pwc-archive/papers-with-abstracts huggingface dataset:
A note and a correction on measuring cognitive distance in multiple dimensions
Authors: Rousseau Ronald, Rahman A. I. M. Jakaria, Guns Raf, Engels Tim C. E.
Date: 2016-07-15 00:00:00

In a previous article (Rahman, Guns, Rousseau, and Engels, 2015) we described
several approaches to determine the cognitive distance between two units. One
of these approaches was based on what we called barycenters in N dimensions.
The present note corrects this terminology and introduces the more adequate
term 'similarity-adapted publication vectors'. Furthermore, we correct an error
in normalization and explain the importance of scale invariance in determining
cognitive distance. We also consider weighted cosine similarity as an
alternative approach to determine cognitive (dis)similarity. Overall, we find
that the three approaches (distance between barycenters, distance between
similarity-adapted publication vectors, and weighted cosine similarity) yield
very similar results.
Compact pairwise models for epidemics with multiple infectious stages on degree heterogeneous and clustered networks
Date: 2016-02-14 00:00:00
Tasks: Clustering

This paper presents a compact pairwise model that describes the spread of
multi-stage epidemics on networks. The multi-stage model corresponds to a
gamma-distributed infectious period which interpolates between the classical
Markovian models with exponentially distributed infectious period and epidemics
with a constant infectious period. We show how the compact approach leads to a
system of equations whose size is independent of the range of node degrees,
thus significantly reducing the complexity of the model. Network clustering is
incorporated into the model to provide a more accurate representation of
realistic contact networks, and the accuracy of proposed closures is analysed
for different levels of clustering and number of infection stages. Our results
support recent findings that standard closure techniques are likely to perform
better when the infectious period is constant.
Filterbased Stochastic Volatility in Continuous-Time Hidden Markov Models
Date: 2016-02-17 00:00:00

Regime-switching models, in particular Hidden Markov Models (HMMs) where the
switching is driven by an unobservable Markov chain, are widely-used in
financial applications, due to their tractability and good econometric
properties. In this work we consider HMMs in continuous time with both constant
and switching volatility. In the continuous-time model with switching
volatility the underlying Markov chain could be observed due to this stochastic
volatility, and no estimation (filtering) of it is needed (in theory), while in
the discretized model or the model with constant volatility one has to filter
for the underlying Markov chain. The motivations for continuous-time models are
explicit computations in finance. To have a realistic model with unobservable
Markov chain in continuous time and good econometric properties we introduce a
regime-switching model where the volatility depends on the filter for the
underlying chain and state the filtering equations. We prove an approximation
result for a fixed information filtration and further motivate the model by
considering social learning arguments. We analyze its relation to the switching
volatility model and present a convergence result for the discretized model. We
then illustrate its econometric properties by considering numerical
simulations.
MetaPalette: A $k$-mer painting approach for metagenomic taxonomic profiling and quantification of novel strain variation
Date: 2016-02-17 00:00:00

Metagenomic profiling is challenging in part because of the highly uneven
sampling of the tree of life by genome sequencing projects and the limitations
imposed by performing phylogenetic inference at fixed taxonomic ranks. We
present the algorithm MetaPalette which uses long $k$-mer sizes ($k=30, 50$) to
fit a $k$-mer "palette" of a given sample to the $k$-mer palette of reference
organisms. By modeling the $k$-mer palettes of unknown organisms, the method
also gives an indication of the presence, abundance, and evolutionary
relatedness of novel organisms present in the sample. The method returns a
traditional, fixed-rank taxonomic profile which is shown on independently
simulated data to be one of the most accurate to date. Tree figures are also
returned that quantify the relatedness of novel organisms to reference
sequences and the accuracy of such figures is demonstrated on simulated
spike-ins and a metagenomic soil sample. The software implementing MetaPalette
is available at: https://github.com/dkoslicki/MetaPalette. Pre-trained
databases are included for Archaea, Bacteria, Eukaryota, and viruses.
Studies on Regional Wealth Inequalities: the case of Italy
Date: 2016-02-17 00:00:00

The paper contains a short review of techniques examining regional wealth
inequalities based on recently published research work but is also presenting
unpublished features.
  The data pertains to Italy (IT), over the period 2007-2011: the number of
cities in regions, the number of inhabitants in cities and in regions, as well
as the aggregated tax income of the cities and of regions. Frequency-size plots
and cumulative distribution function plots, scatter plots and rank-size plots
are displayed. The rank-size rule of a few cases is discussed. Yearly data of
the aggregated tax income is transformed into a few indicators: the Gini,
Theil, and Herfindahl-Hirschman indices. Numerical results confirm that IT is
divided into very different regional realities. One region is selected for a
short discussion: Molise.
  A note on the "first digit Benford law" for testing data validity is
presented.
Power-law cross-correlations estimation under heavy tails
Date: 2016-04-20 00:00:00

