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ACCOUNTING FOR INNOVATION FACTORS IN THE FORMATION OF DEVELOPMENT STRATEGIES OF ENTERPRISES OF THE LEADING SECTORS
OF THE RUSSIAN ECONOMY
S.N. Larin1, Candidate of Technical Sciences, Leading Researcher
L.Yu. Lazareva2, Candidate of Technical Sciences, Leading Researcher
T.V. Stebenyaeva2, Candidate of Economic Sciences, Leading Researcher
1Central Economics and Mathematics Institute of the Russian Academy of Sciences
2Autonomous noncommercial organization Continuing Professional Education Institute of
International Accounting and Management Standards
(Russia, Moscow)
DOI:10.24412/2411-0450-2022-10-2-45-51
The Russian Foundation for Basic Research supported this work, project № 20-010-00169a.
The reported study funded by RFBR, project number 20-010-00169a.
Abstract. This article presents new areas of application of the portfolio analysis methodology for the formation of strategies for the development of enterprises in the leading sectors of the Russian economy. Authors take into account the factors of innovation in the face of constant changes in supply and demand, as well as the instability of prices for extracted raw materials and produced metals and products from them. As the leading sectors of the Russian economy, the study takes gas, oil, coal and metallurgical. Authors presented an analysis of the ratio of profitability and risk for different types of raw materials and metals exported from the Russian Federation. In addition, they described results of calculations of the basic criteria for portfolio analysis and assessed the relationship between average export and world prices for fuel and energy resources and metals. Carries analysis makes it possible to identify raw materials and metals, which in a given time range can show both minimal financial risks and the highest possible growth rates of profitability at an accepted level of risk. Obtained results are useful for the enterprises of the leading sectors of the Russian economy to select promising areas for investment and develop their development strategies on this basis.
Keywords: leading sectors of the economy, raw materials and metals, profitability, risk, portfolio theory, enterprise development strategies, «Profitability-risk» model.
Intrtoduction. The relevance of the work explained by the fact that the Russian economy is still focused on the export of fuel and energy resources. According to the Federal State Statistics Service, mining was one of the industries that had the greatest impact on the growth of the GDP physical volume index in 2018 [1]. Among all economic activities that contributed to GDP growth during 2018, mining ranked first. The indicator is 0,34 [2].
Research results. The purpose of this article is to identify raw materials and metals, which in the considered period can show the highest growth rates of profitability for an accepted level of risk, or minimal risk for a given level of profitability.
1. Materials and methods
According to the Federal Customs Service of Russia, in 2018 the volume of exports of crude oil, petroleum products, diesel fuel and natural gas amounted to almost $290 billion. For the same year, all Russian exports, including supplies of wheat, metals, machinery, equipment, timber, electricity, etc., amounted to $452 billion. Thus, about 65% of the total export volume accounted for by oil and gas industry enterprises. Metals and products are the second largest share in exports. It's volume is 9,9%. However, such a high-tech export item as machinery and equipment is only 6.5% of the total export volume (see Table 1 [3, 4]).
Table 1. Russian export structure in 2018
Export item Share in the export structure, %
Fuel and energy resources 63,7
Metals and products from them 9,9
Machinery and equipment 6,5
Products of the chemical industry 6,1
Food products and raw materials for their production 5,5
Timber and paper products 3,1
Other products 5,2
The average of an actual export prices of the Russian Federation and world prices for individual goods in 2017 (US dollars per ton) were used as the main input data for this study [5]. Prices based on data from the Federal Customs Service of Russia. Customs statistics of foreign trade formed based on cargo customs declarations, filled in by participants in foreign economic activity for all goods.
Innovative analysis has a rich history of its development, starting with an individual analysis of financial instruments and ending with the selection of those that showed the best investment results in the nearest periods. Based on the provisions of the modern theory of portfolio analysis, the investor, when forming an investment portfolio, builds a system of preferences for choosing the most attractive investment instruments. This system includes three basic criteria - expected return, risk, and ratio of expected return to risk. In the final synthesis of the investment portfolio, investment instruments are included in it taking into account the specified criteria.
