Application and Comparison of Altman and Ohlson Models to Predict Bankruptcy of Companies

This study examines the application of Altman and Ohlson models to predict bankruptcy of companies. It focuses on companies from Tehran Stock Exchange and analyzes their financial statements using these models. The goal is to evaluate the prediction power of these models and compare their effectiveness.

Research Journal of Applied Sciences, Engineering and Technology 5(6): 2007-2011, 2013
ISSN: 2040-7459; e-ISSN: 2040-7467
© Maxwell Scientific Organization, 2013
Submitted: July 20, 2012 Accepted: September 08, 2012 Published: February 21, 2013
2007
Application and Comparison of Altman and Ohlson Models to Predict
Bankruptcy of Companies
Mani Shehni Karamzadeh
Multimedia Universiti, Faculty of Management, Malaysia
Abstract: Environment fluctuation and increasing competitiveness between corporations lead to make the
achievement of proper benefit more difficult. Therefore, financial decision making received more attention compare
to past few decades and it forces managers to apply novel techniques and methods in order to make excellent
decisions. This study tries to investigate the application of Altman and Ohlson models as two of these techniques.
To achieve this goal companies from Tehran Stock Exchange are chosen because there are standard financial
statements for corporations in Tehran Stock Exchange and also the data is accessible.
Keywords: Altman model, bankruptcy, Ohlson model, Tehran stock exchange
INTRODUCTION
The most important and vital issues in financial
management are investing and trust to investors for
both real persons and legal persons in different levels of
any business. A large number of studies about process
of decision making in investment have been conducted
in developed countries (Chen et al., 2009). One of
issues that could help organizations in order to have a
superior decision making in their investment positions
is using tools and models for evaluating financial
situation of organizations. Because the investors cannot
make a correct decision unless has a proper evaluation
from its investment. One of these tools that used in
corporations for decision making in their investments
are models of bankruptcy prediction (Beaver, 1966).
Investors always intend to predict the possibility of
bankruptcy of corporations and prevent to the risk of
losing their investment. Hence, they are always looking
for methods that could predict the possibility of
bankruptcy of companies. Because in a case of
bankruptcy the stock price decreases dramatically.
There are a variety of methods for predicting the
bankruptcy but some of them are more famous and
well-established. Therefore, based on the literature,
between these methods, analysis of ratios and analysis
of market risk are more valid. Analysis of market risk
uses fluctuations in the market risk (such as variance of
Rate of Return for a share and systematic risk) in order
to estimate the possibility of bankruptcy of corporation.
On the other hand, analysis of ratios estimates the
possibility of bankruptcy by using a group of financial
ratios that is chosen by experts.
The main goal of this study is to examine the
prediction power of original Altman (1968) and Ohlson
(1980) models on the dataset of Iranian listed
companies. In the Altman model (Z-score) for
bankruptcy prediction analysis of ratios method is used.
The model consists of five financial ratios that are
coefficients by Discriminate Analysis Method and has
been implemented as a function that financial ratios are
as independent variables of it. Ohlson was a pioneer in
introducing legit function to bankruptcy prediction in
1980 and a follow-up study was conducted by
Zmijewski (1984) that is the first application of probity
function.
Bankruptcy: Bankruptcy is a legal status of an
insolvent person or an organization, that is, the one who
cannot repay the debts that owes to creditors. In most
jurisdictions, bankruptcy is imposed by a court order,
often initiated by the debtor. When the amount of
organization debts is higher than its value of existence
assets bankruptcy is occurred (Gitman, 1996).
In Tehran Stock Exchange (TSE) Article, 141
Commercial Code states about the situation that a
corporation count as a bankrupt corporation. This law
says: If an organization looses at least half of its assets
it is compulsory for Board of Director's to make an
appointment and make a decision about the future of
their corporation, whether they are going to decide to
disbandment, the corporation or continue their activities
(Soleimani et al., 2003).
