pwc-archive/papers-with-abstracts huggingface dataset:
Trophic groups and modules: two levels of group detection in food webs
Date: 2015-04-13 00:00:00

Within food webs, species can be partitioned into groups according to various
criteria. Two notions have received particular attention: trophic groups, which
have been used for decades in the ecological literature, and more recently,
modules. The relationship between these two group definitions remains unknown
in empirical food webs because they have so far been studied separately. While
recent developments in network theory have led to efficient methods for
detecting modules in food webs, the determination of trophic groups (sets of
species that are functionally similar) is based on subjective expert knowledge.
Here, we develop a novel algorithm for trophic group detection. We apply this
method to several well-resolved empirical food webs, and show that aggregation
into trophic groups allows the simplification of food webs while preserving
their information content. Furthermore, we reveal a 2-level hierarchical
structure where modules partition food webs into large bottom-top trophic
pathways whereas trophic groups further partition these pathways into sets of
species with similar trophic connections. Bringing together trophic groups and
modules provides new perspectives to the study of dynamical and functional
consequences of food-web structure, bridging topological analysis and dynamical
systems. Trophic groups have a clear ecological meaning in terms of trophic
similarity, and are found to provide a trade-off between network complexity and
information loss.
Continuous-Time Portfolio Choice Under Monotone Mean-Variance Preferences-Stochastic Factor Case
Authors: Jakub Trybuła, Dariusz Zawisza
Date: 2014-03-13 00:00:00

We consider an incomplete market with a nontradable stochastic factor and a continuous time investment problem with an optimality criterion based on monotone mean-variance preferences. We formulate it as a stochastic differential game problem and use Hamilton-Jacobi-Bellman-Isaacs equations to find an optimal investment strategy and the value function. What is more, we show that our solution is also optimal for the classical Markowitz problem and every optimal solution for the classical Markowitz problem is optimal also for the monotone mean-variance preferences. These results are interesting because the original Markowitz functional is not monotone, and it was observed that in the case of a static one-period optimization problem the solutions for those two functionals are different. In addition, we determine explicit Markowitz strategies in the square root factor models.
Structure conditions under progressively added information
Date: 2018-12-27 00:00:00
Tasks: valid

It has been understood that the "local" existence of the Markowitz' optimal
portfolio or the solution to the local-risk minimization problem is guaranteed
by some specific mathematical structures on the underlying assets price
processes known in the literature as "{\it Structure Conditions}". In this
paper, we consider a semi-martingale market model, and an arbitrary random time
that is not adapted to the information flow of the market model. This random
time may model the default time of a firm, the death time of an insured, or any
the occurrence time of an event that might impact the market model somehow. By
adding additional uncertainty to the market model, via this random time, the
{\it structures conditions} may fail and hence the Markowitz's optimal
portfolio and other quadratic-optimal portfolios might fail to exist. Our aim
is to investigate the impact of this random time on the structures conditions
from different perspectives. Our analysis allows us to conclude that under some
mild assumptions on the market model and the random time, these structures
conditions will remain valid on the one hand. Furthermore, we provide two
examples illustrating the importance of these assumptions. On the other hand,
we describe the random time models for which these structure conditions are
preserved for any market model. These results are elaborated separately for the
two contexts of stopping with the random time and incorporating totally a
specific class of random times respectively.
Continuum Model for Pressure Actuated Cellular Structures
Date: 2017-07-28 00:00:00
Tasks: model

Previous work introduced a lower-dimensional numerical model for the
geometric nonlinear simulation and optimization of compliant pressure actuated
cellular structures. This model takes into account hinge eccentricities as well
as rotational and axial cell side springs. The aim of this article is twofold.
First, previous work is extended by introducing an associated continuum model.
This model is an exact geometric representation of a cellular structure and the
basis for the spring stiffnesses and eccentricities of the numerical model.
Second, the state variables of the continuum and numerical model are linked via
discontinuous stress constraints on the one hand and spring stiffness, hinge
eccentricities on the other hand. An efficient optimization algorithm that
fully couples both sets of variables is presented. The performance of the
proposed approach is demonstrated with the help of an examples.
Multilevel Monte Carlo For Exponential L\'{e}vy Models
Date: 2017-05-30 00:00:00
Tasks: Computational Efficiency

