Corporate Financial Management Report: ASI, Beta, and WACC Analysis

This report delves into corporate financial management, commencing with an examination of stock market indices, specifically the Australian Securities Index (ASI), and the calculation of logarithmic returns. It explores portfolio construction based on beta values, analyzing the beta of a selected portfolio relative to the ASX and subsequently testing the weak form market efficiency hypothesis using t-tests. The findings suggest that the ASI exhibits weak form efficiency. Part B of the report shifts focus to Goodman Group, analyzing its financial performance, particularly the cash conversion cycle (CCC). It then addresses the weighted average cost of capital (WACC), the Gordon Growth Model (GGM), the Capital Asset Pricing Model (CAPM), and the debt-to-equity ratio (D/E), concluding with a correlation analysis between WACC and D/E. The report offers a theoretical analysis and results, providing a comprehensive overview of corporate financial management concepts and their application.

Corporate Financial Management

Table of Contents
Part A...............................................................................................................................................3
Stock Market Index......................................................................................................................3
Australian Securities Index..........................................................................................................3
Logarithmic Return......................................................................................................................4
Portfolio and Beta........................................................................................................................5
Beta..............................................................................................................................................6
The hypothesis of weak form market efficiency.........................................................................9
T-test of Weak Form Market Efficiency...................................................................................10
The findings...................................................................................................................................11
PART B.........................................................................................................................................11
Introduction................................................................................................................................11
Weighted average cost of capital (WACC)...............................................................................13
Gordon’s Growth Model (GGM)...........................................................................................13
Capital Asset Pricing Model (CAPM)...................................................................................14
Debt to Equity Ratio (D/E)........................................................................................................15
Correlation coefficient of WACC and D/E...............................................................................16
Theoretical Analysis with results...............................................................................................17
References......................................................................................................................................19

Part A
Stock Market Index
Stock Market Indices provide details of a particular stock or set of stocks in an industry. A
currency exchange file is a fact that shows changes in the stock exchange. To make a list, a
couple of comparable stocks are browsed through the previously registered protections on the
trade and collected (Hautcoeur, 2011).
The stock selection levels can be the type of activity, the display case, or the group size.
Stock quote estimates are recorded using hidden stock estimates. Any change in base inventory
costs shifts the overall estimate of the file. If the prices of most of the underlying securities rise,
then the index will rise and vice-versa (Ake and Ognaligui, 2010).
Australian Securities Index
The choose index was Australian Securities Indices (ASI) that was constituted by the most
superior 50 constituent securities in the Australian Securities Exchange (ASX). Its top 50 listed
enterprises were determined by their listed time (more than 24 months), their market value of
shares, and their volume of transactions. Moreover, both volume and market value required to
rank before the 90% of all stocks in the ASX (Australian Securities Indices, 2020). There was the
classification of 50 listed enterprises showing in the Table 1:

Table 1: 50 Listed Enterprises of ASX
Source: (Australian securities exchange, 2020)
Logarithmic Return
The logarithmic return referred that the changes of the capital value in the two period, and it
could make the stability of the financial data because it eliminated the instability of data set
(Sta˘rica & Granger, 2005).The formula of log return was that:
rt =ln ( Pt
Pt −1 )
Based on the ASI historical data set from January 2014 to December 2018, rt as the logarithmic
return result symbolized the changes of the prices, while the Pt and Pt −1represent respectively
the current price and previous price. The result showed in the Table 2 as the follows:

Table 2: The Logarithmic Return of ASI
Source: (Yahoo finance, 2020)
Portfolio and Beta
Portfolio
Portfolio has aim to distribute risk and profits across a combination of bonds, stocks and
derivatives. There were two types of portfolios, one stated the risk-free and risk-averse campaign
which concerned the interest of benefit and safety, and another commented on the combination
of the risk-taking heads with the negative relationship that the return of the risk would outweigh
the risk and reward an initiative and avoid the risk efficiently (Abreu & Mendes, 2010).

While the chosen portfolio of the researcher was based on the beta, the researcher collected and
arranged the beta of each enterprise through Yahoo Finance and selected the 5 companies with
the highest beta as the portfolio, and they were marked with green in the Table 3:
Table 3: Beta of 50 listed companies
Source: (Yahoo finance, 2020)
Beta
Beta (β) was the primary endpoint of the capital resource valuation model (CAPM), an indicative
indicator of actual risk gains and the valuation tool for assessing the volatility between a stock or

portfolio and the stock market (Blitz, Falkenstein and Vliet, 2014). The computational equation
of beta can be communicated as:
β= Covariance ( R p , Rm )
Variance ( Rm )
Where:
Rp: Returns of Portfolio
Rm: Returns of Market
Covariance: The different variability of the market return and portfolio return
Variance: The market variability of the market return
For example, the covariance estimated the development of both R_p and R_m, and the positive
relationship showed the progress of the two pieces of information moving together in the same
way, on the contrary. Although the variance represented an improvement of R_m relative to the
average R_m.
When:
β=0 Showed no correlation between the changes of portfolio and Market
β=1 Represented the stock price moving together with market
β >1 Denoted the volatility of security price higher than the market
β <1 Expressed the trends of share price lower than the market
The researcher had the ability to use "slope" on Excel to measure the beta, where the log output
of the folder was the known value of y and the logarithmic result of the securities trading list
(ASX) was the known value of x. As can be seen in Table 4, the package was established by the
five companies of equal weight, so the beta was 1.31 between the package and ASX. The value
showed that the volatility of the selected portfolio was 1.31 times higher than ASX, and if ASX 1
revenue increased or decreased, the package would increase by 1.31 as a gain or fall by 1.31 as
its loss. In other words, the beta was the impetus to assess the open door as well as the risk.

