Special Issue "Methods on Discrete Dynamical Systems, Networks, and Optimization for Signal Modelling"

A special issue of Symmetry (ISSN 2073-8994).

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editor

Prof. Dr. Ioannis Dassios
Website SciProfiles
Guest Editor
AMPSAS, University College Dublin, D04 Dublin, Ireland
Interests: differential/difference equations; dynamical systems; modelling and stability analysis of electric power systems; mathematics of networks; fractional calculus; mathematical modelling (power systems, materials science, energy, macroeconomics, social media, etc.); optimization for the analysis of large-scale data sets; fluid mechanics; discrete calculus; Bayes control; e-learning
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Special Issue Information

Dear Colleagues,

This Special Issue aims at collecting the latest results related to Discrete Dynamical Systems, Mathematics of Networks, Optimization, and their application in the mathematical modeling of Signals.

This Special Issue will accept high-quality papers having original research results, and its purpose is to bring together Mathematicians with Engineers, as well as other scientists.

Topics to be covered included but are not limited to:

Differential/difference equations;

Partial differential equations;

Dynamical systems;

Mathematics of networks;

Fractional calculus;

Modelling and stability analysis of signal models;

Discrete calculus;

Circuits theory;

Signal processing.

Prof. Dr. Ioannis Dassios
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Differential/difference equations
  • Partial differential equations
  • Dynamical systems
  • Mathematics of networks
  • Fractional calculus
  • Modelling and stability analysis of signal models
  • Discrete calculus
  • Circuits theory
  • Signal processing

Published Papers (1 paper)

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Research

Open AccessArticle
On the Statistical GARCH Model for Managing the Risk by Employing a Fat-Tailed Distribution in Finance
Symmetry 2020, 12(10), 1698; https://doi.org/10.3390/sym12101698 - 15 Oct 2020
Abstract
The Conditional Value-at-Risk (CVaR) is a coherent measure that evaluates the risk for different investing scenarios. On the other hand, since the extreme value distribution has been revealed to furnish better financial and economical data adjustment in contrast to the well-known normal distribution, [...] Read more.
The Conditional Value-at-Risk (CVaR) is a coherent measure that evaluates the risk for different investing scenarios. On the other hand, since the extreme value distribution has been revealed to furnish better financial and economical data adjustment in contrast to the well-known normal distribution, we here employ this distribution in investigating explicit formulas for the two common risk measures, i.e., VaR and CVaR, to have better tools in risk management. The formulas are then employed under the generalized autoregressive conditional heteroskedasticity (GARCH) model for risk management as our main contribution. To confirm the theoretical discussions of this work, the daily returns of several stocks are considered and worked out. The simulation results uphold the superiority of our findings. Full article
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