pwc-archive/papers-with-abstracts huggingface dataset:
Detecting patterns of species diversification in the presence of both rate shifts and mass extinctions
Date: 2015-08-31 00:00:00
Tasks: Diversity, Open-Ended Question Answering

Recent methodological advances are enabling better examination of speciation
and extinction processes and patterns. A major open question is the origin of
large discrepancies in species number between groups of the same age. Existing
frameworks to model this diversity either focus on changes between lineages,
neglecting global effects such as mass extinctions, or focus on changes over
time which would affect all lineages. Yet it seems probable that both lineages
differences and mass extinctions affect the same groups. Here we used
simulations to test the performance of two widely used methods, under complex
scenarios. We report good performances, although with a tendency to
over-predict events when increasing the complexity of the scenario. Overall, we
find that lineage shifts are better detected than mass extinctions. This work
has significance for assessing the methods currently used for estimating
changes in diversification using phylogenies and developing new tests.
The puzzle of sub-maximal resource use by a parasitoid wasp
Date: 2015-03-20 00:00:00

When there is conspicuous under-exploitation of a limited resource, it is
worth asking what mechanisms allow presumably valuable resources to be left
unused? Evolutionary biologists have generated a wide range of hypotheses to
explain this, ranging from interdemic group selection to selfishly prudent
individual restraint. We consider a situation in which, in spite of high
intraspecific competition, individuals leave most of a key resource
unexploited. The parasitic wasp that does this finds virtually all host egg
clusters in a landscape, but parasitizes only about a third of the eggs in
each, and then leaves a deterrent mark around the cluster. We first test, and
reject, a series of system-specific simple constraints that might limit full
host exploitation, such as asynchronous maturation of host eggs. We then
consider classical hypotheses for the evolution of restraint. Prudent predation
and bet-hedging fail as explanations because the wasp lives as a large
well-mixed population. Also, we find no individual benefits to the parasitoid
of developing in a sparsely parasitized host nest. However an optimal foraging
model, including empirically measured costs of superparasitism and
hyperparasitism, can explain through individual selection, both the
consistently low rate of parasitism and marking.
A modular approach to adaptive structures
Date: 2015-07-17 00:00:00

A remarkable property of nastic, shape changing plants is their complete
fusion between actuators and structure. This is achieved by combining a large
number of cells whose geometry, internal pressures and material properties are
optimized for a given set of target shapes and stiffness requirements. An
advantage of such a fusion is that cell walls are prestressed by cell pressures
which increases, decreases the overall structural stiffness, weight. Inspired
by the nastic movement of plants, Pagitz et al. 2012 Bioinspir. Biomim. 7
published a novel concept for pressure actuated cellular structures. This
article extends previous work by introducing a modular approach to adaptive
structures. An algorithm that breaks down any continuous target shapes into a
small number of standardized modules is presented. Furthermore it is shown how
cytoskeletons within each cell enhance the properties of adaptive modules. An
adaptive passenger seat and an aircrafts leading, trailing edge is used to
demonstrate the potential of a modular approach.
Leveraged {ETF} implied volatilities from {ETF} dynamics
Date: 2015-04-15 00:00:00
Tasks: Form

The growth of the exhange-traded fund (ETF) industry has given rise to the
trading of options written on ETFs and their leveraged counterparts {(LETFs)}.
We study the relationship between the ETF and LETF implied volatility surfaces
when the underlying ETF is modeled by a general class of local-stochastic
volatility models. A closed-form approximation for prices is derived for
European-style options whose payoff depends on the terminal value of the ETF
and/or LETF. Rigorous error bounds for this pricing approximation are
established. A closed-form approximation for implied volatilities is also
derived. We also discuss a scaling procedure for comparing implied volatilities
across leverage ratios. The implied volatility expansions and scalings are
tested in three well-known settings: CEV, Heston and SABR.
Identification of redundant and synergetic circuits in triplets of electrophysiological data
Date: 2015-09-10 00:00:00

