234 research outputs found
Portfolio optimization with mixture vector autoregressive models
Obtaining reliable estimates of conditional covariance matrices is an
important task of heteroskedastic multivariate time series. In portfolio
optimization and financial risk management, it is crucial to provide measures
of uncertainty and risk as accurately as possible. We propose using mixture
vector autoregressive (MVAR) models for portfolio optimization. Combining a
mixture of distributions that depend on the recent history of the process, MVAR
models can accommodate asymmetry, multimodality, heteroskedasticity and
cross-correlation in multivariate time series data. For mixtures of Normal
components, we exploit a property of the multivariate Normal distribution to
obtain explicit formulas of conditional predictive distributions of returns on
a portfolio of assets. After showing how the method works, we perform a
comparison with other relevant multivariate time series models on real stock
return data.Comment: 19 pages, 9 figures, 2 table
Pion and kaon condensation in a 3-flavor NJL model
We analyze the phase diagram of a three-flavor Nambu-Jona-Lasinio model at
finite temperature and chemical potentials . We study
the competition of pion and kaon condensation and we propose a physical
situation in which kaon condensation could be led only by light quark finite
densities.Comment: 21 pages, 8 figures include
Quark coalescence based on a transport equation
We employ the Boltzmann equation for describing hadron production from a
quark-gluon plasma (QGP) in ultrarelativistic heavy-ion collisions. We propose
resonance formation in quark-antiquark scattering as the dominant
meson-production channel, which, in particular, ensures that energy is
conserved in the recombination process. This, in turn, facilitates a more
controlled extension of hadronization to low transverse momenta (), and to
address the experimentally observed transition from a hydrodynamic regime to
constituent quark-number scaling (CQNS). Based on input distributions for
strange and charm quarks with azimuthal asymmetries, , characteristic
for RHIC energies, we recover CQNS at sufficiently high , while at low
a scaling with transverse kinetic energy is found, reminiscent to
experiment. The dependence of the transition regime on microscopic QGP
properties, i.e. resonance widths and -values in the
process, is elucidated.Comment: 7 pages, 6 figure
JRLV at SemEval-2022 Task 5: The Importance of Visual Elements for Misogyny Identification in Memes
Gender discrimination is a serious and widespread problem on social media and online in general. Besides offensive messages, memes are one of the main means of dissemination for such content. With these premises, the MAMI task was proposed at the SemEval-2022, which consists of identifying memes with misogynous characteristics. In this work, we propose a solution to this problem based on Mask R-CNN and VisualBERT that leverages the multimodal nature of the task. Our study focuses on observing how the two sources of data in memes (text and image) and their possible combinations impact performances. Our best result slightly exceeds the higher baseline, but the experiments allowed us to draw important considerations regarding the importance of correctly exploiting the visual information and the relevance of the elements present in the memes images
Bayesian analysis of mixture autoregressive models covering the complete parameter space
Mixture autoregressive (MAR) models provide a flexible way to model time
series with predictive distributions which depend on the recent history of the
process and are able to accommodate asymmetry and multimodality. Bayesian
inference for such models offers the additional advantage of incorporating the
uncertainty in the estimated models into the predictions. We introduce a new
way of sampling from the posterior distribution of the parameters of MAR models
which allows for covering the complete parameter space of the models, unlike
previous approaches. We also propose a relabelling algorithm to deal a
posteriori with label switching. We apply our new method to simulated and real
datasets, discuss the accuracy and performance of our new method, as well as
its advantages over previous studies. The idea of density forecasting using
MCMC output is also introduced.Comment: 27 pages, 10 figures, 4 table
A NJL-based study of the QCD critical line
We employ a 3 flavor NJL model to stress some general remarks about the QCD
critical line. The dependence of the critical curve on
and is discussed. The quark masses are varied to
confirm that, in agreement with universality arguments, the order of transition
depends on the number of active flavors . The slope of the critical curve
vs. chemical potential is studied as a function of . We compare our
results with those recently obtained in lattice simulations to establish a
comparison among different models.Comment: 17 pages, 5 figure
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