We apply multilevel Monte Carlo for option pricing problems using exponential
L\'{e}vy models with a uniform timestep discretisation to monitor the running
maximum required for lookback and barrier options. The numerical results
demonstrate the computational efficiency of this approach. We derive estimates
of the convergence rate for the error introduced by the discrete monitoring of
the running supremum of a broad class of L\'{e}vy processes. We use these to
obtain upper bounds on the multilevel Monte Carlo variance convergence rate for
the Variance Gamma, NIG and $\alpha$-stable processes used in the numerical
experiments. We also show numerical results and analysis of a trapezoidal
approximation for Asian options.
Theoretical Analysis of Discreteness-Induced Transition in Autocatalytic Reaction Dynamics
Date: 2015-02-24 00:00:00

Transitions in the qualitative behavior of chemical reaction dynamics with a
decrease in molecule number have attracted much attention. Here, a method based
on a Markov process with a tridiagonal transition matrix is applied to the
analysis of this transition in reaction dynamics. The transition to bistability
due to the small-number effect and the mean switching time between the bistable
states are analytically calculated in agreement with numerical simulations. In
addition, a novel transition involving the reversal of the chemical reaction
flow is found in the model under an external flow, and also in a
three-component model. The generality of this transition and its correspondence
to biological phenomena are also discussed.
Maximum drawdown, recovery, and momentum
Authors: Jaehyung Choi
Date: 2014-03-31 00:00:00

We empirically test predictability on asset price by using stock selection rules based on maximum drawdown and its consecutive recovery. In various equity markets, monthly momentum- and weekly contrarian-style portfolios constructed from these alternative selection criteria are superior not only in forecasting directions of asset prices but also in capturing cross-sectional return differentials. In monthly periods, the alternative portfolios ranked by maximum drawdown measures exhibit outperformance over other alternative momentum portfolios including traditional cumulative return-based momentum portfolios. In weekly time scales, recovery-related stock selection rules are the best ranking criteria for detecting mean-reversion. For the alternative portfolios and their ranking baskets, improved risk profiles in various reward-risk measures also imply more consistent prediction on the direction of assets in future. In the Carhart four-factor analysis, higher factor-neutral intercepts for the alternative strategies are another evidence for the robust prediction by the alternative stock selection rules.
Is It Possible to OD on Alpha?
Date: 2018-11-14 00:00:00

It is well known that combining multiple hedge fund alpha streams yields
diversification benefits to the resultant portfolio. Additionally, crossing
trades between different alpha streams reduces transaction costs. As the number
of alpha streams increases, the relative turnover of the portfolio decreases as
more trades are crossed. However, we argue, under reasonable assumptions, that
as the number of alphas increases, the turnover does not decrease indefinitely;
instead, the turnover approaches a non-vanishing limit related to the
correlation structure of the portfolio's alphas. We also point out that, more
generally, computational simplifications can arise when the number of alphas is
large.
Evolutionary game theory using agent-based methods
Date: 2016-08-31 00:00:00

Evolutionary game theory is a successful mathematical framework geared
towards understanding the selective pressures that affect the evolution of the
strategies of agents engaged in interactions with potential conflicts. While a
mathematical treatment of the costs and benefits of decisions can predict the
optimal strategy in simple settings, more realistic settings such as finite
populations, non-vanishing mutations rates, stochastic decisions, communication
between agents, and spatial interactions, require agent-based methods where
each agent is modeled as an individual, carries its own genes that determine
its decisions, and where the evolutionary outcome can only be ascertained by
evolving the population of agents forward in time. While highlighting standard
mathematical results, we compare those to agent-based methods that can go
beyond the limitations of equations and simulate the complexity of
heterogeneous populations and an ever-changing set of interactors. We conclude
that agent-based methods can predict evolutionary outcomes where purely
mathematical treatments cannot tread (for example in the weak selection--strong
mutation limit), but that mathematics is crucial to validate the computational
simulations.
Computational experiments successfully predict the emergence of autocorrelations in ultra-high-frequency stock returns
Date: 2018-02-24 00:00:00

