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3.3. АНАЛИЗ ФИНАНСОВЫХ ПОКАЗАТЕЛЕЙ - РЫЧАГ УПРАВЛЕНИЯ ЭФФЕКТИВНОСТЬЮ ДЕЯТЕЛЬНОСТИ НЕФТЯНЫХ КОМПАНИЙ
Кухаренко Олеся Геннадьевна, кандидат экономических наук, доцент кафедры финансов и кредита Место работы: Российский государственный социальный университет
ol.kukharenko@gmail.com
Аннотация: Нефтегазовый комплекс нашей страны играет важную роль, как в национальной экономике, так и на мировом энергетическом рынке. Несмотря на низкую цену на нефть, Россия по итогам 2015 года увеличила добычу нефти на 1,4% (534,081 млн тонн). [1] В связи с выходом России на мировую арену возникает необходимость в информации о финансовом состоянии российских и зарубежных компаний, и соответственно, требуется разработка современных методик проведения сравнительного анализа этих организаций. В статье представлены итоги корреляционного анализа на основании данных финансовых показателей крупнейших российских и международных нефтяных компаний, таких как: ПАО «ЛУКОЙЛ», ОАО «НК «Роснефть», ПАО «Газпром нефть» и ExxonMobil, Chevron, ConocoPhillips за 2009-2013 гг.
Ключевые слова: оценка финансового состояния, анализ финансовых коэффициентов, нефтегазовый комплекс, корреляционная матрица
THE ANALYSIS OF FINANCIAL RATIO - CONTROL'S EFFICIENCY LEVER OF ACTIVITY OF THE OIL AND GAS COMPANIES
Kukharenko Olesya G., Candidate of Economic Sciences, Associate professor of Department of Finance and Credit Work place: Russian State Social University
ol.kukharenko@gmail.com
Annotation: The oil and gas complex of our country plays an important role, both in national economy, and in the world energy market Despite the low price of oil, Russia on results of 2015 has increased its oil production by 1.4% (534.081 million tons). [1] In connection with the release of Russia on the world stage there is a need for information on the financial condition of Russian and foreign companies, and, accordingly, requires the development of modern methods of comparative analysis of these organizations. The article presents the results of the correlation analysis based on the data analysis of the key financial indicators of major Russian and U.S. oil companies, such as PAO
"LUKOIL", OJSC "NK" Rosneft ", PJSC" Gazprom oil "and ExxonMobil, Chevron, ConocoPhillips for 2009-2013 gg.
Keywords: financial condition assessment, ratio analysis, oil and gas industry, correlation matrix.
The financial condition of the company is one of the most important characteristics for assessing how reliable a firm is in market conditions is. Exploring the financial condition you can learn about the possibilities of the subsequent development of the company in the current business environment, and may determine whether the firm is competitive in general.
Professional management of finance inevitably demands the deep analysis which will allow estimating most precisely a financial and economic condition of the enterprises by means of modern methods of research. In this regard the priority and a role of the financial analysis significantly increase. Competent analysis makes it possible to identify and correct weaknesses in the financial sector and to find reserves to improve the financial condition of the company and its solvency; predict financial results based on the actual conditions of economic activities and the availability of equity and debt.
These questions can be tackled using the financial ratios analysis. Financial ratios are a very versatile, easy to use and useful tool. They are also convenient in making comparisons with previous periods or with competitors or market leaders. Therefore, being able to interpret them correctly and see how they are interconnected or how certain actions can affect the rations - in a positive or negative way - will provide valuable insight into how the company works.
In the article the main source for the analysis are the financial statements available for public: balance sheets and income statements and are tested two following hypotheses:
H1. Historical ratio values are good predictors of their own future values so ratio analysis is useful in predicting future performance of Russian and US firms in the oil and gas industry.
H2: The usefulness of certain ratios in the oil and gas industry is different in the US and in Russia.
Data for the analysis are taken from the official published sources for the 2009-2013 years.
In the article ratios were considered into four major categories (Liquidity, Profitability, Activity and Solvency). [2] Ratio analysis is an important tool for analyzing the company's financial performance [3]. Results of Ratio Analysis of the Russian and U.S. companies are shown in Table 1, Table 2 respectively.