We examine the performance of six estimators of the power-law
cross-correlations -- the detrended cross-correlation analysis, the detrending
moving-average cross-correlation analysis, the height cross-correlation
analysis, the averaged periodogram estimator, the cross-periodogram estimator
and the local cross-Whittle estimator -- under heavy-tailed distributions. The
selection of estimators allows to separate these into the time and frequency
domain estimators. By varying the characteristic exponent of the
$\alpha$-stable distributions which controls the tails behavior, we report
several interesting findings. First, the frequency domain estimators are
practically unaffected by heavy tails bias-wise. Second, the time domain
estimators are upward biased for heavy tails but they have lower estimator
variance than the other group for short series. Third, specific estimators are
more appropriate depending on distributional properties and length of the
analyzed series. In addition, we provide a discussion of implications of these
results for empirical applications as well as theoretical explanations.
Robust Financial Bubbles
Date: 2016-02-17 00:00:00

We study the concept of financial bubble in a market model endowed with a set
of probability measures, typically mutually singular to each other. In this
setting we introduce the notions of robust bubble and robust fundamental value
in a consistent way with the existing literature in the case a unique prior
exists. The notion of no dominance is also investigated under the uncertainty
framework. Finally, we provide concrete examples illustrating our results.
Which eligible assets are compatible with comonotonic capital requirements?
Authors: Pablo Koch-Medina, Cosimo Munari, Gregor Svindland
Date: 2016-02-17 00:00:00

Within the context of capital adequacy, we study comonotonicity of risk measures in terms of the primitives of the theory: acceptance sets and eligible, or reference, assets. We show that comonotonicity cannot be characterized by the properties of the acceptance set alone and heavily depends on the choice of the eligible asset. In fact, in many important cases, comonotonicity is only compatible with risk-free eligible assets. The incompatibility with risky eligible assets is systematic whenever the acceptability criterion is based on Value at Risk or any convex distortion risk measure such as Expected Shortfall. These findings qualify and arguably call for a critical appraisal of the meaning and the role of comonotonicity within a capital adequacy context.
Do co-jumps impact correlations in currency markets?
Date: 2017-10-15 00:00:00

We quantify how co-jumps impact correlations in currency markets. To
disentangle the continuous part of quadratic covariation from co-jumps, and
study the influence of co-jumps on correlations, we propose a new wavelet-based
estimator. The proposed estimation framework is able to localize the co-jumps
very precisely through wavelet coefficients and identify statistically
significant co-jumps. Empirical findings reveal the different behaviors of
co-jumps during Asian, European and U.S. trading sessions. Importantly, we
document that co-jumps significantly influence correlation in currency markets.
Molecular-level tuning of cellular autonomy controls the collective behaviors of cell populations
Date: 2016-02-17 00:00:00

A rigorous understanding of how multicellular behaviors arise from the
actions of single cells requires quantitative frameworks that bridge the gap
between genetic circuits, the arrangement of cells in space, and
population-level behaviors. Here, we provide such a framework for a ubiquitous
class of multicellular systems - namely, "secrete-and-sense cells" that
communicate by secreting and sensing a signaling molecule. By using formal,
mathematical arguments and introducing the concept of a phenotype diagram, we
show how these cells tune their degrees of autonomous and collective behavior
to realize distinct single-cell and population-level phenotypes; these
phenomena have biological analogs, such as quorum sensing or paracrine
signaling. We also define the "entropy of population," a measurement of the
number of arrangements that a population of cells can assume, and demonstrate
how a decrease in the entropy of population accompanies the formation of
ordered spatial patterns. Our conceptual framework ties together diverse
systems, including tissues and microbes, with common principles.
The Postulate of the Three Regimes of Economic Growth Contradicted by Data
Date: 2016-03-25 00:00:00

Economic growth in Western Europe, Eastern Europe, Asia, countries of the
former USSR, Africa and Latin America were analysed. It is demonstrated that
the fundamental postulate of the Unified Growth Theory about the existence of
the three regimes of growth (Malthusian regime, post-Malthusian regime and
sustained-growth regime) is contradicted by data. These regimes did not exist.
In particular, there was no escape from the Malthusian trap because there was
no trap. Economic growth in all these regions was not stagnant but hyperbolic.
Unified Growth Theory is fundamentally incorrect. However, this theory is also
dangerously misleading because it claims a transition from the endless epoch of
stagnation to the new era of sustained economic growth, the interpretation
creating the sense of security and a promise of prosperity. The data show that
the opposite is true. Economic growth in the past was sustained and secure.
Now, it is supported by the increasing ecological deficit. The long-term
sustained and secure economic growth has yet to be created. It did not happen
automatically, as suggested incorrectly by the Unified Growth Theory.
The effects of marine protected areas over time and species dispersal potential: A quantitative conservation conflict attempt
Date: 2016-07-28 00:00:00

