This is not the document you are looking for? Use the search form below to find more!

0.00 (0 votes)

Many potential lenders use credit scoring models to assess the creditworthiness of prospective borrowers. The general idea is to ﬁ nd factors that enable the lenders to discriminate be-
tween good and bad credit risks. To put it more precisely, lenders want to identify attributes of the borrower that can be used to predict default or bankruptcy.
Edward Altman has developed a model using ﬁ nancial statement ratios and multiple discriminant analyses to predict bankruptcy for publicly traded manufacturing ﬁ rms. There sultant model is of the form EBIT

- Added:
**October, 07th 2010** - Reads:
**408** - Downloads:
**3** - File size:
**113.08kb** - Pages:
**2** - content preview

- Name:
**matteo**

Related Documents

This paper discusses two of the venerable models for assessing the distress of industrial corporations. These are the so-called Z-Score model (1968) and ZETA® 1977) credit risk model. Both ...

A z-score (aka, a standard score) indicates how many standard deviations an element is from the mean. A z-score can be calculated from the following formula. z = (X - μ) / σ where z is the ...

Use this chart to find the area under a normal curve when finding An approximation for a binomial distribution. Negative z-score - value is to the left of the mean. Positive z-score - value is to the ...

Definition of the Standard Normal Distribution The Standard Normal distribution follows a normal distribution and has mean 0 and standard deviation 1 Notice that the distribution is perfectly ...

1. The mean test score of students is 80 and the standard is 10, the probability that a student gets? A. Between 60 C. Less than 60 B. And 85 in the testAnd > 85 in the test D. None 2. Calculate the ...

Solution Manuals and Test Banks I have huge collection of solution manuals and test banks. I strive to provide you unbeatable prices with excellent support. So, I assure you that you won’t be ...

DogTown: The Legend of the Z-Boys by Glen E. Friedman A Hit At Christmas! In the early 1970s, the sport of skateboarding had so waned from its ...

Needle Park what can we learn from the Zürich experience

To understand Least Common multiple we have to understand about multiple first. When we can get a number by multiplication of certain combinations of other numbers, the numbers multiplied are called ...

This study's underlying premise is that current pension plan accounting has two important negative effects. First, it distorts the measurement of earnings and net worth in the short run, as well as ...

Content Preview

Appendix 30A Predicting Corporate Bankruptcy:

The Z-Score Model1

Many potential lenders use credit scoring models to assess the creditworthiness of prospec-

tive borrowers. The general idea is to ﬁ nd factors that enable the lenders to discriminate be-

tween good and bad credit risks. To put it more precisely, lenders want to identify attributes

of the borrower that can be used to predict default or bankruptcy.

Edward Altman has developed a model using ﬁ nancial statement ratios and multiple

discriminant analyses to predict bankruptcy for publicly traded manufacturing ﬁ rms. The

resultant model is of the form

EBIT

New working capital

Z 3.3

__________

_________________

1.2

Total assets

Total assets

Sales

Market value of equity

1.0

__________

___________________

.6

Total assets

Book value of debt

Accumulated retained earnings

1.4

__________________________

Total assets

where Z is an index of bankruptcy.

.com/rwj

A score of Z less than 2.675 indicates that a ﬁ rm has a 95 percent chance of becoming

bankrupt within one year. However, Altman’s results show that in practice scores between

.mhhe

1.81 and 2.99 should be thought of as a gray area. In actual use, bankruptcy would be pre-

dicted if Z 1.81 and nonbankruptcy if Z 2.99. Altman shows that bankrupt ﬁ rms and

nonbankrupt ﬁ rms have very different ﬁ nancial proﬁ les one year before bankruptcy. These

different ﬁ nancial proﬁ ts are the key intuition behind the Z-score model and are depicted in

Table 30A.1.

visit us at www

Net working capital

_________________

6.1%

41.4%

Total assets

Accumulated retained earnings

__________________________

62.6%

35.5%

Total assets

EBIT

__________

31.8%

15.4%

Total assets

Market value of equity

___________________

40.1%

247.7%

Total liabilities

Sales

______

150%

190%

Assets

SOURCE: Edward I. Altman,

1993),Table 3.1, p. 109.

1Edward I. Altman,

ros05902_ch30(appendix).indd 849

ros05902_ch30(appendix).indd 849

6/21/06 12:28:04 PM

6/21/06 12:28:04 PM

Altman’s

original

a manufacturer. He uses a revised model to make it applicable for private ﬁ rms and non-

manufacturers. The resulting model is this:

Net working capital

Accumulated retained earnings

__________________________

________________

3.26

Total assets

Total assets

Book value of equity

EBIT

1.05

__________

_________________

6.72

Total assets

Total liabilities

where Z 1.23 indicates a bankruptcy prediction,

1.23 Z 2.90 indicates a gray area,

and Z 2.90 indicates no bankruptcy.

U.S. Composite Corporation is attempting to increase its line of credit with First National State

Bank. The director of credit management of First National State Bank uses the Z-score model to de-

termine creditworthiness. U.S. Composite Corporation is not a publicly traded ﬁ rm, so the revised

Z-score model must be used.

The balance sheet and income statement of U.S. Composite Corporation are in Tables 2.1 and

2.2 (Chapter 2).

The ﬁ rst step is to determine the value of each of the ﬁ nancial statement variables and apply

them in the revised Z-score model:

.com/rwj

(in millions)

Net working capital

275

_________________

_____

0.146

.mhhe

Total assets

1,879

Accumulated retained earnings

390

__________________________

_____

0.208

Total assets

1,879

EBIT

219

__________

_____

0.117

Total assets

1,879

Book value of equity

805

_________________

____

1.369

Visit us at www

Total liabilities

588

The next step is to calculate the revised Z-score:

10.96

Finally we determine that the Z-score is above 2.9, and we conclude that U.S. Composite is a good

credit risk.

ros05902_ch30(appendix).indd 850

ros05902_ch30(appendix).indd 850

6/21/06 12:28:05 PM

6/21/06 12:28:05 PM

## Add New Comment