2-19-16

Determination of the discount rate for the conditions of enterprises of the mineral resources sector: argumentative issues

УДК 336.781.5:658.14.01

https://doi.org/10.21440/2307-2091-2019-2-121-125

Подкорытов В. Н., Мочалова Л. А. Determination of the discount rate for the conditions of enterprises of the mineral resources sector: argumentative issues // Известия УГГУ. 2019. Вып. 2(54). С. 121-125. DOI 10.21440/2307-2091-2019-2-121-125

The relevance of this study is the need to improve the accuracy of calculations of indicators characterizing the value of companies and the effectiveness of investments in various projects. The discount rate should accurately reflect market trends. The correctly calculated discount rate should play a special role in assessing the market capitalization of enterprises of the mineral resources sector; securities of the largest companies are the most popular among investors.
The aim of the work is a comparative analysis of definitions and methods for calculating the discount rate to identify its basic characteristics that contribute to obtaining an objective value. Results of work and their application. The authors analyzed various definitions of the discount rate and made the following conclusions. The discount rate should be understood as the minimum rate of return which a typical investor can expect while investing his own money in an asset that generates income at the current time (and/or assumes its receipt in the future). At the same time, it is necessary to have alternative (comparable) investment options on the market. Thus, the discount rate is not a return on the asset being valued, but an alternative return. The core statements of the specified definition of the discount rate are as follows: “Minimum rate of return”, “alternative investment options”, “alternative yield”. When taking into account the most significant aspects of this definition, the authors of this paper analyzed the existing methods of its calculation, which are most often used in the framework of the valuation and investment analysis of enterprises of the mineral resources sector. The Capital Assets Assessment Model (CAPM) was highlighted among other models, which most closely matches the specified definition of the discount rate. The model is based, firstly, not on subjectivism when calculating risk premiums, but on statistically confirmed market data; secondly, it takes into account the average market yield, providing for alternative options for capital investment and, accordingly, alternative yield; thirdly, it implies a minimal, reasonable yield barrier for potential investors. In addition, this model applies the coefficient β, which takes into account non-systemic risks of a particular field of activity, allows to consider the peculiarities and specific risks of enterprises of the mineral resources sector. Conclusion. Theory-based definitions of the discount rate (confirmed by statistical data) will allow building viable financial models of companies, which in turn will contribute to increasing the objectivity of investment analysis and valuation.

Keywords: discount rate, enterprise of the mineral resources sector, cumulative building model, capital asset pricing model, investment analysis, company valuation.

 

REFERENCES

  1. Kamnev I. M., Zhulina A. Yu. 2012, Methods to justify the discount rate. Problemy ucheta i finansov [Problems of Accounting and Finance], no. 2 (6), pp. 30–35. (In Russ.)
  2. Kozyr Yu. V. 2006, Osobennosti otsenki i realizatsii kontseptsii VBM [Features of evaluation and implementation of the VBM concept]. Moscow, 285 p.
  3. Efimova Yu. V. 2011, The choice of the discount rate in assessing the effectiveness of investment projects of industrial enterprises. Izvestiya Tul’skogo gosudarstvennogo universiteta [Izvestiya Tula State University. Economic and legal sciences], issue 1, part 1, pp. 161–165. (In Russ.)
  4. Malinovskaya O. V., Sapko E. A., Brovkina A. V. 2016, The discount rate of cash flows of investment projects of the transport complex: theoretical basis and evaluation. Finansovaya analitika: problemy i resheniya [Financial Analytics: Science and Experience], no. 2, pp. 15–30. (In Russ.)
  5. Titov A. N., Tazieva R. F., Fadeeva E. P. 2018, Simulation of the optimal discount rate and the choice of its probabilistic model. Vestnik tekhnologicheskogo universiteta [Bulletin of the Technological University], vol. 21, no. 4, pp.193–201. (In Russ.)
  6. Gribovsky S. V. 2007, About capitalization and discount rates once again. Otsenochnaya deyatel’nost’ [Valuation activities], no. 3, pp. 9–13. (In Russ.)
  7. Rafanelli P. 2016, Case Study (Part I): Applying And Assessing The Capitalization Rate. The Value Examiner, pp. 16–26.
  8. Lisi G. 2019, Income capitalization method and hedonic model: an integrated approach. Journal of Property Investment & Finance, vol. 37, issue 3, pp. 289–300. https://doi.org/10.1108/JPIF-11-2018-0088
  9. Hayler R. 2019, Post- to Pre-Tax Discount Rates: Not a Simple Conversion. Journal of Business Valuation & Economic Loss Analysis, vol. 14, issue 1. https://doi.org/10.1515/jbvela-2018-0013
  10. Filimonova I. V., Eder L. V., Babikov A. А. 2014, Justification of the choice of the discount rate when evaluating investment projects of the oil and gas complex. Ekologicheskiy vestnik Rossii [Ecological Bulletin of Russia], pp. 12–21. (In Russ.)
  11. Nazarov V. I. 2009, Geological and economic aspects of the problem of introducing a new Classification of reserves and forecast resources of oil and combustible gases. Mineral’nyye resursy Rossii. Ekonomika i upravleniye [Mineral resources of Russia. Economics and Management], no. 2, pp. 32–38. (In Russ.)
  12. Eremenko O. V. 2017, Features of determining the discount rate when evaluating the effectiveness of innovative projects in the development and operation of oil and gas fields. General-methodological issues. Aktual’nyye problemy ekonomiki i upravleniya [Topical issues of economics and management], no. 1 (13), pp. 46–55. (In Russ.)
  13. Ucal Sari Irem. 2018, Development of an integrated discounting strategy based on vendors’ expectations using FAHP and fuzzy goal programming. Technological & Economic Development of Economy, vol. 24, issue 2, pp. 635–652. https://doi.org/10.3846/20294913.2016.1213205
  14. Fokina S. A. 2016, Size premium: analysis of the Russian capital market. Vestnik Sankt-Peterburgskogo universiteta [Vestnik of Saint Petersburg University], ser. 5, issue 4, pp. 92–103. https://doi.org/10.21638/11701/spbu05.2016.405
  15. Demkin I. V., Nikonov I. M., Gabrielov A. A., Barkhatov V. D., Petrova M. S. 2016, Methodological problems of risk analysis of oil and gas projects. Problemy ekonomiki i upravleniya neftegazovym kompleksom [Issues of economics and management of oil and gas complex]. Part I, no. 4, pp. 18–27 (In Russ.). Part II, no. 5, pp. 20–28. (In Russ.)
  16. Boldyrev E. S., Burenina I. V., Zakharova I. M. 2016, Risk inventory when evaluating investment projects in the oil and gas industry. Naukovedenie [Science studies], online magazine, vol. 8, no. 1. http://dx.doi.org/10.15862/48EVN116 The article was received on April 9, 2019

 

Лицензия Creative Commons
All articles posted on the site are available under the Creative Commons Attribution 4.0 Global License.