T r e n d s o f Y o u r B u s i n e s s E x c l u s i v e l y d i s t r i b u t e d b y India, Q4 2010 Electric Power Generation, Transmission and Distribution Please address all comments and enquiries to: [email protected]ISIEmergingMarketsPDF us-mckinsey1 from 115.249.53.242 on 2011-08-29 13:41:30 EDT. DownloadPDF. Downloaded by us-mckinsey1 from 115.249.53.242 at 2011-08-29 13:41:30 EDT. ISI Emerging Markets. Unauthorized Distribution Prohibited.
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T r e n d s o f Y o u r B u s i n e s s
E x c l u s i v e l y d i s t r i b u t e d b y
India, Q4 2010
Electric Power Generation, Transmission and Distribution
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
! This report has been compiled to the best of the authors’ knowledge, using information originating from verifiedsources. The authors of the report take no responsibility for the consequences of any decisions and actions taken as aresult of the use of this report. This report refers to the Indian economy.
Contents Page1. Macroeconomic Scenario - 4
2. Analysis of Investment Attractiveness - 5
- Attractiveness Indicators - 5
- Driving Forces of Attractiveness - 5
- Risk-Profitability Maps - 7
3. Analysis of Revenue - 9
- Long-term Trend. Business Cycle. Correlation - 9
- Seasonality in Revenues. Seasonal Adjusted Revenues - 10
4. Concentration in the Sector - 11
5. Analysis of Financial Ratios - 12
- Distributions of Financials in the sector - 12
- General Indicators - 13
- Profitability Ratios - 18
- Liquidity Ratios - 21
- Financial Cycles - 22
- Financial Leverage Ratios - 23
- Production Factors - 25
- Investment Outlays - 27
- Costs - 29
- Structure of Fixed Assets - 33
- Structure of Current Assets - 34
- Structure of Current Liabilities - 35
- Main Leverages - 36
- DuPont’s Pyramid - 37
6. Companies from the Sector - 38
- Top Players - market shares - 38
- Top Players from the Sector - 39
- Listed Companies from the Sector - 40
- Mergers and Acquisitions - 41
7. Key Concepts - 42
- Definitions of Indices - 42
- Definitions of Selected Concepts - 44
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Analysed sector:
Class Electric Power Generation, Transmission and Distribution
The following sub-classes are included in the class:
Hydroelectric Power Generation Electric Power Transmission, Control, and Distribution Nuclear Electric Power Generation Fossil Fuel Electric Power Generation Other Electric Power Generation
Only the sub-classes marked by an arrow are covered by EconTrends reports.
EconTrends for India is the unique tool for analyzing various Indian industries. It contains description ofmacroeconomic environment, analysis of investment attractiveness, detailed analysis of revenue as well as in-depthanalysis of a wide scope of financial ratios. The report covers not the full sector but only its major part, since it is buildon the bottom-up aggregated financial data on listed companies from the Accord Fintech database reporting onquarterly basis. Quarterly financial data from Income Statement are adjusted to assert their consistency with yearlyaudited figures.
Profitability of a given industry is evaluated on the basis of average forecasted dynamics of EBITDA in two followingquarters. Every industry has a granted profitability mark that ranges from 1 up to 5, which reflects its profitabilityversus other industries. Higher mark indicates higher profitability. Risk of an industry in turn is measured by thestandard deviation of forecasted Profitability Index. Every industry has also an assigned risk mark that ranges from 1up to 5, which reflects its risk versus other industries. Higher mark means here lower risk. Each industry is at the endcharacterized by the following two parameters – its profitability and risk. They are used for evaluation of the short term investment attractiveness, that reflects preferences of investors seeking to maximize their rates of return and tominimize the risk they face.
The final Short-Term Investment Attractiveness Ranking of an analyzed industry explains its relative attractivenesscomparing to other sectors. The lower a position within the ranking the higher is attractiveness of an industry. Changesin this position replicate either changes in profitability or in risk. Additionally like in the case of profitability and riskmeasurement the final attractiveness is graded from 1 to 5, where the highest grade means the highest attractiveness.Lower grade means worse “investment-weather conditions”, so either lower profitability or higher risk. The Short-TermInvestment Attractiveness Ranking is presented according to the structure of the North American IndustryClassification System (NAICS). However the used system of industry classification is not fully compatible with theNational Classification of Activities in India due to Indian statistics - specific factors.