Protected areas are an important conservation measure. However, there are
controversial findings regarding whether closed areas are beneficial for
species and habitat conservation as well as landings. Species dispersal is
acknowledged as a key factor for the design and impacts of closed areas. A
series of agent based models using random diffusion to model fish dispersal
were run before and after habitat protection. All results were normalised
without the protected habitat in each scenario to detect the relative
difference after closing an area, all else being equal. Results show that
landings of species with short dispersal ranges will take longer to reach the
levels of pre Marine Protected Areas (MPAs) establishment than landings of
species with long dispersal ranges. Further the establishment of an MPA
generates a higher relative population source within the MPA for species with
low dispersal abilities than for species with high dispersal abilities. Results
derived here show that there exists a win-win feasible scenario that maximises
both fish biomass as well as fish catches.
Value-at-Risk and backtesting with the APARCH model and the standardized Pearson type IV distribution
Date: 2016-02-18 00:00:00
Tasks: Management

We examine the efficiency of the Asymmetric Power ARCH (APARCH) model in the
case where the residuals follow the standardized Pearson type IV distribution.
The model is tested with a variety of loss functions and the efficiency is
examined via application of several statistical tests and risk measures. The
results indicate that the APARCH model with the standardized Pearson type IV
distribution is accurate, within the general financial risk modeling
perspective, providing the financial analyst with an additional skewed
distribution for incorporation in the risk management tools.
On optimal strategies for utility maximizers in the Arbitrage Pricing Model
Date: 2016-07-18 00:00:00

We consider a popular model of microeconomics with countably many assets: the
Arbitrage Pricing Model. We study the problem of optimal investment under an
expected utility criterion and look for conditions ensuring the existence of
optimal strategies. Previous results required a certain restrictive hypothesis
on the tails of asset return distributions. Using a different method, we manage
to remove this hypothesis, at the price of stronger assumptions on the moments
of asset returns.
ProQ3: Improved model quality assessments using Rosetta energy terms
Date: 2016-01-25 00:00:00

Motivation: To assess the quality of a protein model, i.e. to estimate how
close it is to its native structure, using no other information than the
structure of the model has been shown to be useful for structure prediction.
The state of the art method, ProQ2, is based on a machine learning approach
that uses a number of features calculated from a protein model. Here, we
examine if these features can be exchanged with energy terms calculated from
Rosetta and if a combination of these terms can improve the quality assessment.
Results: When using the full atom energy function from Rosetta in ProQRosFA the
QA is on par with our previous state-of-the-art method, ProQ2. The method based
on the low-resolution centroid scoring function, ProQRosCen, performs almost as
well and the combination of all the three methods, ProQ2, ProQRosFA and
ProQCenFA into ProQ3 show superior performance over ProQ2. Availability: ProQ3
is freely available on BitBucket at https://bitbucket.org/ElofssonLab/proq3
An efficient method for sorting and selecting for social behaviour
Date: 2017-02-22 00:00:00

In this article we provide a systematic experimental method for sorting
animals according to socially relevant traits, without assaying them or even
tagging them individually. Instead, they are repeatedly subjected to
behavioural assays in groups, between which the group memberships are
rearranged, in order to test the effect of many different combinations of
individuals on a group-level property or feature. We analyse this method using
a general model for the group feature, and simulate a variety of specific cases
to track how individuals are sorted in each case. We find that in the case
where the members of a group contribute equally to the group feature, the
sorting procedure increases the between-group behavioural variation well above
what is expected for groups randomly sampled from a population. For a wide
class of group feature models, the individual phenotypes are efficiently sorted
across the groups and thus become available for further analysis on how
individual properties affect group behaviour. We also show that the
experimental data can be used to estimate the individual-level repeatability of
the underlying traits.
Chirality in a quaternionic representation of the genetic code
Date: 2015-12-30 00:00:00
Tasks: Vocal Bursts Type Prediction