With regard to the subject of this article, the essence of portfolio analysis is determined on the basis that financial investments in the
development of the gas, oil, coal and metallurgical industries, like any other category of investment, involve making a profit. The continuous change in supply and demand for raw materials and finished products of these industries, as well as significant changes in export-import prices for raw materials and metals occurring throughout the entire foreseeable period of their implementation, prove the prospect of choosing these industries as areas for investment and strategic development [6]. On this basis, we will consider investments in raw materials and metals as a tool for minimizing risks and diversifying the investment portfolio, and not just as a tool for generating income. The current level of development of the exchange infrastructure allows almost every individual investor to invest free financial resources in the development of the extraction of raw materials and the production of metals.
According to G. Markowitz [7], we will take the average value for each type of raw materials and metals for the period under consideration as the expected return, and the standard deviation as the risk level (see Table 2).
Ta ble 2. Results of calculations of the basic criteria of portfolio analysis
Item № Raw resources and metals Prices Expected return (Dx, %) Level of risk (Rs) Dx/Rs
1 Crude oil Average 1,57 4,11 0,38
World 1,79 5,61 0,32
2 Automobile gasoline Average 1,84 4,01 0,46
World 1,54 7,02 0,22
3 Diesel fuel Average 1,42 3,25 0,44
World 1,51 5,48 0,28
4 Natural gas Average 1,69 1,59 1,06
World 1,97 7,88 0,25
5 Copper Average 1,56 5,94 0,26
World 1,62 3,22 0,50
6 Nickel Average 1,46 6,73 0,22
World 1,48 6,44 0,23
7 Aluminum Average 2,44 3,05 0,80
World 1,40 2,53 0,55
8 Coal Average 0,87 4,23 0,20
World 2,01 6,36 0,32
Maximum value Average 2,44 6,73 1,06
World 2,01 7,88 0,55
Minimum value Average 0,87 1,59 0,2
World 1,40 2,53 0,22
2. Results and discussion
Aluminum demonstrates the highest profitability in the considered time interval at average prices, by world prices - coal. At the same time, the maximum expected return on aluminum at average export prices significantly exceeds the maximum return on coal at world prices. The worst result in terms of profitability at average prices shown by coal, and by world prices - aluminum.
In terms of the level of risk at world prices, the worst result (the maximum volatility of the expected return) shown by natural gas, nickel - by average prices.
The leader in risk level at average prices is natural gas, and at world prices - aluminum. Thus, aluminum at average prices stands out significantly in the group of leaders, which reflected in the value of the return to risk ratio at world prices for aluminum.
In terms of return to risk (let us call it an indicator of preference), natural gas is the leader in average prices, and aluminum in world prices, but with an almost twofold lag. Coal is an outsider at average prices, and motor gasoline is an outsider at world prices.
Some of the results of the above calculations of the basic criteria for portfolio analysis
[7] and the preference indicator "require" comments:
a) for five of the eight primary resources and metals which we consider as exchange goods-oil, diesel fuel, natural gas, aluminum and coal-average export prices were lower than world prices;
b) for motor gasoline, diesel fuel, natural gas, copper and aluminum, preference indicators calculated both at world and average export prices differ significantly;
c) in the vast majority of the considered raw materials and metals as exchange commodities, the variability of world prices is higher than the average export;
d) for oil, diesel fuel, natural gas, copper, nickel and aluminum, there is a correlation between average export and world prices, while for other raw materials and metals there is no such relationship (see Table 3).
If we consider the results separately for fuel and energy (raw) resources and for metals, it should be noted that for all analyzed metals the relationship is direct and close, while for fuel and energy (raw) resources, the relationship between average export and world prices is much weaker.