The liquidity ratios in 2013 were decreased in five companies, except "Gazprom". In this company all ratios were increased including Cash Ratio - 73%, Current Ratio - 27%, Quick Ratio - 43%. The largest decrease was occurred in "Rosneft" including Cash Ratio - 135%, Current
Ratio - 81%, Quick Ratio - 104%. The profitability ratios were decreased in four companies and two companies were increased in 2013: The Activity ratios were increased in 2013 in ConocoPhillips, ExxonMobil, Rosneft OAO, Lukoil OAO. Indexes of other companies (Chevron and Gazprom Neft) were decreased. The Solvency ratios were increased in all Russian companies and one American company - Chevron. Indexes of other companies (ConocoPhillips and ExxonMobil) were decreased.
As we can see, U.S. companies have the problem with the liquidity and two U.S. companies (ConocoPhillips and
ExxonMobil) have the problem with profitability. The analysis shows that the three companies (ConocoPhillips, ExxonMobil, Lukoil OAO) have negative trend in financial performance. Other companies (Chevron, Rosneft OAO, Gazprom Neft) have positive trend in most financial performance. Despite the fact that the oil industry is an important sector in the economy of Russia when we view in terms of revenue for Russian companies is far from American companies.
Table 1.
Results of Ratio Analysis of the Russian companies
Gazprom OAO Lukoil ОАО Rosneft OAO
RATIOS FY FY TV FY FY FY FY FY FY FY FY FY FY FY FY
2009 2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013
iquidity Ratios Cash Ratio 0.3 0.4 0.4 0.3 0.5 0.2 0.2 0.3 0.3 0.2 0.1 0.4 0.4 0.9 0.4
Current Ratio 1.6 1.8 2.0 1.6 2.1 l.a 1.9 2.1 1.9 1.8 1.1 2.0 1.9 2.1 1.2
-i Quick Ratio 0.7 o.s O.S 0.7 1.1 0.7 0.9 0.9 O.S 0.6 0.4 0.7 0.8 1.3 0.6
Return on Common Equity 15.7 16.7 19.1 15.7 13.0 13.2 15.6 16.3 15.6 10.3 N/A 18.0 16.7 16.8 20.2
Ь Return on Assets 10.0 11.0 13.0 10.7 9.0 9.3 11.0 11.8 11.6 7.5 N/A 10.2 9.9 9.9 9.5
jj о Return on Capital 12.6 13.6 16.0 13.3 11.2 il .a 14.0 14.0 14.4 9.4 N/A 13.2 12.5 12.2 13.3
Return on Invested Capital 10.4 12.1 15.4 11.3 11.9 12.6 13.7 14.7 13.8 10.5 N/A 12.2 11.8 9.2 9.7
OperatingMargin 23.3 32.1 36.6 28.3 31.5 14.9 13.8 1.3 12.1 10.8 17.8 20.2 16.4 13.0 11.9
Netlncome Margin 26.1 26.3 28.2 25.7 21.7 10.3 10.5 9.3 9.5 6.6 10.7 15.6 11.9 12.2 12.0
f! Accounts Receivable Turnover 7.6 9.1 9.9 3.0 7.5 17.3 15.5 16.0 17.1 19.1 N/A 17.0 16.7 15.6 16.1
4 « Days Sales Outstanding 4Я.1 40.3 36.9 45.7 48.9 21.1 23.6 22.9 21.5 19.09 N/A 21.4 21.9 23.5 22.7
Long-Term Debt/Equity 21.1 17.2 15.1 13 9 15 3 16.4 15.2 10 8 8.0 12.0 31.4 30 8 29.0 36 4 53 2
Long-Term Debt/Capital 16,4 14,3 12.6 11.3 12.9 13.7 12.a 9.5 7.4 10.6 21.3 22.0 21.3 25.5 30.4
S- и ¡■s Long-Term Debt/Total Assets 14,2 12.2 10.3 9.9 10.9 11.7 10.3 3.0 6,0 3.7 17.4 13.3 17.S 21.3 22.3
Total Debt/Equity 2 В .El 20.1 19 8 17.7 18 7 20.1 1Й.Й 13.5 0.9 13.7 47 1 40 2 36.4 42 7 74 9
Total Debt/Capital 22.4 16,3 16.6 15.0 15.3 16.7 15.3 11.9 3.2 12.1 32.0 23.7 26.7 29.9 42.3
Total Debt/Total Assets 19,4 14,2 14.1 12.6 13.4 14.3 13.3 10.0 6.7 9.9 26.2 23.9 22.3 25.0 31.5
Table 2.
