SciTePress - Affiliation Profile

Research.Publish.Connect.

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Affiliation

State University of Economics and Technology

Context (please use complete words only)

Field

Sort by

2 Papers

Assessing Energy-related Markets through Multifractal Detrended Cross-correlation Analysis

Authors: Andrii Bielinskyi ¹ , Vladimir Soloviev ¹ , Serhiy Semerikov ¹ , Victoria Solovieva ² , Andriy Matviychuk ³ and Arnold Kiv ⁴

Affiliations: ¹ Kryvyi Rih State Pedagogical University, 54, Gagarin av., Kryvyi Rih, Ukraine , ² State University of Economics and Technology, 16, Medychna str., Kryvyi Rih, Ukraine , ³ Kyiv National Economic University named after Vadym Hetman, 54/1, Peremogy pr., Kyiv, Ukraine , ⁴ Ben-Gurion University of the Negev, 653, P.O.B., Beer-Sheva, Israel

Digital Object Identifier: 10.5220/0011365500003350

Proceedings of ISC SAI 2022, ISBN: 978-989-758-600-2

Quick Abstract

Regulatory actions aimed the sustainable development force ordinary traders, policymakers, institutional investors to develop new types of risk management strategies, seek better decision-making processes that would allow them more effectively reallocate funds when trading and investing in energy markets such as oil and gas. Due to their supply and demand, they are presented to non-equilibrium, chaotic, long-range dependent, etc. Oil and gas play an important role not only in the financial markets, but they are important in many goods and services, and their extensive usage leads to environmental damage. Thus, the dynamics of the corresponding energy-related indices is a useful indicator of the current environmental development, and their modeling is of paramount importance. We have addressed one of the methods of multifractal analysis which is known as Detrended Cross-Correlation Analysis (DCCA) and its multifractal extension (MF-DCCA) to get reliable and efficient indicators of critical events in the oil and gas markets. For example, we have taken daily data of Henry Hub natural gas spot prices (US$/MMBTU), WTI spot prices (US$/BBL), and Europe Brent spot prices (US$/BBL) from 7 February 1997 to 14 December 2021. Regarding their (multifractal) cross-correlations, we get such indicators as the DCCA coefficient 𝜌 𝐷𝐶𝐶𝐴 , the cross-correlation Hurst exponent, the maximal, minimal, and mean singularity strength, the width of multifractality, and its asymmetry with the usage of sliding window approach. Our empirical results present that all of the presented indicators respond characteristically during crashes and can be effectively used for modeling current and further perspectives in energy markets and sustainable development indices.

Big Data Aanalytics in Higher Education

Authors: Irina Vdovychenko ¹ , Valentyna Khotskina ² , Serhii Hushko ² , Victoria Solovieva ² and Sergiy Tkalichenko ²

Affiliations: ¹ National University, Vitaly Matusevich str., 11, Kryvyi Rih, 50027, Ukraine , ² State University of Economics and Technology, Medychna Str., 16, Kryvyi Rih, 50005, Ukraine

Digital Object Identifier: 10.5220/0011364200003350

Proceedings of ISC SAI 2022, ISBN: 978-989-758-600-2

Quick Abstract

The article offers an overview of the means and methods of one of the most demanded modern Big Data technologies for the use in the higher education system. The paper presents an analysis of publications on similar studies. A brief description of Big Data technology is given in it. The article highlights various information arrays in the archives of universities, which are systematically replenished. The use of Big Data technology examples in American universities are considered. The research results of correlations and links with characteristics of student subjects Olympiad’s winners were represented in the work. The purpose of the article was to substantiate and propose certain directions for researching processes in the higher education system using big data analytics. The authors propose the tasks, by solving which it would allow improving significantly the educational process in universities.