The Short-Term Investment Attractiveness Ranking developed for India under the EconTrends ® methodology is basedon the so called Profitability Index, that shows forecasted dynamics of EBITDA. It serves as a proxy for dynamics ofdirty cash flows in enterprises from a given industry. Fundamental components of the Profitability Index like net salesand EBITDA margin, are forecasted using econometric models. The behavior over time of all these categories isillustrated using appropriate pictograms in the “Map of Forces”.
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
-> expected slight fall of GDP nominal y/y growth in Q2 2011 comparying to the value from Q4 2010-> expected slight fall of GDP real y/y growth in Q2 2011 comparying to the value from Q4 2010-> expected slight rise of CPI inflation (eop) in Q2 2011 comparying to the value from Q4 2010-> expected slight fall of PPI inflation (eop) in Q2 2011 comparying to the value from Q4 2010-> expected strenghtening of USD/INR exchange rate in Q2 2011 comparying to the value from Q4 2010
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
expected fall of attractiveness in the sector-> expected stabilisation of profitability-> expected stabilisation of risk (expected stabilisation in risk mark shown on the chart)
5 0
4 0
3 0
2 1
1 1
5 1
4 1
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2 1
1 1
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ttra
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ess
Pro
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isk
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1
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Current Attractiveness5 0
4 0
3 0
2 1
1 1
5 1
4 1
3 1
2 1
1 1
Fo
recaste
d A
ttra
cti
ven
ess
Pro
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bilit
yR
isk
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Forecasted Attractiveness
Driving Forces of Attractiveness - Profitability Index - y/y dynamics- Net Revenue per Company - y/y dynamics - EBITDA Margin - y/y dynamics
Current situation b a aForecasted situation e d e
Map of forces for the sector Net revenue per company - Y/Y dynamics
EBITDA margin - Y/Y dynamics
Profitability index - Y/Y dynamics
"+""-""o"
▲▼■
Symbol's colour Dynamics of profit Positive impact on profit’s dynamics Negative impact on profit’s dynamics Neutral impact on profit’s dynamics
Symbol’s sign
Fall of dynamics comparing to previous quarter Stabilisation of dynamics comparing to previous quarter
Symbol’s orientation Rise of dynamics comparing to previous quarter
Positive dynamics of "driving force" Negative dynamics of "driving force" Close to zero dynamics of "driving force"
expected rise in dynamics of net revenue in Q1 2011
expected fall in dynamics of net revenue in Q2 2011
Analysis of Investment Attractiveness Attractiveness Indicators
Net revenue per company - Y/Y dynamics
-10%
-5%
0%
5%
10%
15%
20%
Q1 2
009
Q2 2
009
Q3 2
009
Q4 2
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Q1 2
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Q2 2
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Q3 2
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Q4 2
010
Q1 2
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Q2 2
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Period
Net
reven
ue p
er
com
pan
y -
Y/Y
dyn
am
ics
-10%
-5%
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5%
10%
15%
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25%
30%
Pro
fita
bilit
y in
dex -
Y/Y
dyn
am
ics
Net revenue per company - Y/Y dynamics Profitability index - Y/Y dynamics
Forecast
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
expected rise in dynamics of EBITDA margin in Q1 2011
expected rise in dynamics of EBITDA margin in Q2 2011
EBITDA Margin - Y/Y dynamics
-15%
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
Q1 2
009
Q2 2
009
Q3 2
009
Q4 2
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Q1 2
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Q2 2
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Q3 2
010
Q4 2
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Q1 2
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Q2 2
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Period
EB
ITD
A M
arg
in -
Y/Y
dyn
am
ics
-10%
-5%
0%
5%
10%
15%
20%
25%
30%
Pro
fita
bilit
y in
dex -
Y/Y
dyn
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EBITDA Margin - Y/Y dynamics Profitability index - Y/Y dynamics
Forecast
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Risk-Profitability Maps
Risk - Profitability Map (current situation)
-0.6
-0.4
-0.2
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0.0 0.2 0.4 0.6 0.8 1.0 1.2
Risk
Pro
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All sectorsMost efficient sectorssub-classes belonging to selected groupSelected sector (C lass): Electric Power Generation, Transmission and DistributionInvestors' utility function
Risk - Profitability Map (current situation)Zoom