Results of Ratio Analysis of the U.S. companies
Chevron Corp ConocoPhilli ps Exxon Mobil Corp
RATIOS FY 200 9 FY FY FY FY FY FY FY FY FY FY FY FY FY FY
2010 2011 2012 2013 2009 2010 2011 2012 2013 2009 2010 2011 2012 2013
Й „ .11 Cash Ratio 0 02 0.4 0.2 0.2 0.4 0.3 0.5 0.5 0.6 0.5 0.2 0.1 0.2 0.1 0.06
Current Ratio 0.9 1.3 1.1 1.4 1.3 1.4 1.7 1.6 1.6 15 1.1 0.9 0.9 1.0 0.8
Quick Ratio 0.5 0.9 0.7 0.7 1.0 1.0 1.2 1.1 1.2 1.2 0.7 0.6 0.7 0.7 0.5
Return on Common Equity 7.5 17.4 23.8 20.3 15.0 11.7 19.3 18.6 14.9 18.3 17.3 23.7 27.3 28.0 19.2
& Return on Assets 3 0 7.4 13.6 11,8 8.8 6.4 10 9 8 0 6.2 7.8 8.4 11.4 13.0 13.5 9.6
1 1 Return on Capital N/A 13.2 21.6 18.7 13.5 10.6 17.4 14.3 11.2 13.2 15.9 21.6 24.5 26.5 17.3
t- p r Return on Invested Capital N/A 7.3 17.0 14.1 10.4 8.6 13.7 6.4 6.6 8.2 11.4 14.4 15.6 16.4 12.7
Operating Margin -3.7 7.7 16.2 15.7 12.9 9.0 13.4 23.1 22.1 21.5 9.5 11.7 16.1 15.7 10.3
Net Income Margin 3.2 6.5 11.4 11.8 10.1 6.6 10.0 19.4 14.5 16.8 7.0 8.9 9.5 10.7 8.3
f 1 Accounts Receivable Turnover 12.0 13.7 4.5 4.9 5.3 9.5 9.9 11.1 10.4 9.9 10.5 11.4 12.2 11.4 11.5
s s Days Sales Outstanding 30.5 26.6 80.8 74.4 57.7 38.4 37.0 32.9 35.2 36.7 34.7 32.0 29.9 32.2 31.9
Long-Term Debt/Equity 43.0 32.8 32.9 42.9 40.1 10.9 10.7 8.0 8.8 13.3 5.8 4.6 5.8 4.6 3.8
,5 Long-Term Debt/Capital 29.5 24.4 24.5 29.6 28.4 9.8 9.6 7.4 8.0 11.7 5.2 4.3 5.2 4.3 3.4
S Long-Term Debt /Total Assets 17.7 14.5 14.1 17.7 17.8 6.2 6.1 4.7 5.2 7.9 2.8 2.4 2.8 2.4 2.0
S Total Debt/Equity 45.8 34.1 34.4 44.9 41.3 11.5 10.8 8.3 8.8 13.6 10.6 6.7 10.6 6.7 12.6
5 Total Debt/Capital 31.4 25.4 25.6 31.0 29.2 10.3 9.8 7.7 8.1 12.0 9.6 6.3 9.6 6.3 11.2
Total Debt/Total Assets 18.8 15.1 14.8 18.5 18.3 6.4 6.2 4.8 5.2 8.1 5.1 3.5 5.1 3.5 6.5
Now let's test the hypothesis.
Correlation matrix of all variables included in the analysis is presented in Tables 3-6 which is calculated based on data of firms. This shows the usefulness year-by-year for all ratios six companies in the data base.
Table 3.
