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Study of relationship between delisting of Companies
and bankruptcy as indicated by Altman Z Score
Presented by
Anrag Kumar Tiwari
Enrol- 15BSP0213
IBS Business School
Objective & Methodology of the paper
 Primary objective: - To predict the financial health and
viability of the company using “Z” Score model
 Secondary objective: - To analyze the financial
condition of few selected to know the efficiency in
financial operations of the company. To offer suitable
suggestions.
Need and Scope for the study
 The primary need of the study is to analyze the financial health of
the company and to identify the signs of financial distress and
thereby avoid the Bankruptcy.
 The scope of the study is limited to 5 years financial performance
only.
 This study help company improve the financial health and
performance of the business.
Introduction
 There are various tools to measure the company performance.
 Like- Ratio Analysis, RSI Calculation, DuPont Analysis, and EFQM
Excellence Model Each of them use specific technics to measure the company
profit, liquidity, and efficiency. But none of them is able to accurately predict
overall performance of success trend.
 Dopant Analysis
The return on assets (ROA) ratio developed by DuPont for its own use is now
used by many firms to evaluate how effectively assets are used. It measures
the combined effects of profit margins and asset turnover.
Cont.…
 EFQM excellence model
EFQM Excellence Model provides a holistic view of the
organization and it can be used to determine how these different
methods fit together and complement each other.
The Model can therefore be used in conjunction with any number
of these tools, based on the needs and function of the
organization, as an overarching framework for developing
sustainable excellence.
This tools cannot predict whether the particular
company is going towards bankruptcy.
Altman Z-Score
 The Altman Z-score is the output of a credit-strength test that gauges a
publicly traded manufacturing company's likelihood of bankruptcy. The
Altman Z-score, is based on five financial Ratio.
 The Z-score Formula
Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E
Where,
A = Working Capital/Total Assets
B = Retained Earnings/Total Assets
C = Earnings before Interest & Tax/Total Assets
D = Market Value of Equity/Total Liabilities
E = Sales/Total Assets
Zones of Discrimination:
 Z > 2.99 -“Safe” Zone
 1.81 < Z < 2.99 -“Gray” Zone
 Z < 1.81 -“Distress” Zone
The sample of the 10 Company
Company applied for de-listed Year Company applied for de-listed Year
Max Financial Service 2016 Punj lloyad Ltd. 2016
India Cements 2016 SQL Star International 2016
Hexaware Technologies 2016 Cable Corporation of India 2016
Circuit System 2016 Piramal Glass 2016
Educomp Solution 2016 Hexaware Technologies 2016
Altman Z-Score Calculation
S.N
Company Name
Year's
2015 2014 2013 2012 2011
1Max Financial Service 5.093618 2.875133 3.755659 2.470703 2.345724
2India Cements 1.147843 0.929259 1.163262 1.339966 1.01213
3Hexaware Technologies 9.260657 5.143688 5.132221 5.132221 2.570922
4Circuit System 4.910066 2.78405 1.991317 2.156579 1.864063
5Educomp Solution 0.026086 0.755868 1.312634 2.321558 4.193494
6Punj lloyad Ltd. 1.455609 2.020699 2.319751 2.099082 2.135202
7SQL Star International -16.1122 5.790945 5.15904 -0.86034 7.755316
8Cable Corporation of India 0.20232 2.726337 3.335721 2.956767 3.352931
9Piramal Glass 5.370194 4.329741 5.88315 6.909085 5.849679
10Manjushree Technipark 5.426089 5.319517 4.816005 5.199257 4.437346
CONCLUSION AND RECOMMENDATION
 As our conclusion, we have identified some issues based on our
findings. Firstly, Altman Z-score is mostly designated for
manufacturing firms, and therefore, firms from other industries
may not match with the model. Secondly, external factors like
economic conditions, seasonality of sales, company size,
geographical location and pre-bankruptcy non-financial events
are yet to be included in Altman’s Z-score during bankruptcy
prediction. Thirdly, Altman Z-score only uses past financial data,
which is difficult for projecting the future value of firms. Lastly,
as Altman’s Z-score solely depends on the past financial data, it
may confront with window dressing
Sources
 www.moneycontrol.com
 www.bse.com
 www.yahoo.finance.com
Thank
you

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researsh on Altman Zscore

  • 1. Study of relationship between delisting of Companies and bankruptcy as indicated by Altman Z Score Presented by Anrag Kumar Tiwari Enrol- 15BSP0213 IBS Business School
  • 2. Objective & Methodology of the paper  Primary objective: - To predict the financial health and viability of the company using “Z” Score model  Secondary objective: - To analyze the financial condition of few selected to know the efficiency in financial operations of the company. To offer suitable suggestions.