0.00
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0.12
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14
Risk
Pro
fita
bil
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All sectorsMost efficient sectorssub-classes belonging to selected groupSelected sector (Class): Electric Power Generation, Transmission and DistributionInvestors' utility function
risk - profitability map (current situation)
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
risk - profitability map (forecasted situation)
Risk - Profitability Map (forecasted situation)
-0.2
-0.1
0.0
0.1
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0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
Risk
Pro
fita
bil
ity
All sectorsMost efficient sectorssub-classes belonging to selected groupSelected sector (C lass): Electric Power Generation, Transmission and DistributionInvestors' utility function
All sectorsMost efficient sectorssub-classes belonging to selected groupSelected sector (Class): Electric Power Generation, Transmission and DistributionInvestors' utility function
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Analysis of Revenue Long-term Trend. Business Cycle. Correlation
Long-term trend in net revenue per company
0
2 000
4 000
6 000
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10 000
12 000
14 000
16 000
18 000
Mar
-07
Jun-
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Sep-
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Dec-0
7
Mar-0
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Jun-
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Sep-08
Dec-0
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-09
Jun-
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Dec-0
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Dec-1
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-11
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Dec-1
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Period
[mn
IN
R]
Net revenue per company Long-term trend in net revenue per company
ForecastM
ar-
08
Jun
-08
Sep
-08
Dec-0
8
Mar-
09
Jun
-09
Sep
-09
Dec-0
9
Mar-
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Jun
-10
Sep
-10
Dec-1
0
Mar-
11
Jun
-11
Sep
-11
Dec-1
1
Net Revenues per company [mn INR]
12 2
63.0
9 9
17.6
11 4
56.8
12 5
12.2
14 4
24.4
11 2
17.4
11 2
65.0
11 5
23.2
14 8
21.3
11 6
87.8
12 3
25.9
12 2
04.1
16 2
93.3
12 6
31.0
12 7
45.4
13 0
03.9
Longterm trend in net sales per company [mn INR] 1
Share of depreciation in total operating costs [%]Depreciation
-------------------------Total operating costs
V---V
Fin
an
cia
l le
ve
rag
e r
ati
os
Pro
du
ctio
n f
act
ors
V - Value for a given year
Inve
stm
en
t o
utl
ays
Co
sts
Fin
an
cia
l cy
cle
sDefinition of index
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Definitions of Selected Concepts
EconTrends for India are based to large extent on the structure of the North American IndustryClassification System (NAICS). Analyses made for respective industry divisions, groups, classes andsub-classes are consistent with this classification. However the used system of industry classificationis not fully compatible with the National Industrial Classification in India due to Indian statistics -specific factors. Moreover the reports are based on the bottom-up aggregation of individual companies financial data from the Accord Fintech database, which provides the financials not for all, but for allmajor companies from the non-financial sector. The measurement units in several observations in thedatabase have been adjusted to ensure appropriate consistency and accuracy of the data. Quarterlyfinancial data from Income Statement are adjusted to assert their consistency with yearly auditedfigures. Hence the report covers not the full sector but only its major part. It is worth emphasizingthat the aggregated financials from a given year/quarter apply to companies whose fiscal year/quarterended in that year/quarter. Aggregated financials are calculated only for listed companies reported on
Forecasting models used in EconTrends have a hierarchical structure. The first layer consists ofmodels that transmit behavior of macroeconomic variables like nominal GDP growth, increases in pricesto the behaviors of financial parameters like net sales per company and EBITDA margin in all analyzedeconomic divisions. EBITDA margin should be understood as earnings before interest, taxes,amortisation and depreciation. The next and last layer of models translates the behavior of the aboveparameters in economic divisions into the groups within them. The econometric models that are usedin respective layers have a linear structure and belong to a well known group of ADL (AutoregressiveDistributed Lags) models. The long term relation between GDP growth and growth of sales in a givensector (called implied long term growth) is also developed on the ground of these models.
quarterly basis to assert maximum consistency between quarterly and yearly figures.
