1,720,982 research outputs found
An Empirical Investigation of Heavy Tails in Emerging Markets and Robust Estimation of the Pareto Tail Index
No full textIn this work we analyze and compare the performances of VaR-based estimatorswith respect to three different classes of distributions, i.e., Gaussian, Stable
and Pareto, and to different emerging markets, i.e., Egypt, Qatar and Mexico. This is motivated by the evidence that there are points of distinction between emerging
and developed markets mainly relating to the speed and reliability of information available to investors.We propose a computational Threshold Accepting-VaR based
algorithm (TAVaR) for optimally estimating the Pareto tail index. A Monte Carlo bias estimation analysis is also carried out by comparing our proposed methodology
with the Hill estimator and a variant of it
Fluctuation Distributions and Dynamics of Indexed Markets
No full textMarket price distributions and price fluctuation distributions have developed an increasing research and investment interest since about a century ago, as such distributions have usually been featured by displaying a peak profile with fat tails. In this work we consider a recent model that has successfully explained such fluctuation distribution profiles to currencies and commodities, by considering prices as temporally confined around a mean price, that jump to subsequent prices according to market activity. Thus, this model considers market prices hopping in time from supply-demand equilibrium points according to market forces. We consider such model to better understand the dynamics of indexes from a wide diversity of trading floors. Here, the hopping model successfully depicts fluctuation distributions at relatively short times, i.e., when intraday prices are considered. The inherent dynamics to indexes belong to diffusion as the mean squared price displacement displays a linear time relation to almost all studied indexes. Therefore, our study correctly differentiates fast and slowly diffusing indexes, indicating which markets exhibit faster or slower dynamics. Moreover, we find a particular index, the FTSE50, hallmarked by dynamics faster than diffusion. Here, the fluctuation distribution hopping model stops being efficient in depicting price fluctuation at a time where super diffusion is observed. Nevertheless, establishing an order in index dynamics, from fast to slow diffusion, allows considering the efficiency of different markets as diffusion should be observed at weak markets in terms of efficiency and the Efficient Market Hypothesis. The efficiency of each floor can be ordered, and even it can be considered that to stock floors as the ones considered, semi strong or strong efficiency is not reached, thus market agents are not able to reach all market information in time
Sustainability and Biclustering: An applicative study
No full textThe ongoing increasing importance of the tourism industry along with its multidimensionality and complexity have attracted in recent years great attention from both academics and policymakers. A great concern in public policy has been given to the themes pertaining to local government systems in order to strengthen territorial cooperation and governance [1]. With this regard, particular attention is drawn to clustering approaches which stems from the acknowledgement of their positive influence on companies' performance, countries' competitiveness and regional development [2]. As also stated by [3], clusters facilitate innova6on by contributing to the development of innovative processes, promote and strengthen the networking with other institutions, they are also able to better intercept consumers' demand and interests and boost technology development by inducing the synthesis of knowledge and informa6on needs of all stakeholders. Some real-experienced clustering strategies in tourism aim to foster destination development through policy orientations, marketing programs and attracting investments. The objective of this work is to use a biclustering algorithm, which is a two-dimensional clustering technique, to find spatial neighbours among tourist destination areas, i.e., Local Tourism Systems. We want to obtain aggregates that are better (with respect to some sustainability criteria) to those attained by adopting a standard one-dimensional clustering approach. To this end, we formulate the aforementioned objective as an optimization problem, and we solve it by means of Tabu Search. This last is used to prevent the biclustering algorithm from re-evaluating solutions (biclusters) already processed and targeted as unpromising [4]. The obtained results seem very promising and outperform those reported in the literature [5,6] demonstra6ng the efficacy of our proposed algorithms
Gender analysis and attention to gender: An experimental framework
No full textGender aspects are gaining more and more attention for policy makers, practitioners and faculties. They also have a great importance for funding purposes, since many calls for proposals by national and international agencies require a gender plan and/or an analysis of the gender aspect, especially referring to the extent to which a candidate research project affects differently men and women. In this context, we want to understand whether there exists a relationship between the gender diversity of corporate boards of directors and the way a business articulates gender aspects on their corporate communications and activities on the Internet. To achieve this goal, we created a set of meaningful keywords, coming from EU regulations, gender plan descriptions of EU funded projects, and genderrelated literature. Then, we shall use business intelligence tools to determine the occurrences of such keywords on the websites of the firms considered.
Our goal is to determine the relationship between the occurrence of these keywords and the relative presence of women in a firm board of directors, in order to understand whether the board’s gender diversity is somewhat correlated to the way a business “talks” about gender aspects in its website. A neural network analysis is also devoted to this goal
The Problem of Time Arrow in Financial Time Series
No full textAccording to the efficient market hypothesis, future movements of the market cannot be
predicted. This introduces an intrinsic time asymmetry of the financial time series as there
are no laws forbidding “predicting” past based on the current market fluctuations. This clear
time asymmetry in the basic laws of finance raises a question which we shall be referring
to as the problem of time arrow: are there any noticeable statistical differences between
forward-in-time and reverse-in-time market data. Majority of the statistical methods used
for financial time series are time-symmetric and hence, not usable for our purposes. The
first method used in our study is the analysis of the length-distribution of periods with
high variability. With this method, the markets are judged to have a high variability if
the price movements difference from the local average exceeds a threshold. The time arrow
enters the play via the local average which can be calculated over a retarded time window,
centred time window, or advanced time window. The second method used here is borrowed
from the turbulence studies: the odd order structure functions. These structure functions
have been traditionally used to quantify the so-called small-scale anisotropy of temperature
fields in a fully developed turbulence. Small-scale anisotropy means that if there is a global
anisotropy, i.e. a global average temperature gradient, the anisotropy survives at the smallest
Kolmogorov scales: the largest temperature jumps are taken in the direction of the global
gradient. Our study shows that while typically, there is no noticeable time asymmetry in
market data, under certain circumstances, there is indeed a statistically significant time
asymmetry which might provide a key to predicting a forthcoming crisis
Sustainability and tourist flow networks: a mean field bi-level optimization approach
No full textThe widespread acknowledgement of tourism as a strategic pillar for economic growth and development has boosted competitiveness among tourist destinations. This concept has been greatly emphasized during the current COVID-19 pandemic crisis. Nevertheless, the massive presence of tourists imposes the challenge of adopting sustainable tourism practices to balance economic prosperity opportunities with potential threats to the environment and local communities.
There are many definitions for sustainability, but the most effective one is ``the capacity to endure'' [Emel et al, 1997]: from an economic perspective this leads to find an equilibrium between short and long-term objectives so that to maximize short-term revenues along with long-term growth strategies.
Within the tourism industry a straight definition is provided by the WTO for which sustainable tourism is ``tourism that takes full account of its current and future economic, social and environmental impacts, addressing the needs of visitors, the industry, the environment and host communities''[UNWTO, 2005].
In this study we apply the tools of the mean field game theory [Lasry et al, 2007] to support a local authorities to deal with the challenging problem of finding the total visitors' experiential satisfaction while attaining the maximum sustainability benefits. To this end, inspired by the study in [Bagagiolo et al, 2021], we introduce a theoretical model that describes the visitors flows in a network which depicts an area of tourist attractions.
We also propose and formalize a bi-level optimal control model which addresses the often conflicting objectives of defining a sustainable-oriented policy by the local authorities while visitor aim at maximizing their satisfaction [Andria et al, 2020]. Specifically, the model upper level addresses the problem of selecting an optimal sustainable oriented control strategy, while its lower level describes the visitor flows in the assumption that the visitor satisfaction can be expressed in terms of the minimization of an appropriate cost function
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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