Oil and Gas Industry Companies’ Classification and Ordering by the Level of Investment Attractiveness Algorithm
Chernova N. L., Serhiienko O. A., Huz O. B.

Chernova, Natalia L., Serhiienko, Olena A., and Huz, Ostap B. (2024) “Oil and Gas Industry Companies’ Classification and Ordering by the Level of Investment Attractiveness Algorithm.” The Problems of Economy 3:308–317.
https://doi.org/10.32983/2222-0712-2024-3-308-317

Section: Mathematical methods and models in economy

UDC 336.7, 330.3, 330.4

Abstract:
Investment development of industries is an important factor in their overall development, therefore the issue of classification and ordering of companies in the oil and gas industry by the level of investment attractiveness becomes particularly relevant. The aim of the article is the construction and practical implementation of an algorithm for the classification and ordering of companies in the oil and gas industry according to the level of investment attractiveness, the application of which will increase the efficiency of decisions regarding the formation of appropriate investment portfolios. The proposed algorithm includes the following basic steps: formation of information base of research; selection and implementation of the classification algorithm; arrangement of investment objects according to the level of investment attractiveness; investment portfolio formation. It is proposed to consistently use hierarchical and agglomerative classification algorithms. Hierarchical algorithms make it possible to perform a preliminary analysis of the system of objects in a multidimensional space, to estimate the density of their location and to put forward a preliminary hypothesis regarding the possible number of homogeneous groups. To obtain the final division of objects into a given number of clusters, it is suggested to use iterative algorithms. Depending on the contentual interpretation of the received clusters, one is chosen whose objects can potentially be included in the investment portfolio. Depending on the investor specific preferences, the selected stocks either form an independent portfolio, or are added as part of an already existing one. If the structure of the portfolio has already been determined, the number of stocks is determined depending on the known share of funds allocated to them. If only the list of assets that the portfolio should contain is formed, the task of finding the optimal portfolio structure is additionally solved using nonlinear optimization algorithms. The algorithm is implemented for the initial set of twenty-two stocks of companies that are included in the energy sector of the SP500 stock index. The initial dataset contains information about basic indicators of liquidity, solvency, profitability and market value of the mentioned companies. A division of the initial set of multidimensional objects into homogeneous groups was obtained, a contentual analysis of the obtained clusters was carried out, based on the results of which recommendations were made regarding the stocks inclusion into the investment portfolio.

Keywords: energy, oil and gas industry, risk, investment attractiveness, multidimensional space, cluster.

Fig.: 3. Tabl.: 5. Formulae: 2. Bibl.: 28.

Chernova Natalia L. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Software Engineering and Intelligent Control Technologies, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: natacherchum@gmail.com
Serhiienko Olena A. – Doctor of Sciences (Economics), Professor, Professor, Department of Entrepreneurship, Trade and Logistics, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: Elena.Sergienko@khpi.edu.ua
Huz Ostap B. – Postgraduate Student, Department of Entrepreneurship, Trade and Logistics, National Technical University «Kharkiv Polytechnic Institute» (2 Kyrpychova Str., Kharkіv, 61002, Ukraine)
Email: ostapguz1998@gmail.com