Generally, bankruptcy in corporations could
happen in three different ways: financial, economical
and legal (Chen et al., 2009). In case of financial
bankruptcy, corporation is not able to do its obligations
before the deadline. Hence, it shows weaknesses in
finance. One of the clues of financial weaknesses is
absence of working capital. Lacks of working capital,

Res. J. Appl. Sci. Eng. Technol., 5(6): 2007-2011, 2013
2008
which itself is a sign that causes of weak capital
structure by over current borrowing, high operational
costs and other causes. Usually economic bankruptcy
and financial and credit bankruptcy are different.
Overall, economic bankruptcy is same as failure of
trade, because the corporations could not achieve the
same benefit that can be achieved elsewhere
(Shumway, 2001). Based on laws, bankruptcy is not
defined as inability of a company in payment of its
obligations before the deadline. Regulations define the
bankruptcy when the total assets are not sufficient to
pay the total debt (Gholampour, 2009).
Bankruptcy usually caused by different reasons.
One of the most important reasons in bankruptcy of
corporations is mismanagement. The managerial
failures, high costs, financial activities weakness,
ineffective sales activities and high production costs or
mixture of these reasons can be a warning for a
company for bankruptcy. Economic activities could be
the other reason of bankruptcy in organizations and
corporations. Economic recession, changes in interest
rates, rising inflation, raw material price fluctuations
and international economic conditions, can be
mentioned as economic reasons for bankruptcy of
organizations. On the other hand, government
decisions, natural and unwanted hazards and life-stage
of organizations are also other reasons for the
occurrence of bankruptcy (Goudie, 1987).
LITERATURE REVIEW
The first study in the field of bankruptcy prediction
is conducted by Thomas Woodlock in early 1939. He
was done a classic analysis in railway industry and
published his work as an article under the name of
“Percentage of operational costs to gross retained
earnings” (Agarwal et al., 2007). Edward Altman
(1968) (in an article on financial ratios, discriminate
analysis and bankruptcy prediction of institutions)
presented a model for bankruptcy prediction, which is
known as the Altman’s Model. He implemented five
financial ratios in this model whose accuracy was 95%.
A few years later that, he introduced a modified version
of his model called Z-score model. The Z-score model
is still applied as a general practical tool for assessing
the financial well-being of firms. Due to its
characteristics, this model has been used for small
samples of manufacturing firms as well as bankrupt and
non-bankrupt firms with equal sizes (Grice and Ingram,
2001).
Altman selected 22 financial ratios and analyzed
them by using multiple discriminate analysis method;
he could produce the function Z which contained 5
financial ratios as independent variables and Z as
dependent variable. Financial ratios in this model are as
follows:
 Working capital to total assets
 Retained earnings to total assets
 Earnings before interest and taxes to total assets
 Market value of equity to total debt
 Sales to total assets (Duffie et al., 2003)
After years of using model Z by researchers and
different organizations, some criticisms were raised for
the model. Financial analysts, accountants and even the
companies believed that this model can be used only for
institutions with a general business nature. Altman
continued its research on bankruptcy prediction and
improve its model and presented a new model, called
model Z.
The most important amendment in Altman model
is substituting equity book value and the market value
and then changes the coefficients and limitations of
bankruptcy. These two models were used mainly on
manufacturing companies, usage of these models in
non-manufacturing and service companies were not
significant. Therefore, Altman continued his research to
design a model named Model Z, in these model sales to
total assets ratio variable is eliminated and the four-
variable model provided specifically for non-
manufacturing and service companies (Philosophov and
Philosophov, 2002). In later years, many researchers
study on bankruptcy prediction models and were able to
design new models. Such as: the legit model by Ohlson
(1980). Ohlson raised questions about the MDA model,
particularly regarding the restrictive statistical
requirements imposed by the model (Ohlson, 1980). To
overcome the limitations, Ohlson (1980) employed
logistic regression to predict company failure.