Table ^ 3. Assessment of the relationship between average export and world prices
Item № Primary resources and metals Correlation rate
1 Crude oil 0,96
2 Diesel fuel 0,86
3 Natural gas 0,67
4 Copper 0,92
5 Nickel 0,94
6 Aluminum 0,82
Based on the above results of calculations of the basic criteria of the portfolio theory [8, 9, 10], we will form a group of raw materials and metals promising for investment at average and world prices [11, 12]:
1) Initially, we chart a scatter, including all types of raw materials. The x-axis plots the standard deviation as a measure of risk (Rs), and on the y-axis, the average as an estimate of the expected return (Dx) (see pic. 1);
2.1
2.0
1,8 M 1,6 1,5 1,4 1,3 1.2
• Coal
--— •
Gas
w ¿iiuimiium
Pic. 1. Promising investment groups of raw materials and metals (At world prices)
2) Then we draw a trend line on the scatter, the results of which often compared with analysts' forecasts [8];
3) As a result, we get a trend line, which corrected by excluding some points (types of raw materials and metals). We leave the points with the highest level of profitability, while having the lowest level of risk.
Control of the process of formation of groups of raw materials and metals promising
for investment carried out by the value of the coefficient of determination. The closer R2 to one, the more the market movement determines the change in the profitability of the asset [13].
After that, we form scatter for groups of raw materials and metals that are promising for investment (see pic. 1, 2).
Pic. 2. Promising investment groups of raw materials and metals (At average export prices)
The corresponding "Return-risk" model for a group of raw materials and metals promising for investment (at world prices) has the following form:
Dx = 0,11Rs + 1,21; R2 = 0,87.
(1)
Where R2 - coefficient of determination; Dx - expected return; Rs - risk level.
The high value of the coefficient of determination indicates its practical significance. It follows from the model that an "attempt" to increase profit by 1% causes an increase in risk by 9%! In the formed group of raw materials and metals (according to world prices), it is possible to identify by the level of risk promising for investment:
a) for risk-averse investors, it's aluminum and copper;
b) for investors with a neutral attitude to risk - oil;
c) for risk averse investors - coal and gas.
The "Return-risk" model for a group of
raw materials and metals promising for investment (at average export prices) has the following form:
Dx = 0,30Rs + 1,19; R2 = 0,96.
(2)
It follows from the model that a 1% increase in profit causes an increase in the risk level by 3%, which suggests that the option of targeting at average export prices allows building investment strategies for the development of enterprises in the leading sectors of the Russian economy, associated with a significantly lower level of risk.
In the formed group of raw materials and metals (according to average export prices), it is possible to identify by the level of risk
a) for investors who avoid risk - oil;
b) for investors with a neutral attitude to risk - gas;
c) for risk-averse investors - aluminum.
Conclusion
Based on the results of the analysis, authors formulated the following conclusions.
1. The application of the portfolio analysis methodology and the "Risk-Return" model made it possible to form groups of raw materials and metals promising for investment at world and average export prices. Authors identified raw materials and metals, the implementation of which in the considered period can show either minimal risk at a given level of profitability, or the highest possible growth rates of profitability at an accepted level of risk. From the point of view of the dynamics of world prices, the following considers as promising for investment: coal, gas, copper, oil and aluminum. In addition, from the point of view of average export prices, the following considers as promising for investment: aluminum, gas and oil.
2. When choosing promising types of raw materials and metals for investment, we should first pay attention to aluminum, gas, oil and copper. If we additionally conduct a comparative analysis of raw materials and metals in relation to return to risk, then the results will be more "variegated". Synthesized groups of raw materials and metals ranked by risk level.
3. If we talk specifically about the prospects for investing in raw materials and metals, then we can say that when forming investment strategies for the development of leading industry enterprises, there is considerable room for maneuver and the possibility of obtaining large incomes.
promising for investment:
References
1. Federal State Statistics Service. - [Electronic resource]. - URL: https://www.gks.ru/ stor-age/mediabank/Pervaya-otsenka-VVP-za-2018-god.pdf. (date of the application: 11.10.2022).