List of references in article

“The Global Industry Classification Standard“. https://www.msci.com/our-solutions/indexes/gics
Fidelity. https://digital.fidelity.com/prgw/digital/research/sector/detail/energy
Hayes, A. “S&P GSCI Definition, Commodity Types Listed, Potential Drawbacks“. https://www.investopedia.com/terms/g/gsci.asp
“Bloomberg Commodity Index 2024 Target Weights Announced“. https://www.prnewswire.com/news-releases/bloomberg-commodity-index-2024-target-weights-announced-301976390.html
“SPY ETF Stock Price History“. https://www.investing.com/etfs/spdr-s-p-500-historical-data
“S&P 500 Energy Historical Data“. https://www.investing.com/indices/s-p-500-energy-historical-data
Pohrebniak, A. Yu., and Lopatiuk, V. S. “Otsinka investytsiinoi pryvablyvosti pidpryiemstva“ [Assessment of the Investment Attractiveness of the Enterprise]. Ekonomichnyi visnyk NTU «KPI», no. 26 (2023): 79-83. DOI: https://doi.org/10.32782/2307-5651.26.2023.13
Ekonomika ta upravlinnia v naftohazovomu kompleksi Ukrainy: aktualni problemy, realii ta perspektyvy [Economics and Management in the Oil and Gas Complex of Ukraine: Current Problems, Realities and Prospects]. Ivano-Frankivsk, 2017.
Moiseienko, I. et al. Investytsiinyi analiz [Investment Analysis]. Lviv: LvDUVS, 2019.
Nikonova, N. V. “Investytsiina pryvablyvist pidpryiemstv: sutnist, faktory vplyvu ta otsinka isnuiuchykh metodyk analizu“ [Investment Attractiveness of Enterprises: Essence, Influencing Factors and Assessment of Existing Methods of Analysis]. Ekonomichnyi visnyk universytetu. 2017. https://economicbulletin.com/index.php/journal/article/view/298/300
Blank, I. A. Investitsionnyy menedzhment [Investment Management]. Kyiv: Yunayted London Treyd Limited, 1995.
Koiuda, V. O., Lepeiko, T. I., and Koiuda, O. P. Osnovy investytsiinoho menedzhmentu [Basics of Investment Management]. Kyiv: Kondor, 2008.
Kryvytska, O. R. “Do pytannia shchodo doslidzhennia investytsiinoi pryvablyvosti pidpryiemstva“ [To the Question Regarding the Study of the Investment Attractiveness of Enterprise]. Biznes Inform, no. 10 (2023): 246-252. DOI: https://doi.org/10.32983/2222-4459-2023-10-246-252
Prodanova, N. A. et al. “Techniques for Assessing the Investment Attractiveness of a Commercial Organization based on Classical Methods of Strategic Economic Analysis“. International Journal of Economics and Business Administration, vol. VII, no. 4 (2019): 35-46. DOI: https://doi.org/10.35808/ijeba/330
Mohylova, A. et al. “Estimation of Enterprise's Investment Attractiveness in the Conditions of Development“. Studies of Applied Economics, vol. 39 (5) (2021). DOI: https://doi.org/10.25115/eea.v39i5.5181
Lepetiukha, N. V., and Borokh, A. Yu. “Intehralna otsinka investytsiinoi pryvablyvosti IT-pidpryiemstva “Somnium Game”“ [Integrated Assessment of the Investment Attractiveness of the IT Enterprise "Somnium Game"]. Ekonomika i suspilstvo, no. 18 (2018): 447-452. DOI: https://doi.org/10.32782/2524-0072/2018-18-62
Mamonov, K. et al. “Formuvannia intelektualnykh system investytsiinoi pryvablyvosti budivelnykh pidpryiemstv ta vyznachennia vplyvu na nykh steikkholderiv“ [Formation of Intelligent Systems of Investment Attractiveness of Construction Enterprises and Determination of the Influence of Stakeholders on Them]. Finansovo-kredytna diialnist: problemy teorii ta praktyky, vol. 2 (43) (2022): 193-201. DOI: https://doi.org/10.55643/fcaptp.2.43.2022.3511
Komlichenko, O. O. “Investytsiina pryvablyvist haluzei ekonomichnoi diialnosti rehionu“ [Investment Attractiveness of Branches of Economic Activity of the Region]. Ekonomichnyi prostir, no. 156 (2020): 176-180. DOI: https://doi.org/10.32782/2224-6282/156-32
Kuznichenko, V. M. et al. “Metod analitychnoi protsedury vyboru obiekta dlia investuvannia“ [Method of Analytical Procedure for Choosing an Object for Investment]. Financial and Credit Activity Problems of Theory and Practice, vol. 4 (31) (2021): 291-300. DOI: https://doi.org/10.18371/fcaptp.v4i31.190919
Korepanov, H. S., Lazebnyk, Yu. O., and Ponomarova, T. V. “Zastosuvannia klasternoho analizu dlia hrupuvannia rehioniv za rivnem investytsiinoi pryvablyvosti“ [Application of Cluster Analysis for Grouping Regions According to the Level of Investment Attractiveness]. Visnyk Kharkivskoho natsionalnoho universytetu imeni V. N. Karazina. Ser. «Ekonomichna». 2014. https://periodicals.karazin.ua/economy/article/view/5409/4956
Biliak, N. I. “Klasternyi analiz investytsiinoi pryvablyvosti silskykh terytorii Lvivskoi oblasti“ [Cluster Analysis of Investment Attractiveness of Rural Areas of Lviv Region]. Visnyk Kharkivskoho natsionalnoho tekhnichnoho universytetu silskoho hospodarstva. 2014. https://repo.btu.kharkov.ua/jspui/handle/123456789/31926
Yelnikova, Yu. V. “Klasteryzatsii krain svitu za rivnem yikh pryvablyvosti dlia vidpovidalnykh investytsii“ [Clustering of the Countries of the World According to the Level of Their Attractiveness for Responsible Investments]. Ekonomika ta derzhava, no. 9 (2020): 86-90. DOI: 10.32702/2306-6806.2020.9.86
Hayes, A. “Understanding Liquidity Ratios: Types and Their Importance“. https://www.investopedia.com/terms/l/liquidityratios.asp
Elmerraji, J. “Guide to Financial Ratios“. June 04, 2022. https://www.investopedia.com/articles/stocks/06/ratios.asp
Hayes, A. “Profitability Ratios: What They Are, Common Types, and How Businesses Use Them“. https://www.investopedia.com/terms/p/profitabilityratios.asp
Briukhovetska, N. Yu., and Khasanova, O. V. Investytsiina pryvablyvist publichnoho aktsionernoho tovarystva: teoriia ta praktyka [Investment Attractiveness of a Public Joint-stock Company: Theory and Practice]. Kyiv, 2015.
Chernova, N. et al. “Ukraine Stock Market Spatial-Dynamic Analysis“. 2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). Ankara, Turkey, 2022. 900-906. DOI: https://doi.org/10.1109/ISMSIT56059.2022.9932757
Chernova, N. et al. “Modeling Internationally Diversified Investment Portfolio“. 2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T), 2020. 368-372. DOI: https://doi.org/10.1109/PICST51311.2020.9468042