A STUDY ON FINANCIAL HEALTH OF SELECTED PUBLIC SECTOR MANUFACTURING COMPANIES OF INDIA : WITH REFERENCE TO Z-SCORE ANALYSIS

Financial distressed from a decade has become a common condition for manufacturing companies of India. Many public sector manufacturing companies have also witnessing poor financial health. This study has examined the financial health of eighteen selected public sector manufacturing companies which are further divided into four sectors as Metal, Sugar, Paper and Textile. The examination of financial health of selected companies has been performed by calculating Altman Z-score model for four year prior to become distressed. And it has been found by the analysis that most of the company was in either distressed zone or in grey zone. The study also finds that Altman Z-Score Model is a perfect tool to examine the health of public sector manufacturing companies. companies for a period of ten years from financial year 2007-2008 to 2016-2017. The final sample was comprised to the 171 companies among which 7 were distressed and 164 were sound. Data required for computing BSM- probability of default was accessed from corporate database maintained by Center for Monitoring Indian Economy (CMIE). Current value of assets, Asset volatility, face value of total Liabilities, size, dividend, risk-free rate and standard deviation of stock returns have been taken as variables. The researcher has used two statistical Model; Black-Scholes (1973) and Merton (1974) to know the probability of default. The study shows that the maximum percentage of company becoming Distresses was 44% in 2009. The result demonstrated that approximately 4% of the total companies were found to be financially distresses through the period 2007-2016. The highest distress being in 2009. identified and which Orientation”, the pay” sickness”. viability study secondary analysis the prediction tool. out the correlation between working and total assets, retained and total assets, EBIT and total assets, market value of the equity and total liability, sales and total assets the Z scores ratio for selected five. study that the selected companies overall financial health very much satisfactory and they are financially healthy companies. A Panel Estimated Generalized Least Squares (EGLS) Approach” (2019) aimed to identify the relationship between financial distress and corporate profitability from a developing country like Nigeria. The researcher considered all quoted consumer goods manufacturing firms listed on the Nigerian stock Exchange as at December 2017. Study was secondary data based collected form annual reports. The study used the ex-post facto research design, panel estimated generalized least squares, using cross-sectional weighting to validate the hypothesis. This study concludes that all selected public sector manufacturing companies were in either distressed or in grey zone at the time of declared sick. And this can be also concluded that Altman Z-score model efficiently examines the financial health of company whether it is in safe, grey or distressed zone.

Financial distressed from a decade has become a common condition for manufacturing companies of India. Many public sector manufacturing companies have also witnessing poor financial health. This study has examined the financial health of eighteen selected public sector manufacturing companies which are further divided into four sectors as Metal, Sugar, Paper and Textile. The examination of financial health of selected companies has been performed by calculating Altman Z-score model for four year prior to become distressed. And it has been found by the analysis that most of the company was in either distressed zone or in grey zone. The study also finds that Altman Z-Score Model is a perfect tool to examine the health of public sector manufacturing companies.

…………………………………………………………………………………………………….... Introduction:-
Financial hardship of the companyis the situation when firm is unable to meet its debt and faces financial difficulty. Due to the financial crisis organizations become bankrupt and lead to the loss of wealth. A consecutive financial loss or hardship leads to the condition of financial distress.Performance of any company can be determined by good financial health of the company. Analysis of financial health helps to make overall decisions about the functioning of any company. Financial health of any company can be analyzed by some broadly used accounting tools given below-Z-score formula is given below: Z-Score = (1.2X1) + (1.4X2) + (3.3X3) + (0.6X4) + (1.0X5) Where, X1= Working Capital/Total Assets X2= Retained Earning/Total Assets X2= Earnings before Interest and Tax/Total Assets X3= Earnings before Interest and Tax/ Total Assets X4= Market value of equity/ Total liability X5= Sales/ Total Assets Financial position of the company is determined on the basis of score calculated by the above formula. When score is 2.99 and above the company is in safe zone. If score is lying between 1.81 and 2.99 the company is in grey zone, which means it need to be cautioned. And when score is below 1.81 it is said to be sick or financially distressed. In this study Z-score model has been used for Analysis of Financial health of selected companies.