Seasonal adjustment is an econometric procedure consisting of elimination of seasonal deviations thatimpair the effectiveness of econometric modeling. This statistical procedure is based on appropriate,specialized econometric tools (the Tramo/Seats method). The software applied performs seasonaladjustment according to the Indian calendar (e.g. public and religious holidays, etc.), to set off theimpact of differences in the number of working days in particular quarters. Forecasts of financialparameters in the given sectors are derived based on forecasts of deseasonalised trend. The accuracy of the seasonal adjustment procedure is additionally supported by verification of key statistical tests,inclusion of incidental factors and drastic leaps in production volume, as well as testing the model.
Seasonal deviations are obtained by using the Tramo/Seats econometric procedure. A seasonaldeviation shows the average deviation of the value of revenue at a given quarter from the long termtrend. Seasonal variation informs us about an additional changeability associated with a particularseason of the year, which is a result of temporarily increased or decreased revenue. Skilfulassessment of seasonal deviation may be one of the advantages of a firm, which will be able to assess the level of revenue in a given quarter, that in turn will result in better production planning. However,a bad assessment of seasonal changes may be a source of additional risk. The graph of seasonaldeviation for the period shows deviation from the long term trend in a given quarter (quarterly valuesare arranged chronologically in years i.e. January '98, '99 etc.), which allows for precise forecasting ofdeviation in the analyzed quarter. In the above materials we can see two methods of presentingseasonality. The first is the additive one, when the revenues are decomposed as a sum of long termtrend and nominal value seasonal deviations. The second way of presenting seasonality is the multipli-cative one, where seasonal deviations are calculated as the percentage deviations from the long termtrend (in that case a deviation of 103 means a deviation of 3% from the value of the trend, and e.g.98 a deviation of -2%).
Seasonal adjustment
Seasonal deviations
Forecasting models
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Forecasts presented in EconTrends for India relate to a period of two quarters ahead in relation tothe end of the time period for which statistical data are available.
Risk-profitability maps show the location of sectors depending on the value of profitability and riskthey achieve. Sectors singled out by being encircled by a red ring are most useful –„efficient” forinvestors, due to the relatively highest return at the lowest variability of profit (relatively high value ofthe Sharp’s index). On the basis of the coordinate values of „efficient” sectors, the preferences ofinvestors on the market are shown by a grey dotted line visible on the graphs – this is a level line ofthe linear function of utility for investors (Investors Utility Function). The level line shows preferencesof the majority of investors with regard to achieved profitability at a given risk. Sectors, which areplaced above the linear function of usefulness are preferred by investors due to the possibility ofachieving a high profitability, at a particular level of risk. Sectors lying below the level line are not asattractive for investors, due to the relatively high variability in profit as against their profitability.
The forces map shows decompositions of the profitability index into particular driving forces. The ideaof the strengths map is to show the effect of particular variables on the dynamics of profit both incurrent and forecasted situation.
coefficient is a measure of statistical dispersion in the market shares defined as the field between thediagonal and the Lorentz curve. It is defined as a ratio with values between 0 and 1. A low Ginicoefficient indicates more equal market shares, while a high Gini coefficient indicates more unequaldistribution. 0 corresponds to perfect equality (all companies having exactly the same market share)and 1 corresponds to perfect inequality (where one monopolist has all the market share, whileeveryone else has zero share in the market). It is worth noting that concentrations measurespresented above may be of limited use if the dataset for an analyzed sector consists of a only fewcompanies. Concentration measures are calculated for listed and non-listed companies reporting onyearly basis.
Y/Y Increase (Q/Q Increase), Y/Y Dynamics (Q/Q dynamics). Increases are calculated as absolutedifferences with respect to the preceding year (Y/Y) or preceding quarter (Q/Q). Dynamics arecalculated as relative [%] differences with respect to the preceding year (Y/Y) or preceding quarter(Q/Q).
Several concentration measures are used to examine the degree of the market power concentrationwithin the analyzed sectors. The Herfindahl-Hirschman Index (known as HHI), is a measure of the sizeof firms in relationship to the industry and an indicator of the amount of competition among them. It isdefined as the sum of the squares of the market shares of each individual firm: ie the average marketshare, weighted by market share. As such, it can range from 0 to 10,000 moving from a very largeamount of very small firms to a single monopolistic producer. Decreases in the Herfindahl indexgenerally indicate a loss of market power and an increase in competition, whereas increases imply theopposite. The Lorenz curve in turn, is a graph showing the proportion of the distribution assumed bythe bottom % market share values. It is used to represent market shares distribution, where it showsfor the bottom x% of companies in the sector, what percentage y% of the market share they have.The percentage of companies is plotted on the x-axis, the percentage of market share on the y-axis.It is considered it to be a measure of inequality of the market shares within the given sector. The Gini
The Lorenz curve in turn, is a graph showing the proportion of the distribution assumed by the bottom% market share values. It is used to represent market shares distribution, where it shows for thebottom x% of companies in the sector, what percentage y% of the market share they have. Thepercentage of companies is plotted on the x-axis, the percentage of market share on the y-axis. It isconsidered it to be a measure of inequality of the market shares within the given sector.