Results of Correlation matrix
a) Cash ratio
U.S. companies_
Cash ratio FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
Continuation of Table 3
Russian companies
FY 2009 1
FY 2010 0,190274 1
FY 2011 0,682666 0,847274 1
FY 2012 0,736642 0,804091 0,997061 1
FY 2013 0,04265 0,988953 0,759181 0,707085 1
Russian companies
Cash ratio FY ZOOS FY ZOlO FY ZOll FY ZOlZ FY ZO^
FY 2009 1
FY 2010 0,216266 1
FY 2011 -0,13785 0,9372 1
FY 2012 -0,92846 0,161846 0,495876 1
FY 2013 0,22272 0,999978 0,934872 0,155314 1
b) Current Ratio
U.S. companies
Current FY
Ratio FY 2009 FY 2010 FY 2011 FY 2012 2013
FY 2009 1
FY 2010 0,721237 1
FY 2011 0,868938 0,969536 1
FY 2012 0,583019 0,983276 0,908711 1
FY 2013 0,559016 0,97753 0,896118 0,999572 1
Russian companies
Current FY
Ratio FY 2009 FY 2010 FY 2011 FY 2012 2013
FY 2009 1
FY 2010 -0,67589 1
FY 2011 0,157958 0,620988 1
FY 2012 -0,49603 0,975206 0,779051 1
FY 2013 0,821087 -0,97565 -0,43394 -0,90292 1
c) Quick Ratio
s
Quick
Ratio FY2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,621709 1
FY 2011 0,806362 0,964553 1
FY 2012 0,87871 0,920191 0,990877 1
FY 2013 0,336481 0,946771 0,828262 0,745191 1
Quick Ratio FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,970702 1
FY 2011 0,842014 0,946969 1
FY 2012 -0,0439 0,197438 0,501968 1
FY 2013 0,925149 0,806829 0,574208 -0,41986 1
In this analyse, you can see that Cash ratio, Current ratio, Quick ratio of 2012 year of U.S. companies have a correlation of 0.71, 0.99, 0.75.
In this analyse, you can see that Cash ratio, Current ratio, Quick ratio of 2012 year of Russian companies have a correlation of 0.15, -0.9, -0.42.
So, the predictive power of the historical Liquidity Ratios is bigger in U.S. companies.
Table 4.
Correlation matrix for solvency ratios based on data of firms a) Long-Term Debt/Equity
U.S. companies
Long-Term Debt/Equity FY ZOOS FY ZOlO FY ZOll FY ZOlZ FY ZO^
FY 2009 1
FY 2010 0,999773 1
FY 2011 0,99899 0,99972 1
FY 2012 0,999786 1 0,999706 1
FY 2013 0,990758 0,987643 0,983662 0,987741 1
Russian companies
Long-Term Debt/Equity FY ZOOS FY ZOlO FY ZOll FY ZOlZ FY ZO^
FY 2009 1
FY 2010 0,981913 1
FY 2011 0,996779 0,993935 1
FY 2012 0,993849 0,99684 0,999529 1
FY 2013 0,972017 0,998912 0,987726 0,992052 1
b) Long-Term Debt/Capital U.S. companies
Long-Term Debt/Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,999327 1
FY 2011 0,998253 0,999748 1
FY 2012 0,999663 0,999943 0,99945 1
FY 2013 0,985377 0,978462 0,973586 0,98062 1
Continuation of Table 4
Continuation of Table 4
Russian companies
Long-Term Debt/Capital FY 2009 FY 2009 1 FY 2010 FY 2011 FY 2012 FY 2013
FY 2010 0,980637 1
FY 2011 0,995399 0,994889 1
FY 2012 0,993382 0,99664 0,999817 1
FY 2013 0,969853 0,998797 0,988741 0,991425 1
c) Long-Term Debt/Total Assets
U.S. companies
Long-Term Debt/Total Assets FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,999899 1
FY 2011 0,998891 0,999459 1
FY 2012 0,999555 0,999878 0,999851 1
FY 2013 0,984572 0,981987 0,975241 0,97891 1
Russian companies
Long-Term Debt/Total Assets FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,961765 1
FY 2011 0,984883 0,994667 1
FY 2012 0,978586 0,997544 0,999448 1
FY 2013 0,95684 0,999848 0,992716 0,99617 1
d) Total Debt/Equity
U.S. companies
Total Debt/Equity FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,999248 1
FY 2011 0,988042 0,993276 1
FY 2012 0,999647 0,999926 0,991791 1
FY 2013 0,999001 0,999982 0,993944 0,999836 1
Russian companies
Total Debt/Equity FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,964908 1
FY 2011 0,998755 0,976808 1
FY 2012 0,99764 0,98066 0,999823 1
FY 2013 0,969281 0,999852 0,980346 0,983881 1
e) Total Debt/Capital
U.S. companies
Total Debt/ Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,998470184 1
FY 2011 0,980623592 0,989955353 1
FY 2012 0,999413163 0,999778238 0,986758515 1
FY 2013 0,998111689 0,999981132 0,990805157 0,999630013 1
Russian companies
Total Debt/C apital FY2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,953173537 1
FY 2011 0,998251944 0,969381218 1
FY 2012 0,998206998 0,969566501 0,999999714 1
FY 2013 0,965603257 0,999023702 0,979283046 0,979435784 1
f) Total Debt/Total Assets
U.S. companies
Total Debt/ Total Assets FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,999407647 1
FY 2011 0,984882447 0,990260459 1
FY 2012 0,999182232 0,99998186 0,991081095 1
FY 2013 0,999546593 0,999990726 0,989651658 0,999946646 1
Russian companies
Total Debt/Total Assets FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,933705518 1
FY 2011 0,994197154 0,966803125 1
FY 2012 0,992163344 0,971124861 0,999846999 1
FY 2013 0,957650283 0,997255758 0,983067192 0,986122154 1
In this analyse, you can see that the predictive power of the historical Liquidity Ratios is the same in U.S. and Russian companies.