Neural systems are comprised of interacting units, and relevant information
regarding their function or malfunction can be inferred by analyzing the
statistical dependencies between the activity of each unit. Whilst correlations
and mutual information are commonly used to characterize these dependencies,
our objective here is to extend interactions to triplets of variables to better
detect and characterize dynamic information transfer. Our approach relies on
the measure of interaction information (II). The sign of II provides
information as to the extent to which the interaction of variables in triplets
is redundant (R) or synergetic (S). Here, based on this approach, we calculated
the R and S status for triplets of electrophysiological data recorded from
drug-resistant patients with mesial temporal lobe epilepsy in order to study
the spatial organization and dynamics of R and S close to the epileptogenic
zone (the area responsible for seizure propagation). In terms of spatial
organization, our results show that R matched the epileptogenic zone while S
was distributed more in the surrounding area. In relation to dynamics, R made
the largest contribution to high frequency bands (14-100Hz), whilst S was
expressed more strongly at lower frequencies (1-7Hz). Thus, applying
interaction information to such clinical data reveals new aspects of
epileptogenic structure in terms of the nature (redundancy vs. synergy) and
dynamics (fast vs. slow rhythms) of the interactions. We expect this
methodology, robust and simple, can reveal new aspects beyond pair-interactions
in networks of interacting units in other setups with multi-recording data sets
(and thus, not necessarily in epilepsy, the pathology we have approached here).
Facilitation and Internalization Optimal Strategy in a Multilateral Trading Context
Date: 2015-01-10 00:00:00

This paper studies four trading algorithms of a professional trader at a
multilateral trading facility, observing a realistic two-sided limit order book
whose dynamics are driven by the order book events. The identity of the trader
can be either internalizing or regular, either a hedge fund or a brokery
agency. The speed and cost of trading can be balanced by properly choosing
active strategies on the displayed orders in the book and passive strategies on
the hidden orders within the spread. We shall show that the price switching
algorithms provide lower and upper bounds of the mixed trading algorithms.
Especially, when the internalization premium is zero, an internalizing trader's
optimal mixed trading strategy can be achieved among the set of price switching
strategies. For both an internalizing trader and a regular trader, the optimal
price switching strategy exists and is expressed in terms of the value
function. A parallelizable algorithm to numerically compute the value function
and optimal price switching strategy for the discretized state process is
provided.
The least squares method for option pricing revisited
Date: 2015-11-16 00:00:00
Tasks: regression

It is shown that the the popular least squares method of option pricing
converges even under very general assumptions. This substantially increases the
freedom of creating different implementations of the method, with varying
levels of computational complexity and flexible approach to regression. It is
also argued that in many practical applications even modest non-linear
extensions of standard regression may produce satisfactory results. This claim
is illustrated with examples.
Drawdown: From Practice to Theory and Back Again
Date: 2016-09-21 00:00:00
Tasks: Management

Maximum drawdown, the largest cumulative loss from peak to trough, is one of
the most widely used indicators of risk in the fund management industry, but
one of the least developed in the context of measures of risk. We formalize
drawdown risk as Conditional Expected Drawdown (CED), which is the tail mean of
maximum drawdown distributions. We show that CED is a degree one positive
homogenous risk measure, so that it can be linearly attributed to factors; and
convex, so that it can be used in quantitative optimization. We empirically
explore the differences in risk attributions based on CED, Expected Shortfall
(ES) and volatility. An important feature of CED is its sensitivity to serial
correlation. In an empirical study that fits AR(1) models to US Equity and US
Bonds, we find substantially higher correlation between the autoregressive
parameter and CED than with ES or with volatility.
Hierarchical clustering of DNA k-mer counts in RNA-seq fastq files reveals batch effects
Date: 2017-07-21 00:00:00
Tasks: Clustering, Diagnostic, Experimental Design