  • 3. Need and Scope for the study  The primary need of the study is to analyze the financial health of the company and to identify the signs of financial distress and thereby avoid the Bankruptcy.  The scope of the study is limited to 5 years financial performance only.  This study help company improve the financial health and performance of the business.
  • 4. Introduction  There are various tools to measure the company performance.  Like- Ratio Analysis, RSI Calculation, DuPont Analysis, and EFQM Excellence Model Each of them use specific technics to measure the company profit, liquidity, and efficiency. But none of them is able to accurately predict overall performance of success trend.  Dopant Analysis The return on assets (ROA) ratio developed by DuPont for its own use is now used by many firms to evaluate how effectively assets are used. It measures the combined effects of profit margins and asset turnover.
  • 5. Cont.…  EFQM excellence model EFQM Excellence Model provides a holistic view of the organization and it can be used to determine how these different methods fit together and complement each other. The Model can therefore be used in conjunction with any number of these tools, based on the needs and function of the organization, as an overarching framework for developing sustainable excellence. This tools cannot predict whether the particular company is going towards bankruptcy.
  • 6. Altman Z-Score  The Altman Z-score is the output of a credit-strength test that gauges a publicly traded manufacturing company's likelihood of bankruptcy. The Altman Z-score, is based on five financial Ratio.  The Z-score Formula Z-Score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E Where, A = Working Capital/Total Assets B = Retained Earnings/Total Assets C = Earnings before Interest & Tax/Total Assets D = Market Value of Equity/Total Liabilities E = Sales/Total Assets
  • 7. Zones of Discrimination:  Z > 2.99 -“Safe” Zone  1.81 < Z < 2.99 -“Gray” Zone  Z < 1.81 -“Distress” Zone
  • 8. The sample of the 10 Company Company applied for de-listed Year Company applied for de-listed Year Max Financial Service 2016 Punj lloyad Ltd. 2016 India Cements 2016 SQL Star International 2016 Hexaware Technologies 2016 Cable Corporation of India 2016 Circuit System 2016 Piramal Glass 2016 Educomp Solution 2016 Hexaware Technologies 2016
  • 9. Altman Z-Score Calculation S.N Company Name Year's 2015 2014 2013 2012 2011 1Max Financial Service 5.093618 2.875133 3.755659 2.470703 2.345724 2India Cements 1.147843 0.929259 1.163262 1.339966 1.01213 3Hexaware Technologies 9.260657 5.143688 5.132221 5.132221 2.570922 4Circuit System 4.910066 2.78405 1.991317 2.156579 1.864063 5Educomp Solution 0.026086 0.755868 1.312634 2.321558 4.193494 6Punj lloyad Ltd. 1.455609 2.020699 2.319751 2.099082 2.135202 7SQL Star International -16.1122 5.790945 5.15904 -0.86034 7.755316 8Cable Corporation of India 0.20232 2.726337 3.335721 2.956767 3.352931 9Piramal Glass 5.370194 4.329741 5.88315 6.909085 5.849679 10Manjushree Technipark 5.426089 5.319517 4.816005 5.199257 4.437346
  • 10. CONCLUSION AND RECOMMENDATION  As our conclusion, we have identified some issues based on our findings. Firstly, Altman Z-score is mostly designated for manufacturing firms, and therefore, firms from other industries may not match with the model. Secondly, external factors like economic conditions, seasonality of sales, company size, geographical location and pre-bankruptcy non-financial events are yet to be included in Altman’s Z-score during bankruptcy prediction. Thirdly, Altman Z-score only uses past financial data, which is difficult for projecting the future value of firms. Lastly, as Altman’s Z-score solely depends on the past financial data, it may confront with window dressing