Some of the studies carried out on bankruptcy
prediction models in Iran are as follows: Mehrani et al.
(2005) studied the relationship between financial ratios
and bankruptcy prediction. To examine research
hypothesis and compute the financial ratios of interest
from sample firms, the data related to one and two
years before success or failure (bankruptcy) was
collected for each participant group-successful and
unsuccessful firms and the main research variables
were computed including five financial ratios. The
results of data analysis revealed that the obtained Z-
score model correctly separated the sample firms and
classified them in one of the successful or failed
(bankrupt) groups without any error, indicating the
ability of financial ratios in predicting success or failure
(Mehrani et al., 2005).
RESEARCH METHODOLOGY
In this study, using data extracted from financial
statements of listed companies in Tehran Stock
Exchange (TSE), the ratios calculated in the model and
it’s applying in the model, then the amount of Altman
model for each company in each year of study is

Res. J. Appl. Sci. Eng. Technol., 5(6): 2007-2011, 2013
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determined. Statistical population of this study includes
the companies in Tehran Stock Exchange which are a
total of 90 companies. This study used data for a 4 year
period from 2007 to 2010.
Altman model: Altman (1968) employs Multivariate
Discriminate Analysis (MDA) on a list of financial
ratios to identify those ratios that are statistically
associated with future bankruptcy. Ohlson (1980) uses a
legit model, which uses less restrictive assumptions
than those taken by the MDA approach. Zmijewski
(1984) adopts a probity approach that is also based on
accounting data but uses a different set of independent
variables. All of these approaches predict future
bankruptcy based on accounting ratios drawn from
firm’s financial statements.
The Z-score formula for predicting bankruptcy was
published in 1968 by Edward I. The formula may be
used to predict the probability that a firm will go into
bankruptcy within two years. Z-scores are used to
predict corporate defaults and an easy-to-calculate
control measure for the financial distress status of
companies in academic studies. The Z-score uses
multiple corporate income and balance sheet values to
measure the financial health of a company. In this study
Z’-SCORE model of Altman is used. This model
contains five financial ratios: Working capital to total
assets (T1), Retained earnings to total assets (T2),
Earnings before interest and taxes to total assets (T3),
Book value of equity to book value of debt (T 4), Sales
to total assets (T5). The model is shown in Eq. (1):
Z’ = 0.717(T1) + 0.847 (T2) + 3.1 (T3)
+ 0.42 (T4) + 0.998 (T5) (1)
 Z<1.2 State of complete bankruptcy
 State of between bankruptcy and non bankruptcy
(Grey zone)
 Z≥2.9 State of perfect situation
Ohlson model: The econometric methodology of
logistic analysis was chosen. The dependent variable is
binomial and is defined as 1 if the firm is delisted and 0
if the firm is non‐delisted firm. The same nine
independent variables used by Ohlson (1980) are
employed. The definitions of the nine independent
variables are as follows:
SIZE = Log (total assets/GNP price‐level index).
The index assumes a base value of 100 for
2003. The index year is as of the year
prior to the year of the balance sheet date
TLTA = Total liabilities divided by total assets
WCTA = Working capital divided by total assets
CLCA = Current liabilities divided by current
assets
OENEG = One if total liabilities exceeds total assets,
zero otherwise
NITA = Net income divided by total assets
FUTL = Funds provided by operations divided by
total liabilities
INTWO = One if net income was negative for the
last two years, zero otherwise
CHIN = (NIt‐NIt‐1)/ (│NIt│+│NIt‐1│), where NIt
is net income for the most recent period
The denominator acts as a level indicator. The
variable is thus intended to measure change in net
income:
zi = -1.32 - 0.407x1 - 6.03x2 - 1.43x3 - 0.0757x4 -
2.37x5 - 1.83x6 - 0.285x7 - 1.72x8 - 0.521x9 (2)
Consistent with Ohlson, three sets of estimates
were computed for the logistic model using the
predictors previously described.