Review of Literature:-
Japneet Kaur in their study "Financial distress identification: application of black-scholes-merton model"(2018) have tried to determine the probability of default among the NSE Nifty-500 companies for a period of ten years from financial year 2007-2008 to 2016-2017. The final sample was comprised to the 171 companies among which 7 were distressed and 164 were sound. Data required for computing BSM-probability of default was accessed from corporate database maintained by Center for Monitoring Indian Economy (CMIE). Current value of assets, Asset volatility, face value of total Liabilities, size, dividend, risk-free rate and standard deviation of stock returns have been taken as variables. The researcher has used two statistical Model; Black-Scholes (1973) and Merton (1974) to know the probability of default. The study shows that the maximum percentage of company becoming Distresses was 44% in 2009. The result demonstrated that approximately 4% of the total companies were found to be financially distresses through the period 2007-2016. The highest distress being in 2009. Golla, Siva Krishna; Rao, K Ramachandra in their study "A Factor Analysis on the Determinants of Industrial Sickness in Small Scale Enterprises"(2019) have tried to find out the identification and classification of the factors which contribute towards industrial sickness in The researcher also tried to quantify the cross factorial impact on organizational survival or sickness in small scale enterprise and they also analyze the relationship among the factors that defines the survival or sickness and revival, for the purpose of study 300 enterprise were selected across three district of Andhra Pradesh. The collected data was analyzed through SPSS based explorative factor analysis. The factors were identified as "internal" and "External" which contribute to "market Orientation", influence on the "ability to pay" and Threat from sickness". The sickness was attributes to internal, external as well as market orientation grounded factors that all together shape the revival or sickness of enterprise.
Dr. PranamDhar, BidhanBaidya, Bishnupada Das, Sayantan Bose in their study "Financial Health Of Select Indian It Companies -A Study With Reference To Z-Score Analysis" (2019) has tried to find out the overall financial 859 performance of the ten companies selected form different sectors, efficiency in financial operation and tried to predict the financial health and viability of the selected company. For the purpose of study secondary data collected form the annual reports of the companies for the period of five years (2009-10 to 2013-14). Ratio analysis was used as the prediction tool. The researchers have found out the correlation between working and total assets, retained earnings and total assets, EBIT and total assets, market value of the equity and total liability, sales and total assets and the Z scores ratio for selected five. The study concluded that the selected companies overall financial health was very much satisfactory and they are financially healthy companies.
Bishwajeet Prakash, Dr. Vijay, Dr. Jainendra Kumar Vermain their study "Predicting financial performance of Agro Based (Tea & Coffee) Industries in India: An empirical study Using Altman Z-Score Multivariate Model" (2019) aimed to predict the financial stability of Agro & allied based (Coffee & tea) producers companies listed in NSE over the period of 2014-2018. For the study top five agro based companies were selected on the bases of largest market capitalization value. Data has been analyzed by Multiple Discriminate Analysis model (Altman z score) which concludes that 50 % of the selected companies were in the position of financial distress and some of them were in grey and safe zone.
Corina Georgiana COSTEA in their study "Blockchain-Based Solutions For Financially Distressed Or Insolvent Companies" (2019) they aimed to identify the use of blockchian technology as an instrument of insolvency treatment of companies and financial difficulty prevention. The paper analyzed the way that blockchain technology could be applied to business rescue through pre-insolvency and insolvency proceedings, in accordance with the insolvency legal framework. The research concluded that blockchain may be applied in practice, because of its properties which may be useful to detect and prevent financial difficulties and insolvency.
Egbunike, Francis Chinedu, Ogbodo, Cy. Okenwa, Ojimadu, Jerry Okechukwuin their study "The Effect of Financial Distress on Corporate Profitability: A Panel Estimated Generalized Least Squares (EGLS) Approach" (2019) aimed to identify the relationship between financial distress and corporate profitability from a developing country like Nigeria. The researcher considered all quoted consumer goods manufacturing firms listed on the Nigerian stock Exchange as at December 2017. Study was secondary data based collected form annual reports. The study used the ex-post facto research design, panel estimated generalized least squares, using cross-sectional weighting to validate the hypothesis.

Objectives Of The Study:-
1. To study the various methods toexamine financial health of selected companies. 2. To examine the financial health of selected companies.

Type of Research
The research is exploratory and descriptive in nature

Scope of the Study
The study has included sick public sector manufacturing companies. Eighteen companies have been selected on the basis of convenient sampling method, which were declared sick by BIFR. The selected eighteen companies are further classified in four industries as Metal, paper, sugar and Textile.

Sample selection criteria
For the purpose of the study 18 Indian public sectorsmanufacturing companies have been selected, which were badly suffering from loss during the selected period. Companies have been declared sick by BIFR during the period of 2010-2011 to 2015-2016.

Sampling Technique
Sample is collected on the basis of Convenient Sampling method.

Type of data
Secondary data has been used for the purpose of study.

Sources of data
The data required for the study has been collected from the Annual Reports and official websites of selected companies have been considered.

Duration of research
Six financial years during which the selected companies were declared sick i.e. from 2010-2011 to 2015-2016.

Tools for study
Altman Z-score model has been used for the purpose of examination of financial health of selected company.

Data Analysis
For the purpose of analysis of financial health of selected companies Z-scores for four years of prior to become financially distressed have been calculated for each company and financial health has been classified in different zone on the basis of score calculated.

Z-Scores of Shree Krishna Paper Mills & Industries Ltd
All the financial figures have been taken in Crores Rupees.