Analysis of Virgin & Qantas Annual Reports

This report analyzes the financial health of Virgin Australia and Qantas Airways using the Altman Z-Score model. The analysis involves calculating the Z-score for both airlines for 2015 and 2016 using data extracted from their annual reports. The calculations include key financial ratios such as working capital to total assets, retained earnings to total assets, EBIT to total assets, market value of equity to book value of total liabilities, and sales to total assets. The results show that Qantas had Z-scores above 3 in both years, indicating a low risk of bankruptcy, while Virgin Australia's Z-scores were below 1.8, suggesting a high risk of financial distress. The report also discusses earnings management and its potential impact on the accuracy of the Altman Z-Score model. It explains how earnings management techniques, such as capitalizing expenses, can distort the financial ratios used in the model, leading to inaccurate predictions of financial distress. The report concludes by highlighting the limitations of the Altman Z-Score model and emphasizes the importance of considering other factors in assessing a company's financial health.

Analysis of Virgin Australia and Qantas
Annual Reports applying Altman Z-Score
model
Assessment Task 1
Student Name: Student ID
Subject Name: Subject ID:
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Table of Contents
Answer to Question No 1:...............................................................................................................3
Answer to Question No 2................................................................................................................9
Reference List................................................................................................................................12
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Answer to Question No 1:
Qantas Altman Z-Score:
Heads 2015 2016
Net Working Capital (CA-CL) (2421) (3570)
Total Assets 17,530 16,705
Total Current Assets 5,049 3,458
Total Current Liabilities 7470 7028
EBIT 1,233 1,751
Retained Earning (1,146) (175)
Market Value of Equity 55778.4 102900.2
Book Value of Total
Liabilities
11356 10185
Sales or Revenue 15,816 16,200
Qantas 2015 Altman Z-Score:
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X1= Total Working Capital/Total Assets
X1= (Total Current Assets-Total Current Liabilities)/Total Assets
X1= -0.138
X2= Retained Earnings/ Total Assets
X2= -0.065
X3= EBIT/ Total Assets
X3= 0.070
X4=Market Value Equity/Book Value of Total Liabilities
X4= 4.911
X5= Revenue /Total Assets
X5= 0.902
Z= 1.2 (X1) + 1.4(X2)+ 3.3(X3) + 0.6(X4) + 1.0 (X5)
Z=1.2*20,276 + 1.4*(1,146) + 3.3*1,751 + 0.6*16,849 + 1.0*7,966
Z= 3.823
Qantas 2016 Altman Z-Score:
X1= Total Working Capital/Total Assets
X1= (Total Current Assets-Total Current Liabilities)/Total Assets
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X1= -0.213
X2= Retained Earnings/ Total Assets
X2=-0.010
X3= EBIT/ Total Assets
X3=0.104
X4=Market Value Equity/Book Value of Total Liabilities
X4= 10.10
X5= Revenue /Total Assets
X5=0.969
Z= 1.2 (X1) + 1.4(X2)+ 3.3(X3) + 0.6(X4) + 1.0 (X5)
Z= 6.9766
Heads 2015 2016
X1 -0.138 -0.213
X2 -0.065 -0.010
X3 0.070 0.104
X4 4.911 10.10
X5 0.902 0.969
Altman’s Z-Score 3.823 6.9766
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Virgin Altman’s Z-Score:
Heads 2015 2016
Net Working Capital (713.8) (1066.1)
Total Assets 5,779.6 6,040.8
EBIT 65.9 210.6
Market Value of Equity 1511.526 741.468
Book Value of Total
Liabilities
4758.8 5142
Sales or Revenue 4749.2 5021
Retained Earnings (253.6) (514.5)
Virgin 2015 Altman Z-Score:
X1= Total Working Capital/Total Assets
X1= -0.123
X2= Retained Earnings/ Total Assets
X2=-0.043
X3= EBIT/ Total Assets
X3=0.011
X4=Market Value Equity/Book Value of Total Liabilities
X4=0.317
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X5= Revenue /Total Assets
X5=0.821
Z= 1.2* (0.123) + 1.4*(0.043)+ 3.3*0.011 + 0.6*0.317 + 1.0*0.821
Z= 0.8397
Virgin 2016 Altman Z-Score:
X1= Total Working Capital/Total Assets
X1=(Total Current Assets-Total Current Liabilities)/Total Assets
X1=-0.176
X2= Retained Earnings/ Total Assets
X2=-0.085
X3= EBIT/ Total Assets
X3=0.034
X4=Market Value Equity/Book Value of Total Liabilities
X4=0.144
X5= Revenue /Total Assets
X5=0.831
Z= 1.2*(0.176) + 1.4*(0.085)+ 3.3*0.034+ 0.6*0.144+ 1.0*0.831
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Z=0.6994\
Heads 2015 2016
X1 -0.123 -0.176
X2 -0.043 -0.085
X3 0.011 0.034
X4 0.317 0.144
X5 0.821 0.831
Altman’s Z-Score 0.8397 0.6994
The analysis of the financial figures of Qantas and Virgin Airlines with the help of
Altman’s Z-Score model has revealed that Qantas Airlines has a value of 3.823 in the year 2015
and 6.9766 in the year 2016 revealing the company will not go bankrupt and has not been facing
any financial distress and investors would be attracted to purchase their stock. On the other hand,
Virgin has shown the Altman Z-Score model has a value of 0.8397 in the year 2015 and 0.6994
in the year 2016. The values are lower than 1.8 and therefore Virgin is facing financial distress
and requires undertaking changes in their financial policies so that they can prevent the company
from getting bankrupt. Hence, Virgin Airlines is facing financial distress and Qantas is having
sufficient financial condition.