RESULT ANALYSIS
The sample is composed of 90 corporations with
45 firms in each of the two groups. The bankrupt group
(group 1) is listed companies of Iran Stock Exchange
that as per the Article No. 141 of Iran Commerce Code,
their Retained Loss is more than twice of their capital.
The second group (group 2) consists of a paired sample
of listed firms chosen on a stratified random basis from
the same database of Iran Stock Exchange.
With finding amount of variables and calculating
the amount of ‘Z and Ohlson model, Type I error rate
(company is bankrupt, but it is predicted non-bankrupt
companies) and type II errors (company is Non-
bankrupt, but it is predicted as a bankrupt company) for
each model is determined. Figure 1 shows a comparison
of Altman model and Ohlson model regard with their
accuracy in bankruptcy prediction.
Summary of examination of Altman bankruptcy
prediction model for 1, 2 and 3 years before has been
Fig. 1: A comparison of accuracy of Altman and Ohlson
models
0
10
20
30
40
50
60
70
80
One year before Two years before Three years before
Altman model
Ohlson model

Res. J. Appl. Sci. Eng. Technol., 5(6): 2007-2011, 2013
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Table 1: Results of Altman model for 1, 2 and 3 years before
Year
Actual
-------------------------------------------------
Predicted
--------------------------------------------------------
Accuracy
-------------------------------
Group 1 Group 2 Total
Group 1
(bankrupt)
Group 2
(non-bankrupt)
Gray zone
(critical)
Number
correct
Percent
correct
One year before 45 45 90 32 35 23 67 74.4
Two year before 45 45 90 28 30 32 58 64.4
Three year before 45 45 90 19 26 45 45 50
Total 135 135 270 89 91 100
Table 2: Results of Ohlson model for 1, 2 and 3 years before
Year
Actual
-------------------------------------------------
Predicted
--------------------------------------------------------
Accuracy
-------------------------------
Group 1 Group 2 Total
Group 1
(bankrupt)
Group 2
(non-bankrupt)
Gray zone
(critical)
Number
correct
Percent
correct
One year before 45 45 90 20 28 0 48 53.3
Two year before 45 45 90 19 23 0 42 46.6
Three year before 45 45 90 12 18 0 30 33.3
Total 135 135 270 51 69 0
Fig. 2: Results of Altman model for 1, 2 and 3 years before
Fig. 3: Results of Ohlson model for 1, 2 and 3 years before
presented in Table 1. Table 1 shows Altman model in
on year before is more accurate compare to two or three
years before. Therefore, the most accurate prediction is
for one year before with 74.4% of correct predictions
and the worse one is 3 year before with 50%. Summary
of examination of Ohlson bankruptcy prediction model
for the past 1, 2 and 3 years has been presented in
Table 2.
As Table 2 shows none of the predictions are in the
grey area. Figure 2 demonstrates the results of Altman
model for one, two and three years before. Accordingly,
Fig. 3 depicts the results for Ohlson model for one, two
and three years before. As is mentioned in Table 2 there
is no records for gray zone.
CONCLUSION
Considering the results original Altman (1968)
bankruptcy prediction model, without any modification
made in the independent variables and coefficients, can
predict bankruptcy issue of Iranian listed companies
with the accuracy of 74.4, 64.4 and 50%, respectively
for 1, 2 and 3 years before and original Ohlson (1980)
bankruptcy prediction model, without any modification
made in the independent variables and coefficients, can
predict bankruptcy issue of Iranian listed companies
with the accuracy of 53.3, 46.6 and 33.3%, respectively
for 1, 2 and 3 years before. A comparison between
Altman and Ohlson model shows in all three situations
Altman works better and it could be suggested to
investors in order to predict bankruptcy of companies.
For further research other bankruptcy prediction models
can be applied and compare the results and also
application of Neural network models is suggested for
future research.
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