Table 5.
Correlation matrix for activity ratios (Accounts Receivable Turnover) based on data of firms
U.S. companies
Accounts Receivable Turnover FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,999743 1
FY 2011 -0,84375 -0,85571 1
FY 2012 -0,84027 -0,85235 0,999979 1
FY 2013 -0,74856 -0,76341 0,98749 0,988487 1
Russian companies
Accounts Receivable Turnover FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 1 1
FY 2011 1 0,99609 1
FY 2012 1 0,942165 0,96809 1
FY 2013 1 0,904895 0,93896 0,995212 1
So, the predictive power of the historical Liquidity Ratios is the same in U.S. and Russian companies (0.99).
Table 6.
Correlation matrix for activity ratios based on data of firms a) Return on Common Equity
Return Common Equity on FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,989745 1
FY 2011 0,471503 0,592638 1
FY 2012 0,645693 0,748148 0,977835 1
FY 2013 0,920804 0,855647 0,090211 0,296734 1
Russian companies
Return Common Equity on FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,981913 1
FY 2011 0,996779 0,993935 1
FY 2012 0,993849 0,99684 0,999529 1
FY 2013 0,972017 0,998912 0,987726 0,992052 1
Continuation of Table 6. b) Return on Assets
U.S. companies
Return on Assets FY2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 0,96853 1
FY 2011 -0,27052 -0,50162 1
FY 2012 0,05855 -0,19176 0,945224 1
FY 2013 0,278445 0,030628 0,849316 0,975107 1
Russian companies
Return on Assets FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 FY 2011 FY 2012 -1 1 -1 1 0,91175 8 0,88280 8 1 0,611974 1
FY 2013 1 -0,72748 -0,38148 -0,96452 1
c) Return on Capital U.S. companies
Return on Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 1 1
FY 2011 1 0,26929 1
FY 2012 1 0,508634 0,966148 1
FY 2013 1 0,839155 0,749777 0,895105 1
Russian companies
Return on Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 -1 1
FY 2011 1 0,427743 1
FY 2012 -1 0,999781 0,446562 1
FY 2013 1 -0,99834 -0,47916 -0,99932 1
d) Return on Invested Capital U.S. companies Return on Invested
Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 1 1
FY 2011 1 -0,53247 1
FY 2012 1 -0,20017 0,935902 1
FY 2013 1 0,103346 0,786887 0,953828 1
Continuation of Table 6
Russian companies Return on Invested
Capital FY 2009 FY 2010 FY 2011 FY 2012 FY 2013
FY 2009 1
FY 2010 1 1
FY 2011 -1 0,313836 1
FY 2012 1 0,870872 0,739989 1
FY 2013_-1 -0,16349 0,885395 0,342523_1
In this analyse, you can see that ROE, ROA, ROC, ROIC of 2012 year of U.S. companies have a correlation of 0.29, 0.97, 0.89, 095.
In this analyse, you can see that ROE, ROA, ROC, ROIC of 2012 year of Russian companies have a correlation of 0.99, -0.96, -0.99, 0.34.
So, the predictive power of the historical Profitability Ratios is bigger in U.S. companies.
