IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i3p877-d734050.html
   My bibliography  Save this article

Assessment and Integral Indexing of the Main Indicators of Oil and Gas Companies by Circular Convolution

Author

Listed:
  • Irina Vygodchikova

    (Department of Differential Equations & Mathematic Economics, National Research Saratov State University, 410012 Saratov, Russia)

  • Mikhail Gordienko

    (Department of Financial Management, Plekhanov Russian University of Economics, 117997 Moscow, Russia)

  • Natalia Natocheeva

    (Department of Financial Markets, Plekhanov Russian University of Economics, 117997 Moscow, Russia)

  • Natalia Rud

    (Department of World Economy and Customs, North-Caucasus Federal University, 357500 Pyatigorsk, Russia)

  • Anzhela Namitulina

    (Department of Finance, Financial University under the Government of the Russian Federation, 105064 Moscow, Russia)

Abstract

In the oil and gas industry, which is the basis of the Russian energy market, a significant and urgent question arises: How to distribute companies according to their investment attractiveness? Accordingly, quantitative indicators are needed. Lacking extensive experience in the practical implementation of fundamental rating tools, work is needed to develop methodologies of weighting coefficients and lists, built on the experience of the “big three” rating agencies. The article proposes an algorithm for forming an integral rating of companies based on financial reporting indicators and the author’s rules of fuzzy logic based on the principle of “circular convolution”, from the best to the slave, deepening the analysis to the center, when all companies are exhausted and places in the rating are distributed. The problem of assessing and integrally indexing the indicators of large companies in leading sectors of the economy (e.g., oil and gas, banks, electricity) is becoming manifest, while it is obvious that there is competition between large companies of the country’s leading industries for state investment resources. The nature of the leading industries is such that it is necessary to assess the quality of the company’s functioning based on the formation of rating groups. Based on the rating, investments are distributed among the companies under consideration. The author has developed a portfolio model that is analogous to the Harry Max Markowitz model, which does not contradict this model but allows consideration of a broader range of risk assessments used in the model (for example, the rating of companies). The optimal portfolio is built, taking into account the resulting index and the initial grouping in the hierarchical data correction mode. The logically sequential method of circular convolution of four important indicators to an integral index and a mathematically substantiated method for optimizing the minimax portfolio presented in the work will allow the investor to develop optimal (from the point of view of the transparency of the apparatus used, mathematical feasibility and time spent on the implementation of the software package) tools for investing and enlarging his capital.

Suggested Citation

  • Irina Vygodchikova & Mikhail Gordienko & Natalia Natocheeva & Natalia Rud & Anzhela Namitulina, 2022. "Assessment and Integral Indexing of the Main Indicators of Oil and Gas Companies by Circular Convolution," Energies, MDPI, vol. 15(3), pages 1-13, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:877-:d:734050
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/3/877/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/3/877/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Boyer, M. Martin & Filion, Didier, 2007. "Common and fundamental factors in stock returns of Canadian oil and gas companies," Energy Economics, Elsevier, vol. 29(3), pages 428-453, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alex Borodin & Irina Vygodchikova & Galina Panaedova & Irina Mityushina, 2023. "Rating of Stability of Russian Companies in Oil and Gas and Electric Power Industries Based on Interval Volatility," Energies, MDPI, vol. 16(14), pages 1-16, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Miklesh Yadav & Nandita Mishra & Shruti Ashok, 2023. "Dynamic connectedness of green bond with financial markets of European countries under OECD economies," Economic Change and Restructuring, Springer, vol. 56(1), pages 609-631, February.
    2. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    3. Arezki,Rabah & Cho,Caleb Sungwoo & Ha Nguyen & Pham,Anh, 2022. "Corporate Debt and Stock Returns : Evidence from U.S. Firms during the 2020 Oil Crash," Policy Research Working Paper Series 10079, The World Bank.
    4. Aynur Pala, 2014. "The Effect of Valuation Ratios, Gold Price, and Petroleum Price on Equity Returns: A Comparison of Static Panel and Quantile Regressions," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 4(1), pages 80-89, January.
    5. Muñoz, M. Pilar & Dickey, David A., 2009. "Are electricity prices affected by the US dollar to Euro exchange rate? The Spanish case," Energy Economics, Elsevier, vol. 31(6), pages 857-866, November.
    6. Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Gül Serife Huyugüzel Kisla & Mohamad Husam Helmi & Coskun Akdeniz, 2021. "Oil Prices, Exchange Rates and Sectoral Stock Returns in the BRICS-T Countries: A Time-Varying Approach," CESifo Working Paper Series 9322, CESifo.
    7. Turhan Korkmaz & Emrah I. Çevik & Elif Birkan & Nesrin ÖzataÇ, 2010. "Testing Capm using Markov Switching Model: The Case of Coal Firms," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 23(2), pages 44-59, January.
    8. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2012. "Oil prices, exchange rates and emerging stock markets," Energy Economics, Elsevier, vol. 34(1), pages 227-240.
    9. Aastvedt, Tonje Marthinsen & Behmiri, Niaz Bashiri & Lu, Li, 2021. "Does green innovation damage financial performance of oil and gas companies?," Resources Policy, Elsevier, vol. 73(C).
    10. Ramaprasad Bhar & Biljana Nikolova, 2010. "Global Oil Prices, Oil Industry And Equity Returns: Russian Experience," Scottish Journal of Political Economy, Scottish Economic Society, vol. 57(2), pages 169-186, May.
    11. Wang, Zi-Xin & Liu, Bing-Yue & Fan, Ying, 2023. "Network connectedness between China's crude oil futures and sector stock indices," Energy Economics, Elsevier, vol. 125(C).
    12. Kumeka, Terver Theophilus & Uzoma-Nwosu, Damian Chidozie & David-Wayas, Maria Onyinye, 2022. "The effects of COVID-19 on the interrelationship among oil prices, stock prices and exchange rates in selected oil exporting economies," Resources Policy, Elsevier, vol. 77(C).
    13. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    14. Equiza-Goñi, Juan & de Gracia, Fernando Perez, 2020. "Impact of proved reserves on stock returns of U.S. oil and gas corporations using firm-level data," Energy Economics, Elsevier, vol. 92(C).
    15. Ali, Mohsin & Masih, Mansur, 2014. "Does Indian Stock Market Provide Diversification Benefits Against Oil Price Shocks? A Sectoral Analysis," MPRA Paper 58828, University Library of Munich, Germany.
    16. Swaray, Raymond & Salisu, Afees A., 2018. "A firm-level analysis of the upstream-downstream dichotomy in the oil-stock nexus," Global Finance Journal, Elsevier, vol. 37(C), pages 199-218.
    17. Ahmed, Walid M.A., 2020. "Corruption and equity market performance: International comparative evidence," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    18. Broadstock, David C. & Filis, George, 2014. "Oil price shocks and stock market returns: New evidence from the United States and China," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 417-433.
    19. Bård Misund & Petter Osmundsen, 2017. "Valuation of proved vs. probable oil and gas reserves," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1385443-138, January.
    20. Chia-Lin Chang & Michael McAleer & Roengchai Tansuchat, 2009. "Volatility Spillovers Between Crude Oil Futures Returns and Oil Company Stocks Return," CARF F-Series CARF-F-157, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:877-:d:734050. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.