2. Analytical Center under the Government of the Russian Federation. - [Electronic resource]. - URL: https://ac. gov.ru/archive/files/publication/a/21974.pdf. (date of application: 11.10.2022).
3. Kagan A. Export and import of the Russian Federation - 2019. Volumes, structure, goods (13.03.2019). - [Electronic resource]. - URL: https://kubdeneg.ru/eksport-import-rf-2019-obemy-struktura-tovary/ (date of the application: 14.10.2022).
4. Federal State Statistics Service. Export and import of the Russian Federation by goods (as of 08.10.2022). - [Electronic resource]. - URL: https://customs.gov.ru/folder/ 502 (date of the application: 08.10.2022).
5. Russian statistical yearbook. 2018: Statistical compendium. - Moscow: Rosstat, 2018. -694 p.
6. Financial portal Investing.com. - [Electronic resource]. - URL: https://www. investrat-ing.ru/investments/oil-gas-raw/ (date of the application: 10.10.2022).
7. Markowitz, H. Portfolio selection // The Journal of Finance. - 1952. - Vol. 7. - №1. -P. 77-91.
8. Gitman L.J., Jonk M.D. Fundamentals of investing. - Moscow: Delo, 1997. -1088 p.
9. Damodoran, A. Investment Appraisal: Tools and Methods for Appraising Any Assets. -Moscow: Alpina, 2007. -1340 p.
10. Fabozzi, F. Investment Management: Translation from English. - Moscow: INFRA-M, 2000. - 932 p.
11. Gertsekovich, D.A. Dynamic Portfolio Analysis of World Stock Indices / D.A. Gertsekovich, R.V. Babushkin // World of Economics and Management. - 2019. - V. 19. -№4. - P. 14-30.
12. Gertsekovich, D.A. The choice of priority areas for investing in the stock markets according to the "Return-risk" model // Economy and entrepreneurship. - 2018. - №9. - P. 673-680.
13. Burenin, A.N. Market of securities and derivative financial instruments. - Moscow: First Federal Bookselling Company, 1998. - 352 p.
УЧЕТ ФАКТОРОВ ИННОВАЦИОННОСТИ ПРИ ФОРМИРОВАНИИ СТРАТЕГИЙ РАЗВИТИЯ ПРЕДПРИЯТИЙ ВЕДУЩИХ ОТРАСЛЕЙ РОССИЙСКОЙ
ЭКОНОМИКИ
С.Н. Ларин1, канд. техн. наук, ведущий научный сотрудник
Л.Ю. Лазарева2, канд. техн. наук, ведущий специалист
Т.В. Стебеняева2, канд. экон. наук, ведущий специалист
Центральный экономико-математический институт РАН
2АНО ДПО Институт стандартов международного учета и управления
(Россия, г. Москва)
Аннотация. В статье представлены новые области применения методологии портфельного анализа для формирования стратегий развития предприятий ведущих отраслей российской экономики с учетом факторов инновационности в условиях постоянного изменения спроса и предложения, а также нестабильности цен на добываемые сырьевые ресурсы и производимые металлы и изделия из них. В качестве ведущих отраслей российской экономики в исследовании приняты газовая, нефтяная, угольная и металлургическая. Представлен анализ соотношения доходности и риска для разных видов сырьевых ресурсов и металлов, поставляемых на экспорт из Российской Федерации. Описаны результаты расчетов базовых критериев портфельного анализа и дана оценка взаимосвязи средних экспортных и мировых цен на топливно-энергетические ресурсы и металлы. Проведенный анализ позволяет выявлять сырьевые ресурсы и металлы, которые в заданном диапазоне времени могут показать, как минимальные финансовые риски, так и максимально высокие темпы роста доходности при принятом уровне риска. Полученные результаты могут использоваться предприятиями ведущих отраслей российской экономики для выбора перспективных направлений инвестирования и разработки на этой основе стратегий своего развития.
Ключевые слова: ведущие отрасли экономики, сырьевые ресурсы и металлы, доходность, риск, теория портфеля, стратегии развития предприятий, модель «Доходность-риск».