After our correlation analysis we can say, that Liquidity Ratios and Profitability Ratios are good predictors in U.S. So, ratio analysis is useful in predicting future performance for U.S. firms in the oil and gas industry. Correlation analysis shows that:
- American companies have higher correlation, so ratio analysis will be useful and we can use most of the classic ratios;
- Russian companies have low correlation coefficients than U.S. companies and they have low value, so the operations are more volatile.
- Historical value more predicting power for U.S. companies in the oil and gas industry.
- Analyse the biggest oil companies in both countries, that Russian market is more risky than American and ratio analysis will show less about future of Russian companies.
The oil and gas industry remains the most important sector in the economy of Russia. Russia has one of the world's largest potential energy resources. At 13 % of the Earth, in a country with less than 3% of the world's population, accounts for about 13 % of the world's proven oil reserves. [3]
Despite the fact that the oil industry is an important sector in the economy of Russia when we view in terms of revenue for Russian companies is far from American companies. Список литературы:
1. http://www.cdu.ru/ URL:
http://www.cdu.ru/news/detail.php?ID=333240&sphrase_id=6067 (дата обращения: 09.06.16);
2. Robinson Th., Henry E., Pirie W., Broihahn M., Cope A. (2012) - International Financial Statement Analysis, 2nd Edition;
3. Tracy A. (2012). Ratio Analysis Fundamentals: How 17 Financial Ratios Can Allow You to Analyse Any Business on the Planet, Kindle Edition
4. Analytical Bulletin (2013). Oil and gas extraction and refining industries: Trends and Forecasts, № 13, Results 2013.
5. Викторов Е.Д., (2013), Анализ основных подходов к диагностике финансовой несостоятельности и банкротства российских
страховых компаний. Бизнес в законе. Экономико-юридический журнал, 1: 185-188.
6. Хмыров В.В., (2013), Управление кредитными рисками и рисками ликвидности в деятельности негосударственных пенсионных фондов. Бизнес в законе. Экономико-юридический журнал, 3: 151-157.
7. Чечеткин С.А., (2016), Анализ и оценка финансовых рисков на предприятии ОАО «БАБУШКИНА КРЫНКА». Бизнес в законе. Экономико-юридический журнал, 2: 101-104.
РЕЦЕНЗИЯ
Статья О.Г. Кухаренко посвящена вопросу оценки основных финансовых показателей крупнейших российских и международных нефтяных компании. Оценка финансового состояния предприятия помогает определить платежеспособность и финансовую устойчивость предприятия, а также своевременно выявить негативные тенденции в ее деятельности.
Успешное управление финансами неизбежно требует глубокого анализа, который позволит оценить наиболее точно финансовое состояние предприятия посредством современных методов исследования. В связи с этим роль финансового анализа значительно увеличивается.
Таким образом, сегодня, когда компания подвергается влиянию множества внутренних и внешних факторов, точная оценка финансового состояния является ключом к ее эффективному функционированию, основой для дальнейшего роста и развития компании.
Актуальность данной статьи не вызывает сомнения. Несмотря на сложившуюся ситуацию на мировой арене, нефтегазовая индустрия для России имеет особое значение. Ее влияние распространяется на многие сферы хозяйства нашей страны. Данная отрасль национальной экономики наиболее конкурентоспособная с точки зрения интеграции России в мировую экономическую систему. В связи с этим возникает необходимость в информации о существующем финансовом состоянии российских и зарубежных нефтяных компаний.
Автором статьи проведена глубокая работа по определению влияния финансовых показателей за прошедшие периоды на формирование прогноза о дальнейшем развитии российских и американских компаний нефтегазовой отрасли. Кроме того, автор выявил насколько отличается влияние некоторых финансовых коэффициентов компании нефтегазовой отрасли в США и России.
В результате проведенных исследований сделан следующий вывод. Поскольку у американских компаний более высокая корреляция, то коэффициентный анализ будет более полезен в предсказании будущего развития американских компаний нефтегазовой отрасли, чем российских компаний.
Научная статья О.Г. Кухаренко «Анализ эффективности природопользования в Курской области» полностью соответствует требованиям, предъявляемым к научным работам подобного рода. Статья может быть рекомендована для публикации в научном журнале.
Доктор экономических наук, профессор, профессор Российского государственного социального университета
Н.П. Белотелова
