Analysis of Metcash Limited on Australian Securities Exchange

This report provides an analysis of Metcash Limited on Australian Securities Exchange including details of the publicly traded company, finding beta of stock on basis of 5 years’ data, calculating the beta for analyzing the impact of COVID 19 over the chosen company, collecting 5- year data relating to the dividend and calculating the growth rate and return on share investment, and visualizing the problem with help of graphs.

Australian Securities
Exchange

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
PROBLEM 1....................................................................................................................................3
Details of publicly traded company from Australian Securities Exchange................................3
PROBLEM 2....................................................................................................................................3
Finding beta of stock on basis of 5 years’ data...........................................................................3
PROBLEM 3....................................................................................................................................5
Calculating the beta for analysing the impact of COVID 19 over the chosen company............5
PROBLEM 4....................................................................................................................................7
Collecting 5- year data relating to the dividend and calculating the growth rate and return on
share investment..........................................................................................................................7
PROBLEM 5....................................................................................................................................8
Visualising the problem with help of graphs..............................................................................8
CONCLUSION................................................................................................................................8
REFERENCES................................................................................................................................9

INTRODUCTION
Analysis of the return of the company and the stock is very important. This is because of
the reason that in case proper return will not be earned by the company then it will be affecting
the working efficiency of the company. This calculating of the return is helpful in analyzing and
evaluating the performance of the company.
PROBLEM 1
Details of publicly traded company from Australian Securities Exchange
Company Name: Metcash Limited
Stock Ticker Symbol: ASX:MTS
Stock Information: Ordinary fully paid
Most recent price $4.31
Market capitalization $4.13B
Daily volume 4,879,905
Number of ordinary
securities published on ASX 965,541,602
Most recent dividend $0.105
Annual dividend yield 4.67%
P/E ratio 18.03
EPS 0.239
Company Description: Food and Staples Retailing
PROBLEM 2
Finding beta of stock on basis of 5 years’ data
Variables
Metacash (1/1/2017
- 31/3/2022)
ASX200 (1/1/2017 -
31/3/2022)
Return (most recent period) -0.22 1.26
Mean (average returns) 0.45 0.12
Variance 22.59 4.11
Standard Deviation 4.762006 2.032181
*Slope (Beta) 0.038700317

In the above table required data for Metacash Limited and ASX200 is calculated. Return for
most recent period of Metacash is -0.22% whereas of ASX200 is 1.26% which shows share of
the company is on downfall as compared to the index which is positive. Also, average returns of
Metacash is 0.45% whereas of ASX200 is 0.12% which shows that average returns earned by the
company is favourable and even more than the index. Variation is seen as degree of variation of
actual return over a specific period of time is lower or higher than expected. Variance of
Metacash is 22.59 whereas of index is 4.11 which shows risk of variation is more in Metacash as
compared to the index. Standard deviation shows risk that actual return deviates from the mean
return. Lesser the deviation the better. Standard deviation of Metacash is 4.76 whereas of index
in 2.03 which shows Metacash is at more risk. Beta shows the volatility of stock to overall
market. Here, beta of 0.038 shows stock will move 3.8% of the market.
Regression
Regression
Statistics
Multiple R 0.02229788
R Square 0.0004972
Adjusted R
Square -0.0031793
Standard Error 2.03778718
Observations 273
ANOVA
df SS MS F
Significance
F
Regression 1 0.561862044 0.56186 0.1353 0.71328152
Residual 272 1129.500835 4.15258
Total 273 1130.062697
Coefficie
nts
Standard
Error t Stat
P-
value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 0 #N/A #N/A #N/A #N/A #N/A #N/A #N/A
-
0.219780
22
0.009484
28
0.0257838
71
0.367
84
0.713
28
-
0.041277
05
0.06024
56
-
0.0412
77
0.06024
56

The multiple R shows there is low correlation between the return of the company and
returns of the index. It computed result means that in the data set of returns of company and
index there is no relation between the two. R Square is used for showing the change that is
caused in the dependent variable as a result of change in the independent variable. In the above
data calculation, the dependent variable is the returns of the company and the independent
variable is the returns of the index (Seng and et.al., 2020). The computed result is 0.0004972 it
means that the change in independent variable does not bring about a change in the dependent
variable. Brook and Arnold (2018) say in contradiction to this that the returns of company are
influenced by the returns of the index.
PROBLEM 3
Calculating the beta for analysing the impact of COVID 19 over the chosen company
Chosen company Metcash ASX 200
Return (most recent period) 0.033 0.006
Mean 0.007 0.005
Variance 0.0012 0.0003
Standard deviation 0.0341 0.0171
Slope (beta) 0.863616037
In the above table required data for Metacash Limited and ASX200 is calculated. Return for
most recent period of Metacash is 0.033% whereas of ASX200 is 0.006% which shows share of
the company is earning more return than index in COVID situation. Also, average returns of
Metacash is 0.007% whereas of ASX200 is 0.005% which shows that average returns earned by
the company is favourable and more than the index. Variation is seen as degree of variation of
actual return over a specific period of time is lower or higher than expected (Reboredo, 2018).
Variance of Metacash is 0.0012 whereas of index is 0.0003 which shows risk of variation is more
in Metacash as compared to the index. Standard deviation shows risk that actual return deviates
from the mean return. Lesser the deviation the better. Standard deviation of Metacash is 0.0341
whereas of index in 0.0171 which shows Metacash is at more risk. Beta shows the volatility of
stock to overall market. Here, beta of 0.86 shows stock will move 86% of the movement in the
market.