A quaternionic representation of the genetic code, previously reported by the
authors, is updated in order to incorporate chirality of nucleotide bases and
amino acids. The original representation assigns to each nucleotide base a
prime integer quaternion of norm 7 and involves a function that associates with
each codon, represented by three of these quaternions, another integer
quaternion (amino acid type quaternion) in such a way that the essentials of
the standard genetic code (particulaty its degeneration) are preserved. To show
the advantages of such a quaternionic representation we have, in turn,
associated with each amino acid of a given protein, besides of the type
quaternion, another real one according to its order along the protein (order
quaternion) and have designed an algorithm to go from the primary to the
tertiary structure of the protein by using type and order quaternions. In this
context, we incorporate chirality in our representation by observing that the
set of eight integer quaternions of norm 7 can be partitioned into a pair of
subsets of cardinality four each with their elements mutually conjugates and by
putting they in correspondence one to one with the two sets of enantiomers (D
and L) of the four nucleotide bases adenine, cytosine, guanine and uracil,
respectively. Thus, guided by two diagrams proposed for the codes evolution, we
define functions that in each case assign a L- (D-) amino acid type integer
quaternion to the triplets of D- (L-) bases. The assignation is such that for a
given D-amino acid, the associated integer quaternion is the conjugate of that
one corresponding to the enantiomer L. The chiral type quaternions obtained for
the amino acids are used, together with a common set of order quaternions, to
describe the folding of the two classes, L and D, of homochiral proteins.
On the Profitability of Optimal Mean Reversion Trading Strategies
Date: 2016-02-18 00:00:00
Tasks: PAIR TRADING

We study the profitability of optimal mean reversion trading strategies in
the US equity market. Different from regular pair trading practice, we apply
maximum likelihood method to construct the optimal static pairs trading
portfolio that best fits the Ornstein-Uhlenbeck process, and rigorously
estimate the parameters. Therefore, we ensure that our portfolios match the
mean-reverting process before trading. We then generate contrarian trading
signals using the model parameters. We also optimize the thresholds and the
length of in-sample period by multiple tests. In nine good pair examples, we
can see that our pairs exhibit high Sharpe ratio (above 1.9) over the in-sample
period and out-of-sample period. In particular, Crown Castle International
Corp. (CCI) and HCP, Inc. (HCP) achieve a Sharpe ratio of 2.326 during
in-sample period and a Sharpe ratio of 2.425 in out-of-sample test. Crown
Castle International Corp. (CCI) and Realty Income Corporation (O) achieve a
Sharpe ratio of 2.405 and 2.903 respectively during in-sample period and
out-of-sample period.
Modelling modal gating of ion channels with hierarchical Markov models
Date: 2016-02-18 00:00:00

Many ion channels spontaneously switch between different levels of activity.
Although this behaviour known as modal gating has been observed for a long time
it is currently not well understood. Despite the fact that appropriately
representing activity changes is essential for accurately capturing time course
data from ion channels, systematic approaches for modelling modal gating are
currently not available. In this paper, we develop a modular approach for
building such a model in an iterative process. First, stochastic switching
between modes and stochastic opening and closing within modes are represented
in separate aggregated Markov models. Second, the continuous-time hierarchical
Markov model, a new modelling framework proposed here, then enables us to
combine these components so that in the integrated model both mode switching as
well as the kinetics within modes are appropriately represented. A mathematical
analysis reveals that the behaviour of the hierarchical Markov model naturally
depends on the properties of its components. We also demonstrate how a
hierarchical Markov model can be parameterised using experimental data and show
that it provides a better representation than a previous model of the same data
set. Because evidence is increasing that modal gating reflects underlying
molecular properties of the channel protein, it is likely that biophysical
processes are better captured by our new approach than in earlier models.
Folding and escape of nascent proteins at ribosomal exit tunnel
Date: 2016-02-18 00:00:00

We investigate the interplay between post-translational folding and escape of
two small single-domain proteins at the ribosomal exit tunnel by using Langevin
dynamics with coarse-grained models. It is shown that at temperatures lower or
near the temperature of the fastest folding, folding proceeds concomitantly
with the escape process, resulting in vectorial folding and enhancement of
foldability of nascent proteins. The concomitance between the two processes,
however, deteriorates as temperature increases. Our folding simulations as well
as free energy calculation by using umbrella sampling show that, at low
temperatures, folding at the tunnel follows one or two specific pathways
without kinetic traps. It is shown that the escape time can be mapped to a
one-dimensional diffusion model with two different regimes for temperatures
above and below the folding transition temperature. Attractive interactions
between amino acids and attractive sites on the tunnel wall lead to a free
energy barrier along the escape route of protein. It is suggested that this
barrier slows down the escape process and consequently promotes correct folding
of the released nascent protein.
Pathways towards instability in financial networks
Date: 2017-02-25 00:00:00

Following the financial crisis of 2007-2008, a deep analogy between the
origins of instability in financial systems and complex ecosystems has been
pointed out: in both cases, topological features of network structures
influence how easily distress can spread within the system. However, in
financial network models, the details of how financial institutions interact
typically play a decisive role, and a general understanding of precisely how
network topology creates instability remains lacking. Here we show how
processes that are widely believed to stabilise the financial system, i.e.
market integration and diversification, can actually drive it towards
instability, as they contribute to create cyclical structures which tend to
amplify financial distress, thereby undermining systemic stability and making
large crises more likely. This result holds irrespective of the details of how
institutions interact, showing that policy-relevant analysis of the factors
affecting financial stability can be carried out while abstracting away from
such details.