Batch effects, artificial sources of variation due to experimental design,
are a widespread phenomenon in high throughput data. Therefore, mechanisms for
detection of batch effects are needed requiring comparison of multiple samples.
We apply hierarchical clustering (HC) on DNA k-mer counts of multiple RNA-seq
derived Fastq files. Ideally, HC generated trees reflect experimental treatment
groups and thus may indicate experimental effects, but clustering of
preparation groups indicates the presence of batch effects. In order to provide
a simple applicable tool we implemented sequential analysis of Fastq reads with
low memory usage in an R package (seqTools) available on Bioconductor. DNA
k-mer counts were analysed on 61 Fastq files containing RNA-seq data from two
cell types (dermal fibroblasts and Jurkat cells) sequenced on 8 different
Illumina Flowcells. Results: Pairwise comparison of all Flowcells with
hierarchical clustering revealed strong Flowcell based tree separation in 6 (21
%) and detectable Flowcell based clustering in 17 (60.7 %) of 28 Flowcell
comparisons. In our samples, batch effects were also present in reads mapped to
the human genome. Filtering reads for high quality (Phred >30) did not remove
the batch effects. Conclusions: Hierarchical clustering of DNA k-mer counts
provides a quality criterion and an unspecific diagnostic tool for RNA-seq
experiments.
MVA: Initial Margin Valuation Adjustment by Replication and Regression
Date: 2015-01-12 00:00:00
Tasks: regression

Initial margin requirements are becoming an increasingly common feature of
derivative markets. However, while the valuation of derivatives under
collateralisation (Piterbarg 2010, Piterbarg2012), under counterparty risk with
unsecured funding costs (FVA) (Burgard2011, Burgard2011, Burgard2013) and in
the presence of regulatory capital (KVA) (Green2014) are established through
valuation adjustments, hitherto initial margin has not been considered. This
paper further extends the semi-replication framework of (Burgard2013a), itself
later extended by (Green2014), to cover the cost of initial margin, leading to
Margin Valuation Adjustment (MVA). Initial margin requirements are typically
generated through the use of VAR or CVAR models. Given the form of MVA as an
integral over the expected initial margin profile this would lead to excessive
computational costs if a brute force calculation were to be used. Hence we also
propose a computationally efficient approach to the calculation of MVA through
the use of regression techniques, Longstaff-Schwartz Augmented Compression
(LSAC).
Default Probability Estimation via Pair Copula Constructions
Date: 2015-08-21 00:00:00

In this paper we present a novel approach for firm default probability
estimation. The methodology is based on multivariate contingent claim analysis
and pair copula constructions. For each considered firm, balance sheet data are
used to assess the asset value, and to compute its default probability. The
asset pricing function is expressed via a pair copula construction, and it is
approximated via Monte Carlo simulations. The methodology is illustrated
through an application to the analysis of both operative and defaulted firms.
Simultaneous Trading in 'Lit' and Dark Pools
Date: 2016-01-12 00:00:00

We consider an optimal trading problem over a finite period of time during
which an investor has access to both a standard exchange and a dark pool. We
take the exchange to be an order-driven market and propose a continuous-time
setup for the best bid price and the market spread, both modelled by L\'evy
processes. Effects on the best bid price arising from the arrival of limit buy
orders at more favourable prices, the incoming market sell orders potentially
walking the book, and deriving from the cancellations of limit sell orders at
the best ask price are incorporated in the proposed price dynamics. A permanent
impact that occurs when 'lit' pool trades cannot be avoided is built in, and an
instantaneous impact that models the slippage, to which all 'lit' exchange
trades are subject, is also considered. We assume that the trading price in the
dark pool is the mid-price and that no fees are due for posting orders. We
allow for partial trade executions in the dark pool, and we find the optimal
trading strategy in both venues. Since the mid-price is taken from the
exchange, the dynamics of the limit order book also affects the optimal
allocation of shares in the dark pool. We propose a general objective function
and we show that, subject to suitable technical conditions, the value function
can be characterised by the unique continuous viscosity solution to the
associated partial integro differential equation. We present two explicit
examples of the price and the spread models, and derive the associated optimal
trading strategy numerically. We discuss the various degrees of the agent's
risk aversion and further show that roundtrips, i.e. posting the remaining
inventory in the dark pool at every point in time, are not necessarily
beneficial.
Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage
Date: 2015-04-24 00:00:00
Tasks: Diversity