Social and economic systems are complex adaptive systems, in which
heterogenous agents interact and evolve in a self-organized manner, and
macroscopic laws emerge from microscopic properties. To understand the
behaviors of complex systems, computational experiments based on physical and
mathematical models provide a useful tools. Here, we perform computational
experiments using a phenomenological order-driven model called the modified
Mike-Farmer (MMF) to predict the impacts of order flows on the autocorrelations
in ultra-high-frequency returns, quantified by Hurst index $H_r$. Three
possible determinants embedded in the MMF model are investigated, including the
Hurst index $H_s$ of order directions, the Hurst index $H_x$ and the power-law
tail index $\alpha_x$ of the relative prices of placed orders. The
computational experiments predict that $H_r$ is negatively correlated with
$\alpha_x$ and $H_x$ and positively correlated with $H_s$. In addition, the
values of $\alpha_x$ and $H_x$ have negligible impacts on $H_r$, whereas $H_s$
exhibits a dominating impact on $H_r$. The predictions of the MMF model on the
dependence of $H_r$ upon $H_s$ and $H_x$ are verified by the empirical results
obtained from the order flow data of 43 Chinese stocks.
Market Efficiency and Government Interventions in Prewar Japanese Rice Futures Markets
Date: 2017-02-18 00:00:00

This study analyzes how colonial rice trade in prewar Japan affected its rice
market, considering several government interventions in the two rice futures
exchanges in Tokyo and Osaka. We explore the interventions in the futures
markets using two procedures. First, we measure the joint degree of efficiency
in the markets using a time-varying vector autoregression model. Second, we
examine many historical events that possibly affected the markets and focus on
one event at a time. The degree varies over time within our sample period
(1881-1932). The observation, together with historical analysis, leads to the
following conclusions. (1) The two major markets in Tokyo and Osaka were nearly
efficient. (2) Government interventions involving the delivery of imported rice
from Taiwan and Korea often reduced futures market efficiency. Finally, (3)
this relationship continued as long as the quality difference between imported
and domestic rice existed. The government interventions that promoted domestic
distributions of the colonial goods resulted in confusion in the commodity
markets, and decreased efficiency of the markets in the metropole.
Multi-Linear Interactive Matrix Factorization
Authors: Yu Lu, Liu Chuang, Zhang Zi-Ke
Date: 2015-05-18 00:00:00
Tasks: Collaborative Filtering, Recommendation Systems

Recommender systems, which can significantly help users find their interested
items from the information era, has attracted an increasing attention from both
the scientific and application society. One of the widest applied
recommendation methods is the Matrix Factorization (MF). However, most of MF
based approaches focus on the user-item rating matrix, but ignoring the
ingredients which may have significant influence on users' preferences on
items. In this paper, we propose a multi-linear interactive MF algorithm
(MLIMF) to model the interactions between the users and each event associated
with their final decisions. Our model considers not only the user-item rating
information but also the pairwise interactions based on some empirically
supported factors. In addition, we compared the proposed model with three
typical other methods: user-based collaborative filtering (UCF), item-based
collaborative filtering (ICF) and regularized MF (RMF). Experimental results on
two real-world datasets, \emph{MovieLens} 1M and \emph{MovieLens} 100k, show
that our method performs much better than other three methods in the accuracy
of recommendation. This work may shed some light on the in-depth understanding
of modeling user online behaviors and the consequent decisions.
Towards Inverse Modeling of Intratumoral Heterogeneity
Date: 2015-05-30 00:00:00