Table 4: Beta of Portfolio

Source: (Yahoo Finance, 2020)
The hypothesis of weak form market efficiency
The factor that influenced the productive profitability of the market (EMH) was given by
heterogeneous data that could influence the level of value while a cost difference would have
emerged from the data differential (Jarrow) and Larsson, 2012).
The market was capable of weak structure, citing interrelated data that were similar to
current value costs and it could not be assumed that previous protection costs and future costs
influenced by the new data and its models were unknown, to characterize the sporadic future

costs. In this way, the vulnerable type of EMH has also been cited as a predisposition to irregular
walking (Bowen, Hutchinson and O’Sullivan, 2013).
The point of this article was to find the test to establish whether the ASX market is non-
random walk or the weak form efficient, so below are two theories:
H0 : R ( p ) ≤ R ( I )
H1 : R ( p ) > R ( I )
Where H0signified the weak form of EMH which the both variables were indifference
relationship, while H1represented the non-random walk market efficiency that the both variables
existed the difference relationship.
The test would use one-tailed test to measure the both hypotheses and the formula of t-start
showed in the following:
tstat = x p−xi
√ σ p
2
n + σi
2
n
If t-stat was lower than t-critical, H0 had been accepted.
If t-stat was higher than t-critical, H1had been accepted and H0 had been rejected.
T-test of Weak Form Market Efficiency
The probability of rejection taken was 0.05 considering the confidence interval at 0.95. As
shown in Table 5, the t-stat was 0.8544 and less than 1.67 of a single-tailed t-critical, which
meant that the H_0 suspect was accepted, along these lines the market the irregular walking
pattern. Thus the p-value of one-tail estimate was 0.195 and greater than 0.05 of the rejection
probabilities that further confirmed the weak form of EMH.
Table 5: The consequences of T- test
t-Test: Paired Two Sample for Means
Portfolio ASX
Mean
0.04795
1
0.00154
2
Variance 0.17111
0.00107
4
Observations 59 59

Pearson Correlation -0.0687
Hypothesized Mean
Difference 0
df 58
t Stat
0.85447
5
P(T<=t) one-tail
0.19817
9
t Critical one-tail
1.67155
3
P(T<=t) two-tail
0.39635
7
t Critical two-tail
2.00171
7
The findings
The study showed that ASI of ASX was the weak form efficient through t-test. In the
Australian equity markets of stock, the ASI as a weak structure was determined by performing
tests, automated reports, and unit root tests, while the volatility ratio test showed the specific
result (Patel, Radadia, & Dhawan, 2012). Be that as it may, Cheung and Coutts (2011) came to
similar conclusions to a tax structure demonstrating the effectiveness of ASI by attempting to
modify the relationship with heteroskedastic and homoskedastic error differences that would
explain the validity of the results in this study. Explain why the two are unique. the results were
that the success used daily information while the success used information over five years,
according to which lines the recurrence and duration of the selected information affect the
potential output of the market.
As pointed out by Milburn (2008), the relevant validated data was similar to the current
cost of inventory and the past cost of protection could estimate future unstructured market costs.
Similarly to these lines, it showed that it was difficult to quantify the information gathered by the
Australian Securities Index and its constituent entities in order to quantify future costs in the
current type of market productivity.

PART B
Introduction
Goodman Group is an integrated industrial property group. The Group has operations in
Australia, New Zealand, UK, Asia and Europe. Goodman's activities include property
investment, funds management, property development and property services. The Group's
property portfolio includes business parks, industrial estates, office parks and
warehouse/distribution centers. It is one of the biggest recorded master finance administrators of
modern property and business space all inclusive, with around $43 billion in resources under
administration. It has a group of around 900 individuals in 29 workplaces worldwide all through
Australia, New Zealand, Asia, Europe, the United Kingdom, North America and Brazil.
Goodman’s compensation system ensures that the agreement between fixed compensation
and performance-based compensation is adequate for the prices incurred by the Holders; that is,
the practical development of long-range EPS and, ultimately, risk outcome. Our show usually
touches the holders of titles and colleagues of Goodman, with the Guardians ’biases met before
strong-strength transition grants or long-term incentives are paid. There is a particular emphasis
on long-term motivational forces for all colleagues, who are at risk with a three-year
probationary period and a maturity over three to five years.
Strong customer searches gather every year, and company has expanded work to $ 3.6
billion across 80 businesses in 12 countries. In essence, most of the development work is in
partnerships, leading to the organization of potential capital for Goodman and a better outcome
for partners. Goodman Partnerships continued to operate consistently, with an average yield of
15% for its partners this year. Similarly, outsourced external resources increased to $ 35.1
billion. This was driven by $ 2.8 billion in revaluation earnings and $ 3.5 billion in customer
development in the Group and in partnerships.
As shown in Table 6, the cash conversion cycle of 2014 and 2015 were gently and the
lowest value reached -183 in 2015. From this year to 2018, the CCC was a steady downward
trend and the highest value was -109 in 2018. Real estate companies usually operated in the form
of providing services to customers after they had paid for them (Pezhman, Javadi, & Shahin,
2013). Therefore, the negative CCC of GMG showed a favorable level of working capital
management during the 5 years period.