In this paper we propose a method and discuss its computational
implementation as an integrated tool for the analysis of viral genetic
diversity on data generated by high-throughput sequencing. Most methods for
viral diversity estimation proposed so far are intended to take benefit of the
longer reads produced by some NGS platforms in order to estimate a population
of haplotypes. Our goal here is to take advantage of distinct virtues of a
certain kind of NGS platform - the platform SOLiD (Life Technologies) is an
example - that has not received much attention due to the short length of its
reads, which renders haplotype estimation very difficult. However, this kind of
platform has a very low error rate and extremely deep coverage per site and our
method is designed to take advantage of these characteristics. We propose to
measure the populational genetic diversity through a family of multinomial
probability distributions indexed by the sites of the virus genome, each one
representing the populational distribution of the diversity per site. The
implementation of the method focuses on two main optimization strategies: a
read mapping/alignment procedure that aims at the recovery of the maximum
possible number of short-reads; the estimation of the multinomial parameters
through a Bayesian approach, which, unlike simple frequency counting, allows
one to take into account the prior information of the control population within
the inference of a posterior experimental condition and provides a natural way
to separate signal from noise, since it automatically furnishes Bayesian
confidence intervals. The methods described in this paper have been implemented
as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral
Populations).
Combinatorics of Linked Systems of Quartet Trees
Date: 2015-03-16 00:00:00

We apply classical quartet techniques to the problem of phylogenetic
decisiveness and find a value $k$ such that all collections of at least $k$
quartets are decisive. Moreover, we prove that this bound is optimal and give a
lower-bound on the probability that a collection of quartets is decisive.
Nonspecific transcription factor binding reduces variability in transcription factor and target protein expression
Date: 2015-04-14 00:00:00

Transcription factors (TFs) interact with a multitude of binding sites on DNA
and partner proteins inside cells. We investigate how nonspecific
binding/unbinding to such decoy binding sites affects the magnitude and
time-scale of random fluctuations in TF copy numbers arising from stochastic
gene expression. A stochastic model of TF gene expression, together with decoy
site interactions is formulated. Distributions for the total (bound and
unbound) and free (unbound) TF levels are derived by analytically solving the
chemical master equation under physiologically relevant assumptions. Our
results show that increasing the number of decoy binding sides considerably
reduces stochasticity in free TF copy numbers. The TF autocorrelation function
reveals that decoy sites can either enhance or shorten the time-scale of TF
fluctuations depending on model parameters. To understand how noise in TF
abundances propagates downstream, a TF target gene is included in the model.
Intriguingly, we find that noise in the expression of the target gene decreases
with increasing decoy sites for linear TF-target protein dose-responses, even
in regimes where decoy sites enhance TF autocorrelation times. Moreover,
counterintuitive noise transmissions arise for nonlinear dose-responses. In
summary, our study highlights the critical role of molecular sequestration by
decoy binding sites in regulating the stochastic dynamics of TFs and target
proteins at the single-cell level.
Quantum Brownian motion model for the stock market
Date: 2015-11-18 00:00:00
Tasks: model

It is believed by the majority today that the efficient market hypothesis is
imperfect because of market irrationality. Using the physical concepts and
mathematical structures of quantum mechanics, we construct an econophysics
framework for the stock market, based on which we analogously map massive
numbers of single stocks into a reservoir consisting of many quantum harmonic
oscillators and their stock index into a typical quantum open system--a quantum
Brownian particle. In particular, the irrationality of stock transactions is
quantitatively considered as the Planck constant within Heisenberg's
uncertainty relationship of quantum mechanics in an analogous manner. We
analyze real stock data of Shanghai Stock Exchange of China and investigate
fat-tail phenomena and non-Markovian behaviors of the stock index with the
assistance of the quantum Brownian motion model, thereby interpreting and
studying the limitations of the classical Brownian motion model for the
efficient market hypothesis from a new perspective of quantum open system
dynamics.
An explicit Euler scheme with strong rate of convergence for financial SDEs with non-Lipschitz coefficients
Date: 2016-04-10 00:00:00