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Answer to Question No 2
Earnings management is a general phenomenon in the construction of the financial
statements or disclosure of the information related to earnings. The intention for earnings
management is to exhibit sensible income quality that meets either the investors' desire or, on the
other hand the prerequisite of getting pertinent approval from the regulators. Consequently,
earnings management has much in similarity with respect to the profit quality that are inclusive
of the earnings persistence, predictability of the earnings, quality of the accruals and the
smoothness of the earnings (Haislip, & Richardson 2015). It is seen that increasingly handled
earnings can lead to the low earnings quality as the information that is artificial in nature may
lead to inaccurate decisions. On the other hand, the nonexistence of the earnings management is
not sufficient to make sure of the higher level of quality earnings, due to the fact that the other
factors like the management compensation and capital market may add in to the earnings quality.
The Altman Z-score model is a mixture of the five weighted ratios of business that is
utilized to predict the chances of the financial distress. The model comprises of evaluating the
financial statements of the organizations and with the help of which this Z-Score model can
establish a score value that would indicate whether the company is facing any financial distress
or not. The general value that is considered in this model has been found to be 3 and any value
that is close to the value of 3 would indicate that the company is not facing any financial distress
and has been facing profit (Altman et al., 2015). Any figure higher than 3 is a positive display for
the organization revealing that the company can expand and is earning adequate profit. On the
other hand, any value that is lower than 1.8 suggests that the company has been facing massive
issues related to the operational and financial aspects and therefore may face financial distress or
even bankruptcy. The Altman Z-score model has even created a various zones and each of the
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zones is placed according to the scores that the organizations score (Altman et al., 2014). It has
been observed that a company with a value of more than 2.99 is placed in the safe zone that
indicates that the company is safe. Any company that is in between the value of 1.88 to 2.99 is
within the grey zone, which indicates that the organization has a good chance of facing a
financial distress or even going bankrupt within the next years of its business (Villar et al.,
2014). The company that has a value below 1.88 is positioned in the distress zone, which
indicates that there exists an increased probability that the company would face distress during
the upcoming period of time.
It has been observed that under certain conditions, the management of the may become
incentivized to engage in earnings management, which means undertaking measures to increase
earnings or the profit and to capitalize expenses. In such cases, the Altman Z-score model faces a
significant impact as it is seen that the model computes the data based on the financial statements
that are available from the annual report of the organization (Biddle et al., 2016). This model
considers making use of the total assets, current liabilities, current assets, and market value of the
equity, book value of the total liabilities, earnings before income and tax, revenue of the
company and the retained earnings. If the management of the organization looks to capitalize
their expenses, it means they are in the attitude of delaying the identification of the expenses by
recording the expenditure as an asset that is long term in nature (Guan et al., 2016). It has been
observed that capitalizing the expenses is an advantageous process as the organizations that are
purchasing new assets with a longer period of life have the advantage of distributing their cost.
However, it has been observed that in case of Altman’s Z-score model, such policies may not be
fruitful because during the computation of the model, the current as well as the total liabilities
are considered. The model even makes use of market value of the equity as well as the retained
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earnings, book value of the total liabilities and sales. The capitalization of the expenses would
mean that the expenses are not recorded in the current books of account and in a way may have
an impact on the actual sales and the total liabilities. The changes in the value of these figures
can imperatively change value that would be attained from the Altman’s Z-score model that may
lead to inaccurate distribution of the results (Almamy et al., 2016). The Z-score does not have
the intention of estimating when the company will file for the bankruptcy. It is a process of
computing how relatively a company resembles another company who has filed for bankruptcy.
This process looks to predict the likelihood of the bankruptcy. It has even observed that
this model make use of unadjusted accounting data and therefore the results that would be
attained from this model will be way different from the financial statements that have been
prepared by the organizations and in a way would a disclose a difference thereby creating a
confusion among the stakeholders. The stakeholders may not be sure about the effectiveness of
the Altman results and may be reluctant in understanding the financial distress figures as
indicated by the model (Altman et al., 2017). Therefore, it can be said that making use of the
earnings management by capitalizing the expenses during certain situations can lead to incorrect
results of the Altman score thereby confusing the management of the organizations to come to a
decision whether the company would face any financial distress or bankruptcy. Even though
there are such issues related to this model, the organizations make use of it in order to assess the
financial distress of the organizations.
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Reference List
Almamy, J., Aston, J., & Ngwa, L. N. (2016). An evaluation of Altman's Z-score using cash flow
ratio to predict corporate failure amid the recent financial crisis: Evidence from the
UK. Journal of Corporate Finance, 36, 278-285.
Altman, E. I., Danovi, A., & Falini, A. (2015). Z-Score Models' application to Italian companies
subject to extraordinary administration.
Altman, E. I., Iwanicz-Drozdowska, M., Laitinen, E. K., & Suvas, A. (2014). Distressed Firm
and Bankruptcy Prediction in an International Context: A Review and Empirical Analysis
of Altman's Z-Score Model.
Altman, E. I., Iwanicz‐Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial Distress
Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐
Score Model. Journal of International Financial Management & Accounting, 28(2), 131-
171.
Biddle, G. C., Ma, M. L., & Song, F. M. (2016). Accounting conservatism and bankruptcy risk.
Guan, Y., Su, L. N., Wu, D., & Yang, Z. (2016). Do school ties between auditors and client
executives influence audit outcomes?. Journal of accounting and economics, 61(2), 506-
525.
Haislip, J. Z., & Richardson, V. J. (2015). The Effect of CEO IT Expertise on the Information
Environment: Evidence from Earnings Forecasts and Announcements.
Villar, J., Ismail, L. C., Victora, C. G., Ohuma, E. O., Bertino, E., Altman, D. G., ... & Gravett,
M. G. (2014). International standards for newborn weight, length, and head
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