Ppt on Synopsis

1. FINANCIAL ANALYSIS OF two BSE
LISTED SMALL CAP COMPANIES BY
USINGALTMANZ SCOREMODEL
Presented By:- Bibhudutta Tripathy
ROLL NO:- IBS22PGDM008
Guided By:- Asst . Prof. Smruti Ranjan Sahoo
03/02/2024

2. AGENDA
WHAT IS THE MOTIVATION ON BEHIND THIS TOPIC?
LITERATURE REVIEW
RESEARCH GAP
RESEARCH OBJECTIVE
CONCEPTUAL FRAME WORK
SAMPLING AND SAMPLE SIZE
SOURCES OF DATA COLLECTION
LIST OF REFERENCES

3. Investors Are Interested To Measure
Financial Performance Of Stock Exchange
Listed Companies.
Investors Perceive That Investment In
Small Cap Companies Are Risky.
WHAT IS THE MOTIVATION BEHIND
THIS TOPIC

4. AUTHOR TITLE
OBJECTIVE OF THE
STUDY
RESEARCH
METHODLOGY
FINDINGS
Dr Riyas Kalathinkal
and Muhammad
Imthiyaz Ahamed
(2015)
“ A study on
Application of Altman
Z Score model for
Oman cement
company”
To analyze the financial
statements of Oman
Cement Company
during the period 2009-
2013 by using Altman Z
score model
Altman Z Score Model
During 2009-2013 the
company's Z score was
more than 2.90, So
therefore it is
understood that the
company is not affected
by bankrupt.
Shariq Mohammed
(2016)
“ Bankruptcy Prediction
Using the Altman Z-
Score Model in Oman:
A case study of Raysut
Cement company
SAOG and its
subsidiaries”
 To assess the overall
financial
performance of the
company from 2007-
2014.
 To predict the
financial health and
viability of the
company from 2007-
Altman Z Score Model
The study revealed that
Raysut Cement
Company SAOG and its
subsidiaries is
financially sound in
study period as they
have higher Z score
than the benchmark
2.99 except
LITERATURE REVIEW

5. Soumya Agarwal
(2018)
“Altman Z Score With
Reference To Public
Sector Banks in India”
To identify a trend in
the Z” Score of the Top
5 Public Sector Banks in
India from 2012- 2016.
Altman Z Score Model
The Z” Scores of the
control banks SBI, PNB,
BOB and Central Bank
of India are currently
relatively low compared
to IDBI Bank with a high
Z” Score.
Dr. Prameela S. Shetty
and Ms. Ramya Shetty
(2020)
“Prediction Of
Bankruptcy of a Bank
through Z Score Model-
A case study of Yes
Bank”
 To analyses the
financial
performance of Yes
Bank for a period of
6 years,2013-14 to
2018-19.
 To predict the
possibility of
bankruptcy using z
score formula.
Altman Z Score Model
 The Z-score failed to
predict the banks
movement.
 The actual reason for
the banks
performance was
the internal fight
between the
promoters and also
the aggressive
lending policy of the
bank.

6. Meena Rani
(2022)
“A comparative Study
on Analyzing the
Solvency of The Indian
Public, Private and
Foreign Sector
Commercial Banks
Using Modified Altman
Z-Score”
To analyze the
solvency position of
different public sector,
private sector, and
Foreign banks by
putting Altman Z score
from 2016 – 2020.
Altman Z Score Model
Took data of total 77
commercial banks. The
study has found
interesting outcomes,
that private sector
banks were more
financially solvent in
comparison to foreign
and public sector
banks.

7. A very few study have been
conducted to study financial
performance of Banking and
Cement industry by using
ALTMAN Z SCORE MODEL.

8. RESEARCH OBJECTIVE
o TO study financial performance analysis of
Indian Cement by using ALTMAN Z
SCORE model.
o TO study financial performance analysis of
UCO Bank by using ALTMAN Z
SCORE model.

9. Conceptual Frame Work
The Z-score formula for predicting bankruptcy was published in 1968 by Edward Altman.
The formula may be used to predict the probability that a firm will go into bankruptcy within two years.
 X1 = Working Capital / Total assets
(WC=Current Assets-Current Liabilities)
 X2 = Retained Earnings / Total Assets
(RE= Total Reserve & Surplus)
 X3 = Earnings Before Interest and Taxes / Total Assets
(EBIT= Net Profit + Interest + Tax)
 X4 = Market Value of Equity / Total Liabilities
(MVE= Paid up Share Capital)
 X5 = Sales / Total Assets

10. Altman Z Score Model
 Z-score bankruptcy model (Manufacturing Firms):
 Z = 1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1X5
Zones of discrimination:
 Z > 2.99 – “Safe" zone
 1.81 < Z < 2.99 – “Grey" zone
 Z < 1.81 – “Distress" zone
 Z-score bankruptcy model (Non-manufacturers/ Service Sector):
 Z = 6.56X1 + 3.26X2 + 6.72X3 + 1.05X4
Zones of discrimination:
 Z > 2.6 – "Safe" zone
 1.1 < Z < 2.6 – "Grey" zone
 Z < 1.1 – "Distress" zone

11. SAMPLING AND SAMPLE SIZE
 Convenience and Random sampling methods are used
 Sample size is Two
 In Cement Industry we choose Indian Cement limited
 In Banking Industry we choose UCO Bank

12. SOURCES OF DATA COLLECTION
 Secondary sources of data
collection from Financial
Statements of companies.

13. LIST OF REFERENCES
 Dr Riyas. Kalathinkal and Muhammad Imthiyaz Ahamed (2015) in their study “ A study of Application of Altman Z
Score model for Oman cement company”.
 Shariq Mohammed (2016) in his study on “ Bankruptcy Prediction Using the Altman Z-Score Model in Oman: A
case study of Raysut Cement company SAOG and its subsidiaries”.
 Soumya Agarwal(2018) “Altman Z Score With Reference To Public Sector Banks in India”.
 Dr. Prameela S. Shetty and Ms. Ramya Shetty (2020) “Prediction Of Bankruptcy of a Bank through Z Score Model-
A case study of Yes Bank”.
 Meena Rani (2022) “ A comparative Study on Analyzing the Solvency of The Indian Public, Private and Foreign
Sector Commercial Banks Using Modified Altman Z-Score”.