Regression
Regression
Statistics
Multiple R 0.43299
R Square 0.18748
Adjusted R
Square 0.17123
Standard Error 0.03134
Observations 52
ANOVA
df SS MS F
Significance
F
Regression 1 0.01133 0.01133 11.5371 0.00135
Residual 50 0.04911 0.00098
Total 51 0.06044
Coefficients
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept 0.00284 0.00451 0.62978 0.5317 -0.0062 0.01191 -0.0062 0.01191
Return of
index 0.86362 0.25426 3.39663 0.00135 0.35293 1.37431 0.35293 1.37431
The data sets that were considered for the above calculations are returns of the company,
Metcash Limited and returns of the index for the duration of covid (Cepoi, 2020). The value of
multiple R is computed as 0.43299, it indicates that there is existence of moderate correlation
between the two variables. R Square for the data sets is 0.18748. this further indicates that the
change in the independent variable brings about a change of 18% in the independent variable.
The value for significance F is 0.00135. It means that there is correlation between the two
variables. Supply chain of the company was affected adversely during the pandemic period. It
faced difficulties in meeting the demands of the market (SEMENKOVA and EDILBAEV, 2018).
The stock of the company gets piled up and huge losses were suffered by the company because
of disparencies in the supply chain.

PROBLEM 4
Collecting 5- year data relating to the dividend and calculating the growth rate and return on
share investment
Year Dividends Growth Rates Stock price
Annual rate of
return using
Gordon Model
2022 0 -100% 4.31 NA
2021 0.105 31% 4.5 31%
2020 0.08 33% 3.222535 44%
2019 0.06 -8% 2.393918 0%
2018 0.065 8% 2.081667 14%
2017 0.06 100% 2.481224 107%
2016 0 0% 1.80 6%
The calculations and data in the above table shows the growth rate of dividends from the
year 2016 to 2022 and the rate of return on share investment from the year 2016 to 2022. Data
for dividend of 2022 is not available yet therefore growth rate of dividend in the year 2022 is -
100% and then dividend growth rate was calculated by the difference in the current and previous
dividend taking previous dividend as base. Data shows varied rate of growth rates with both
positive and negative movements (Ramelli and Wagner, 2020). Now, stock price was taken from
the website of yahoo finance to calculate value of rate of return according to the Gordon model.
Gordon model calculates current stock price by using dividend, rate of return and growth rate of
dividend therefore, Gordon model formula is used to calculate the rate of return as shown in the
last column. Here, dividend is taken of next year and price is taken of current year to calculate
the rate of return.

PROBLEM 5
Visualising the problem with help of graphs
CONCLUSION
In the end it is concluded that the return need to be growing and high for the company to
be successful. This is essential for the reason that when the return will not be high then it will be
affecting the working efficiency of the company. The above report concluded that performance
of the company was wide in case of five years’ data and in case of COVID duration it was less.

REFERENCES
Books and Journals
Cepoi, C. O., 2020. Asymmetric dependence between stock market returns and news during
COVID-19 financial turmoil. Finance Research Letters. 36. p.101658.
Derakhshan, A. and Beigy, H., 2019. Sentiment analysis on stock social media for stock price
movement prediction. Engineering Applications of Artificial Intelligence. 85. pp.569-578.
Ramelli, S. and Wagner, A.F., 2020. Feverish stock price reactions to COVID-19. The Review of
Corporate Finance Studies. 9(3). pp.622-655.
Reboredo, J. C., 2018. Green bond and financial markets: Co-movement, diversification and
price spillover effects. Energy Economics. 74. pp.38-50.
SEMENKOVA, E.V. and EDILBAEV, A.A., 2018. Behavioral Aspects in Calculating the Cost
of Risk in the Russian Stock Market. Journal of Applied Economic Sciences. 13(2).
Seng, C. Y., and et.al., 2020. New method for calculating electromagnetic effects in semileptonic
beta-decays of mesons. Journal of High Energy Physics. 2020(10). pp.1-27.