriptional activity. Together these observations demonstrate
that local factors, such as chromatin local mobility and the microenvironment
of the transcription site, are an important source of transcription kinetics
variability.
Bounds on the Expected Size of the Maximum Agreement Subtree
Date: 2015-08-31 00:00:00

We prove polynomial upper and lower bounds on the expected size of the
maximum agreement subtree of two random binary phylogenetic trees under both
the uniform distribution and Yule-Harding distribution. This positively answers
a question posed in earlier work. Determining tight upper and lower bounds
remains an open problem.
The Western Africa Ebola virus disease epidemic exhibits both global exponential and local polynomial growth rates
Date: 2015-01-27 00:00:00
Tasks: Time Series Analysis

Background: While many infectious disease epidemics are initially
characterized by an exponential growth in time, we show that district-level
Ebola virus disease (EVD) outbreaks in West Africa follow slower
polynomial-based growth kinetics over several generations of the disease.
Methods: We analyzed epidemic growth patterns at three different spatial scales
(regional, national, and subnational) of the Ebola virus disease epidemic in
Guinea, Sierra Leone and Liberia by compiling publicly available weekly time
series of reported EVD case numbers from the patient database available from
the World Health Organization website for the period 05-Jan to 17-Dec 2014.
Results: We found significant differences in the growth patterns of EVD cases
at the scale of the country, district, and other subnational administrative
divisions. The national cumulative curves of EVD cases in Guinea, Sierra Leone,
and Liberia show periods of approximate exponential growth. In contrast, local
epidemics are asynchronous and exhibit slow growth patterns during 3 or more
EVD generations, which can be better approximated by a polynomial than an
exponential. Conclusions: The slower than expected growth pattern of local EVD
outbreaks could result from a variety of factors, including behavior changes,
success of control interventions, or intrinsic features of the disease such as
a high level of clustering. Quantifying the contribution of each of these
factors could help refine estimates of final epidemic size and the relative
impact of different mitigation efforts in current and future EVD outbreaks.
Hydrodynamic limit of order book dynamics
Date: 2016-02-24 00:00:00

In this paper, we establish a fluid limit for a two--sided Markov order book
model. Our main result states that in a certain asymptotic regime, a pair of
measure-valued processes representing the "sell-side shape" and "buy-side
shape" of an order book converges to a pair of deterministic measure-valued
processes in a certain sense. We also test our fluid approximation on data. The
empirical results suggest that the approximation is reasonably good for
liquidly--traded stocks in certain time periods.
A statistical model for in vivo neuronal dynamics
Date: 2015-10-23 00:00:00
Tasks: model

Single neuron models have a long tradition in computational neuroscience.
Detailed biophysical models such as the Hodgkin-Huxley model as well as
simplified neuron models such as the class of integrate-and-fire models relate
the input current to the membrane potential of the neuron. Those types of
models have been extensively fitted to in vitro data where the input current is
controlled. Those models are however of little use when it comes to
characterize intracellular in vivo recordings since the input to the neuron is
not known. Here we propose a novel single neuron model that characterizes the
statistical properties of in vivo recordings. More specifically, we propose a
stochastic process where the subthreshold membrane potential follows a Gaussian
process and the spike emission intensity depends nonlinearly on the membrane
potential as well as the spiking history. We first show that the model has a
rich dynamical repertoire since it can capture arbitrary subthreshold
autocovariance functions, firing-rate adaptations as well as arbitrary shapes
of the action potential. We then show that this model can be efficiently fitted
to data without overfitting. Finally, we show that this model can be used to
characterize and therefore precisely compare various intracellular in vivo
recordings from different animals and experimental conditions.
Maximum sustainable yield from interacting fish stocks in an uncertain world: two policy choices and underlying trade-offs
Date: 2016-05-31 00:00:00
Tasks: Management

The case of fisheries management illustrates how the inherent structural
instability of ecosystems can have deep-running policy implications. We
contrast ten types of management plans to achieve maximum sustainable yields
(MSY) from multiple stocks and compare their effectiveness based on a
management strategy evaluation (MSE) that uses complex food webs in its
operating model. Plans that target specific stock sizes ($B_{\text{MSY}}$)
consistently led to higher yields than plans targeting specific fishing
pressures ($F_{\text{MSY}}$). A new self-optimising control rule, introduced
here for its robustness to structural instability, led to intermediate yields.
Most plans outperformed single-species management plans with pressure targets
set without considering multispecies interactions. However, more refined plans
to "maximise the yield from each stock separately", in the sense of a Nash
equilibrium, produced total yields comparable to plans aiming to maximise total
harvested biomass, and were more robust to structural instability. Our analyses
highlight trade-offs between yields, amenability to negotiations, pressures on
biodiversity, and continuity with current approaches in the European context.
Based on these results, we recommend directions for developments of EU
fisheries policy.
Hierarchical Network Structure Promotes Dynamical Robustness
Date: 2015-06-16 00:00:00

The relationship between network topology and system dynamics has significant
implications for unifying our understanding of the interplay among metabolic,
gene-regulatory, and ecosystem network architecures. Here we analyze the
stability and robustness of a large class of dynamics on such networks. We
determine the probability distribution of robustness as a function of network
topology and show that robustness is classified by the number of links between
modules of the network. We also demonstrate that permutation of these modules
is a fundamental symmetry of dynamical robustness. Analysis of these findings
leads to the conclusion that the most robust systems have the most hierarchical
structure. This relationship provides a means by which evolutionary selection
for a purely dynamical phenomenon may shape network architectures across scales
of the biological hierarchy.
Stochasticity enhances the gaining of bet-hedging strategies in contact-process-like dynamics
Date: 2015-03-10 00:00:00

In biology and ecology, individuals or communities of individuals living in
unpredictable environments often alternate between different evolutionary
strategies to spread and reduce risks. Such behavior is commonly referred to as
"bet-hedging." Long-term survival probabilities and population sizes can be
much enhanced by exploiting such hybrid strategies. Here, we study the simplest
possible birth-death stochastic model in which individuals can choose among a
poor but safe strategy, a better but risky alternative, or a combination of
both. We show analytically and computationally that the benefits derived from
bet-hedging strategies are much stronger for higher environmental variabilities
(large external noise) and/or for small spatial dimensions (large intrinsic
noise). These circumstances are typically encountered by living systems, thus
providing us with a possible justification for the ubiquitousness of
bet-hedging in nature.