299 research outputs found
Limitations of portfolio diversification through fat tails of the return Distributions: Some empirical evidence
This study investigates the level of risk due to fat tails of the return distribution and the changes of tail fatness (TF) through portfolio diversification. TF is not eliminated through portfolio diversification, and, interestingly, the positive tail has declining fatness until a certain level is reached, while the negative tail has rising fatness. This indicates that fat tails are highly relevant to common factors on systematic risk and that the relevance of common factors is higher for the negative tail compared to the positive tail. In the portfolio diversification effect, the declining fatness of the positive tail further reduces risk, but the rising fatness of the negative tail does not contribute to this effect. The asymmetry between the fatness of the positive and negative tails in the return distribution corresponds to the asymmetry of the trade-off relationship between loss avoidance and profit sacrifice that is expected as a consequence of portfolio diversification. Investors use portfolio diversification to reduce their risk of suffering high losses, but following this strategy means sacrificing high-profit potential. Our study provides empirical confirmation for the practical limitation of portfolio diversification and explains why investors with diversified portfolios suffer high losses from market crashes. An examination of the Northeast Asian stock markets of China, Japan, Korea, and Taiwan show identical results
A Formal Model of Algorand Smart Contracts
We develop a formal model of Algorand stateless smart contracts (stateless ASC1). We exploit our model to prove fundamental properties of the Algorand blockchain, and to establish the security of some archetypal smart contracts. While doing this, we highlight various design patterns supported by Algorand. We perform experiments to validate the coherence of our formal model w.r.t. the actual implementation
Adsorption and release of sulfamethizole from mesoporous silica nanoparticles functionalised with triethylenetetramine
Mesoporous silica nanoparticles (MSN) were synthesised and functionalised with tri-ethylenetetramine (MSN-TETA). The samples were fully characterised (transmission electron mi-croscopy, small angle X-ray scattering, Fourier transform infrared spectroscopy, thermogravimetric analysis, zeta potential and nitrogen adsorption/desorption isotherms) and used as carriers for the adsorption of the antimicrobial drug sulphamethizole (SMZ). SMZ loading, quantified by UV–Vis spectroscopy, was higher on MSN-TETA (345.8 mg g−1) compared with bare MSN (215.4 mg g−1) even in the presence of a lower surface area (671 vs. 942 m2 g−1). The kinetics of SMZ adsorption on MSN and MSN-TETA followed a pseudo-second-order model. The adsorption isotherm is described better by a Langmuir model rather than a Temkin or Freundlich model. Release kinetics showed a burst release of SMZ from bare MSN samples (k1 = 136 h−1) in contrast to a slower release found with MSN-TETA (k1 = 3.04 h−1), suggesting attractive intermolecular interactions slow down SMZ release from MSN-TETA. In summary, the MSN surface area did not influence SMZ adsorption and release. On the contrary, the design of an effective drug delivery system must consider the intermolecular interactions between the adsorbent and the adsorbate
A Hierarchical Bayesian Approach to Ecological Count Data: A Flexible Tool for Ecologists
Many ecological studies use the analysis of count data to arrive at biologically meaningful inferences. Here, we introduce a hierarchical Bayesian approach to count data. This approach has the advantage over traditional approaches in that it directly estimates the parameters of interest at both the individual-level and population-level, appropriately models uncertainty, and allows for comparisons among models, including those that exceed the complexity of many traditional approaches, such as ANOVA or non-parametric analogs. As an example, we apply this method to oviposition preference data for butterflies in the genus Lycaeides. Using this method, we estimate the parameters that describe preference for each population, compare the preference hierarchies among populations, and explore various models that group populations that share the same preference hierarchy
Network conduciveness with application to the graph-coloring and independent-set optimization transitions
We introduce the notion of a network's conduciveness, a probabilistically
interpretable measure of how the network's structure allows it to be conducive
to roaming agents, in certain conditions, from one portion of the network to
another. We exemplify its use through an application to the two problems in
combinatorial optimization that, given an undirected graph, ask that its
so-called chromatic and independence numbers be found. Though NP-hard, when
solved on sequences of expanding random graphs there appear marked transitions
at which optimal solutions can be obtained substantially more easily than right
before them. We demonstrate that these phenomena can be understood by resorting
to the network that represents the solution space of the problems for each
graph and examining its conduciveness between the non-optimal solutions and the
optimal ones. At the said transitions, this network becomes strikingly more
conducive in the direction of the optimal solutions than it was just before
them, while at the same time becoming less conducive in the opposite direction.
We believe that, besides becoming useful also in other areas in which network
theory has a role to play, network conduciveness may become instrumental in
helping clarify further issues related to NP-hardness that remain poorly
understood
Tactical Voting in Plurality Elections
How often will elections end in landslides? What is the probability for a
head-to-head race? Analyzing ballot results from several large countries rather
anomalous and yet unexplained distributions have been observed. We identify
tactical voting as the driving ingredient for the anomalies and introduce a
model to study its effect on plurality elections, characterized by the relative
strength of the feedback from polls and the pairwise interaction between
individuals in the society. With this model it becomes possible to explain the
polarization of votes between two candidates, understand the small margin of
victories frequently observed for different elections, and analyze the polls'
impact in American, Canadian, and Brazilian ballots. Moreover, the model
reproduces, quantitatively, the distribution of votes obtained in the Brazilian
mayor elections with two, three, and four candidates.Comment: 7 pages, 4 figure
When Models Interact with their Subjects: The Dynamics of Model Aware Systems
A scientific model need not be a passive and static descriptor of its
subject. If the subject is affected by the model, the model must be updated to
explain its affected subject. In this study, two models regarding the dynamics
of model aware systems are presented. The first explores the behavior of
"prediction seeking" (PSP) and "prediction avoiding" (PAP) populations under
the influence of a model that describes them. The second explores the
publishing behavior of a group of experimentalists coupled to a model by means
of confirmation bias. It is found that model aware systems can exhibit
convergent random or oscillatory behavior and display universal 1/f noise. A
numerical simulation of the physical experimentalists is compared with actual
publications of neutron life time and {\Lambda} mass measurements and is in
good quantitative agreement.Comment: Accepted for publication in PLoS-ON
Interplay between telecommunications and face-to-face interactions - a study using mobile phone data
In this study we analyze one year of anonymized telecommunications data for
over one million customers from a large European cellphone operator, and we
investigate the relationship between people's calls and their physical
location. We discover that more than 90% of users who have called each other
have also shared the same space (cell tower), even if they live far apart.
Moreover, we find that close to 70% of users who call each other frequently (at
least once per month on average) have shared the same space at the same time -
an instance that we call co-location. Co-locations appear indicative of
coordination calls, which occur just before face-to-face meetings. Their number
is highly predictable based on the amount of calls between two users and the
distance between their home locations - suggesting a new way to quantify the
interplay between telecommunications and face-to-face interactions
Generalized Central Limit Theorem and Renormalization Group
We introduce a simple instance of the renormalization group transformation in
the Banach space of probability densities. By changing the scaling of the
renormalized variables we obtain, as fixed points of the transformation, the
L\'evy strictly stable laws. We also investigate the behavior of the
transformation around these fixed points and the domain of attraction for
different values of the scaling parameter. The physical interest of a
renormalization group approach to the generalized central limit theorem is
discussed.Comment: 16 pages, to appear in J. Stat. Phy
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