Development of resistance limits efficiency of present anticancer therapies
and preventing it remains big challenge in cancer research. It is accepted, at
intuitive level, that the resistance emerges as a consequence of cancer cells
heterogeneity at molecular, genetic and cellular levels. Produced by many
sources, tumor heterogeneity is extremely complex time dependent statistical
characteristics which may be quantified by the measures defined in many
different ways, most of them coming from statistical mechanics. In the paper we
apply Markovian framework to relate population heterogeneity with the
statistics of environment. As, from the evolutionary viewpoint, therapy
corresponds to a purposeful modification of the cells fitness landscape, we
assume that understanding general relation between spatiotemporal statistics of
tumor microenvironment and intratumor heterogeneity enables to conceive the
therapy as the inverse problem and solve it by optimization techniques. To
account for the inherent stochasticity of biological processes at cellular
scale, the generalized distance-based concept was applied to express distances
between probabilistically described cell states and environmental conditions,
respectively.
Regularizing Portfolio Risk Analysis: A Bayesian Approach
Date: 2015-10-26 00:00:00

It is important for a portfolio manager to estimate and analyze recent
portfolio volatility to keep the portfolio's risk within limit. Though the
number of financial instruments in the portfolio can be very large, sometimes
more than thousands, daily returns considered for analysis are only for a month
or even less. In this case rank of portfolio covariance matrix is less than
full, hence solution is not unique. It is typically known as the ``ill-posed"
problem. In this paper we discuss a Bayesian approach to regularize the
problem. One of the additional advantages of this approach is to analyze the
source of risk by estimating the probability of positive `conditional
contribution to total risk' (CCTR). Each source's CCTR would sum up to the
portfolio's total volatility risk. Existing methods only estimate CCTR of a
source, and does not estimate the probability of CCTR to be significantly
greater (or less) than zero. This paper presents Bayesian methodology to do so.
We use a parallelizable and easy to use Monte Carlo (MC) approach to achieve
our objective. Estimation of various risk measures, such as Value at Risk and
Expected Shortfall, becomes a by-product of this Monte-Carlo approach.
Asymptotic expression for the fixation probability of a mutant in star graphs
Date: 2016-03-18 00:00:00
Tasks: Math

We consider the Moran process in a graph called the "star" and obtain the
asymptotic expression for the fixation probability of a single mutant when the
size of the graph is large. The expression obtained corrects the previously
known expression announced in reference [E Lieberman, C Hauert, and MA Nowak.
Evolutionary dynamics on graphs. Nature, 433(7023):312-316, 2005] and further
studied in [M. Broom and J. Rychtar. An analysis of the fixation probability of
a mutant on special classes of non-directed graphs. Proc. R. Soc. A-Math. Phys.
Eng. Sci., 464(2098):2609-2627, 2008]. We also show that the star graph is an
accelerator of evolution, if the graph is large enough.
Option Pricing Accuracy for Estimated Heston Models
Date: 2015-07-21 00:00:00

We consider assets for which price $X_t$ and squared volatility $Y_t$ are
jointly driven by Heston joint stochastic differential equations (SDEs). When
the parameters of these SDEs are estimated from $N$ sub-sampled data $(X_{nT},
Y_{nT})$, estimation errors do impact the classical option pricing PDEs. We
estimate these option pricing errors by combining numerical evaluation of
estimation errors for Heston SDEs parameters with the computation of option
price partial derivatives with respect to these SDEs parameters. This is
achieved by solving six parabolic PDEs with adequate boundary conditions. To
implement this approach, we also develop an estimator $\hat \lambda$ for the
market price of volatility risk, and we study the sensitivity of option pricing
to estimation errors affecting $\hat \lambda$. We illustrate this approach by
fitting Heston SDEs to 252 daily joint observations of the S\&P 500 index and
of its approximate volatility VIX, and by numerical applications to European
options written on the S\&P 500 index.
Identifying the genetic basis of antigenic change in influenza A(H1N1)
Date: 2015-09-11 00:00:00