We consider the approximation of stochastic differential equations (SDEs)
with non-Lipschitz drift or diffusion coefficients. We present a modified
explicit Euler-Maruyama discretisation scheme that allows us to prove strong
convergence, with a rate. Under some regularity and integrability conditions,
we obtain the optimal strong error rate. We apply this scheme to SDEs widely
used in the mathematical finance literature, including the
Cox-Ingersoll-Ross~(CIR), the 3/2 and the Ait-Sahalia models, as well as a
family of mean-reverting processes with locally smooth coefficients. We
numerically illustrate the strong convergence of the scheme and demonstrate its
efficiency in a multilevel Monte Carlo setting.
Local martingale deflators for asset processes stopped at a default time $S^\tau$ or right before $S^{\tau-}$
Date: 2016-07-20 00:00:00

Let $\mathbb{F}\subset \mathbb{G}$ be two filtrations and $S$ be a
$\mathbb{F}$ semimartingale possessing a $\mathbb{F}$ local martingale
deflator. Consider $\tau$ a $\mathbb{G}$ stopping time. We study the problem
whether $S^{\tau-}$ or $S^{\tau}$ can have $\mathbb{G}$ local martingale
deflators. A suitable theoretical framework is set up in this paper, within
which necessary/sufficient conditions for the problem to be solved have been
proved. Under these conditions, we will construct $\mathbb{G}$ local martingale
deflators for $S^{\tau-}$ or for $S^{\tau}$. Among others, it is proved that
$\mathbb{G}$ local martingale deflators are multiples of $\mathbb{F}$ local
martingale deflators, with a multiplicator coming from the multiplicative
decomposition of the Az\'ema supermartingale of $\tau$. The proofs of the
necessary/sufficient conditions require various results to be established about
Az\'ema supermartingale, about local martingale deflator, about filtration
enlargement, which are interesting in themselves.
  Our study is based on a filtration enlargement setting. For applications, it
is important to have a method to infer the existence of such setting from the
knowledge of the market information. This question is discussed at the end of
the paper.
Combining Alpha Streams with Costs
Date: 2015-01-16 00:00:00

We discuss investment allocation to multiple alpha streams traded on the same
execution platform with internal crossing of trades and point out differences
with allocating investment when alpha streams are traded on separate execution
platforms with no crossing. First, in the latter case allocation weights are
non-negative, while in the former case they can be negative. Second, the
effects of both linear and nonlinear (impact) costs are different in these two
cases due to turnover reduction when the trades are crossed. Third, the
turnover reduction depends on the universe of traded alpha streams, so if some
alpha streams have zero allocations, turnover reduction needs to be recomputed,
hence an iterative procedure. We discuss an algorithm for finding allocation
weights with crossing and linear costs. We also discuss a simple approximation
when nonlinear costs are added, making the allocation problem tractable while
still capturing nonlinear portfolio capacity bound effects. We also define
"regression with costs" as a limit of optimization with costs, useful in
often-occurring cases with singular alpha covariance matrix.
Set-valued shortfall and divergence risk measures
Date: 2017-09-10 00:00:00

Risk measures for multivariate financial positions are studied in a
utility-based framework. Under a certain incomplete preference relation,
shortfall and divergence risk measures are defined as the optimal values of
specific set minimization problems. The dual relationship between these two
classes of multivariate risk measures is constructed via a recent Lagrange
duality for set optimization. In particular, it is shown that a shortfall risk
measure can be written as an intersection over a family of divergence risk
measures indexed by a scalarization parameter. Examples include set-valued
versions of the entropic risk measure and the average value at risk. As a
second step, the minimization of these risk measures subject to trading
opportunities is studied in a general convex market in discrete time. The
optimal value of the minimization problem, called the market risk measure, is
also a set-valued risk measure. A dual representation for the market risk
measure that decomposes the effects of the original risk measure and the
frictions of the market is proved.