The Gini coefficient is a measure of statistical dispersion in the market shares defined as the fieldbetween the diagonal and the Lorentz curve. It is defined as a ratio with values between 0 and 1. Alow Gini coefficient indicates more equal market shares, while a high Gini coefficient indicates moreunequal distribution. 0 corresponds to perfect equality (all companies having exactly the same marketshare) and 1 corresponds to perfect inequality (where one monopolist has all the market share, whileeveryone else has zero share in the market).
It is worth noting that concentrations measures presented above may be of limited use if the datasetfor an analyzed sector consists of a only few companies.
Several concentration measures are used to examine the degree of the market power concentrationwithin the analyzed sectors.
The Herfindahl-Hirschman Index (known as HHI) is a measure of the size of firms in relationship to theindustry and an indicator of the amount of competition among them. It is defined as the sum of thesquares of the market shares of each individual firm: ie the average market share, weighted by marketshare. As such, it can range from 0 to 10,000 moving from a very large amount of very small firms to asingle monopolistic producer. Decreases in the Herfindahl index generally indicate a loss of marketpower and an increase in competition, whereas increases imply the opposite.
Herfindahl-Hirschman Index
Lorenz Curve
Gini coefficient
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E lec tric P ower Generation, T ransmiss ion and Dis tribution
Liquidity (of public company) - ranked accordingly to the averaged daily shares' turnover from the lastyear
Betas and Required Rates of Return - are calculated for listed companies under CAPM model.
- rate of return from investments in shares of an analysed company,
- Leveraged Beta,
- Unleveraged Beta,
- Required Rate of Return, where:
- effective tax rate.
- required (by investors) rate of return from investments in the shares of an analysed company; i.e. the expected rate of return when the market stays in equilibrium under CAPM assumptions,
- expected rate of return of the stock market index (BSESN, NSEI),
- risk-free rate of return (Yield of 364-days Treasury Bills)
- debt to equity ratio,
DuPont Pyramid is a very useful tool to decompose Return on Equity (ROA) into various ratios like:Return on Assets (ROA), Return on Sales (ROS) and Total Assets Turnover (TAT). It enables easydrawing of conclusions about the efficiency of an analyzed company in various areas of its activity.
The long-term trend indicates so-called potential level of production for a given sector i.e. a level atwhich there is no significant tension for a rise/fall in price dynamics and employment within the sector.
The business cycle shows fluctuations of business activity for a given sector around a long-term trendrepresenting the potential level of production for the sector. Positive values of the business cycleindicate a possibility of price dynamics’ increase pressure, increase of employment or rebound ininvestments, since the capacity utilization ratio remains currently high. Negative values of thebusiness cycle indicate a possibility of price dynamics’ decrease pressure, decrease of employment ordeterioration in investment activity, since the capacity utilization ratio remains relatively weak.
- rate of return of a stock market index (BSESN, NSEI),
Distributions of Financials present critical values of the distributions of various financials in theanalyzed sector. The presented critical values represent quartiles of the empirical distribution i.e. theyare calculated for 20%, 40%, 60% and 80% of the total population of companies from the givensector in a given year. These distributions make possible easy comparison of an analyzed company toother companies in the sector, looking at it from various financial angles.
Market multipliers (P/E, P/BV) - are widely used for the valuation purposes. Price to Earnings (P/E) iscalculated by dividing closury company's capitalisation in the quarter after analysed quarter by theearnings (net profits) from the last audited year. For the calculation of Price to Book Value (P/BV) theending year book value is taken.
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The long-term trend
Distributions of Financials
DuPont Pyramid
Market multiples (P/E, P/BV)
Betas and Required Rates of Return
Liquidity
The business cycle
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