Determining phenotype from genetic data is a fundamental challenge. Influenza
A viruses undergo rapid antigenic drift and identification of emerging
antigenic variants is critical to the vaccine selection process. Using former
seasonal influenza A(H1N1) viruses, hemagglutinin sequence and corresponding
antigenic data were analyzed in combination with 3-D structural information. We
attributed variation in hemagglutination inhibition to individual amino acid
substitutions and quantified their antigenic impact, validating a subset
experimentally using reverse genetics. Substitutions identified as low-impact
were shown to be a critical component of influenza antigenic evolution and by
including these, as well as the high-impact substitutions often focused on, the
accuracy of predicting antigenic phenotypes of emerging viruses from genotype
was doubled. The ability to quantify the phenotypic impact of specific amino
acid substitutions should help refine techniques that predict the fitness and
evolutionary success of variant viruses, leading to stronger theoretical
foundations for selection of candidate vaccine viruses.
A mathematical approach to territorial pattern formation
Date: 2015-01-23 00:00:00

Territorial behaviour is widespread in the animal kingdom, with creatures
seeking to gain parts of space for their exclusive use. It arises through a
complicated interplay of many different behavioural features. Extracting and
quantifying the processes that give rise to territorial patterns requires both
mathematical models of movement and interaction mechanisms, together with
statistical techniques for rigorously extracting parameters from data. Here, we
give a brisk, pedagogical overview of the techniques so far developed to tackle
the problem of territory formation. We give some examples of what has already
been achieved using these techniques, together with pointers as to where we
believe the future lies in this area of study. This progress is a single
example of a major aim for 21st century science: to construct quantitatively
predictive theory for ecological systems.
Dynamical transitions in a pollination--herbivory interaction
Date: 2016-07-20 00:00:00

Plant-pollinator associations are often seen as purely mutualistic, while in
reality they can be more complex. Indeed they may also display a diverse array
of antagonistic interactions, such as competition and victim--exploiter
interactions. In some cases mutualistic and antagonistic interactions are
carried-out by the same species but at different life-stages. As a consequence,
population structure affects the balance of inter-specific associations, a
topic that is receiving increased attention. In this paper, we developed a
model that captures the basic features of the interaction between a flowering
plant and an insect with a larval stage that feeds on the plant's vegetative
tissues (e.g. leaves) and an adult pollinator stage. Our model is able to
display a rich set of dynamics, the most remarkable of which involves
victim--exploiter oscillations that allow plants to attain abundances above
their carrying capacities, and the periodic alternation between states
dominated by mutualism or antagonism. Our study indicates that changes in the
insect's life cycle can modify the balance between mutualism and antagonism,
causing important qualitative changes in the interaction dynamics. These
changes in the life cycle could be caused by a variety of external drivers,
such as temperature, plant nutrients, pesticides and changes in the diet of
adult pollinators.
  Abstract Keywords: mutualism, pollination, herbivory, insects,
stage-structure, oscillations
The Futures Premium and Rice Market Efficiency in Prewar Japan
Date: 2017-09-30 00:00:00

This paper studies the interrelation between spot and futures prices in the
two major rice markets in prewar Japan from the perspective of market
efficiency. Applying a non-Bayesian time-varying model approach to the
fundamental equation for spot returns and the futures premium, we detect when
efficiency reductions in the two major rice markets occurred. We also examine
how government interventions affected the rice markets in Japan, which
colonized Taiwan and Korea before World War II, and argue that the function of
rice futures markets crucially depended on the differences in rice spot
market's structure. The increased volume of imported rice of a different
variety from domestic rice first disrupted the rice futures. Then, government
intervention in the rice futures markets failed to improve the disruption.
Changes in colonial rice cropping successfully improved the disruption, and
colonial rice was promoted to unify the different varieties of inland and
colonial rice.