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Financial Health of Select Teclecomcompanies in India

2019, Think India Journal

Indian telecom industrywas disrupted with the entry of Reliance Jio in the year 2016. It introduced low cost call and data resulted in extreme competition amongst the existing players in the market. In the disruption situation, the competitors tried to offer services at low prices in order to retain itscustomers and market share, and hence impacting growth in revenues and profitability. This resulted in financial stress in this particular sector during the entry of reliance Jio. The study attempted to evaluate the financial health of telecom service companies in India namely Vodafone Idea,RCOM and Bharati Airtel. The study considers the period from 2013-14 to 2017-2018. The study is quantitative in nature and hasused Altman 'Z' score model for understanding the financial stability.

THINK INDIA JOURNAL ISSN: 0971-1260 Vol-22-Issue-10-November-2019 Financial Health of Select Teclecomcompanies in India Dr. MARIMUTHU, KN Assistant Professor, Department of Management Studies, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli-627012, Tamilnadu- India. 9492024843,marimuthumsu@msuniv.ac.in Dr. SYED AZHAR Assistant Professor, ICBM-SBE, Attapur Hyderabad, Telangana- 500048 8142311156,azharsyed4617@gmail.com Dr. B. RAMESH Assistant Professor, GITAM University Hyderabad, Telangana 9849625937, rameshbyshetty@gmail.com Abstract Indian telecom industrywas disrupted with the entry of Reliance Jio in the year 2016. It introduced low cost call and data resulted in extreme competition amongst the existing players in the market. In the disruption situation, the competitors tried to offer services at low prices in order to retain itscustomers and market share, and hence impacting growth in revenues and profitability. This resulted in financial stress in this particular sector during the entry of reliance Jio. The study attempted to evaluate the financial health of telecom service companies in India namely Vodafone Idea,RCOM and Bharati Airtel. The study considers the period from 2013-14 to 20172018. The study is quantitative in nature and hasused Altman ‘Z’ score model for understanding the financial stability. Key Words: Telecom Industry, Financial Health and Z-Score Bankruptcy Model INTRODUCTION India is presently the world‟s second-largest telecommunications market with a subscriber base of 1.17 billion and has registered strong growth in the past decade and a half. According to a report by GSM Association (GSMA) in association with the Boston Consulting Group (BCG), the Indian mobile economy is developing at a great pace and will contribute significantly to India‟s Gross Domestic Product (GDP). Downloading of Apps in the country developed approximately 215 per cent between 2015 and 2017. This shows the increase in the usage of teleservices. The liberal and reformist policies of the Government of India have been instrumental, along with strong consumer demand for the rapid growth in the Indian telecom sector. The government has enabled easy market access to telecom equipment and a fair and proactive regulatory framework that has ensured availability of telecom services to consumer at affordable prices. The deregulation of Foreign Direct Investment (FDI) norms has made the sector one of the fastest growing and a top five employment opportunity generator in the country. P a g e | 8797 Copyright ⓒ 2019Authors THINK INDIA JOURNAL ISSN: 0971-1260 Vol-22-Issue-10-November-2019 REVIEW OF LITERATURE: The present study has critically evaluated the literature on financial performance using Altam Z score. The studies by Altam and Deakin have pioneered in evaluating the financial solvency position of companies. Altman (1968) has evaluated the Financial analysis and forecast of corporate Bankruptcy using five financial ratios for predicting the risk of failure and developed „Z' scoremodel whereas Deakin (1972) elaborated using fourteen important ratios identified by Beaver but applied using multivariate methodology. A sample of 32 failed andnon-failed firms respectively. It is found that cash flow coverage to total debt was important for predicting bankruptcy. Few studies have used Altman Z score to predict the solvency position of selected companies in different industries. Kannadhasan(2007) have analysed the financial health of a public limited company using „Z‟ score model Azhar& Ramesh (2017) studied the financial health of power generation/distribution utilities listed operating in India. The study found that most of the sample companies are falling in the distress zone.It is widely used to predict the financial health of companies in both manufacturing and service sector. Altman‟s Z score is used world-wide for assessing the financial health in telecom industry. Zaemah, Afiruddin and Rahim (2018) have evaluated the financial health of listed technology companies in Malaysia for the period of 2012-2016 The result indicates that the Green Packet Bhd, OmestiBhd and HeiTechPaduBhd were falling in grey zone to distress zone indicating poor financial performance. On average, the listed technology companies are using 67.1 per cent of debt and 32.9 per cent of equity to finance their assets. AlAli, Musaed S. (2018) have analysed the financial health of listed mobile companies in Kuwait stock exchange (KSE) for the period of 2013-2016 using Altman Z-score model to examine the likelihood of bankruptcy. The study found that one company among the three companies operating in Kuwait was financially sound. The study found that the sample companies were at the verge of bankruptcy due to their working capital. The current liabilities were more than the current assets due to the short-term obligations were not met.Ramachandran, Nithya& Al Hajri, JawaherAamir (2019) have analysed the financial health of telecom companies Using Altman‟s Z- Score Model for the period of 2016 to 2018. The sample comprised of both private and public companies operating in GCC countries namely Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and U.A.E. The study found that the financial soundness of sample companies is satisfactory. Problem of the Study: Evaluation of Financial health of a firms is very important to understand the performanceof the Industry. A stressed financial position of the companies has been a danger on revenues and may lead to bankruptcy. The Telcomindustry is in turmoil and government is expected to provide relief in taxation to reduce the financial stress. It is also evident that this sector has witnessed fall in foreign direct investments in the year 2018-19 amounting to $2.67 billion from $6.21 billion. Ravi Shankar Prasad, The Minister of Communications said that “Financial health of the telecom sectoris a matter of concern for the Government and measures are on the way to boost the financial position. P a g e | 8798 Copyright ⓒ 2019Authors THINK INDIA JOURNAL ISSN: 0971-1260 Vol-22-Issue-10-November-2019 OBJECTIVE OF THE STUDY  To study the financial health of selected companies in telecom sector of India RESEARCH METHODOLOGY The study attempted to evaluate the financial health of selected telecom companies in India. The data is based on secondary sources procured frommoneycontrol. The data was extracted from the annual reports of selected companies for a period of five years starting from 20132014 to 2017-2018. The most popular model, Dr. Edward I. Altman‟s Multiple Discriminate Analysis has been used as tool to analyse the collected data. According to Suriyamurthi&Velavan (2010) predictive viability of company‟s financial health using a combination of financial ratio ultimately predicts a score which can be used to determine the financial health of company. The formula used to evaluate the „Z‟ Score analysis for Non- Manufacturing Firms: Z-Score bankruptcy model: Z = 6.56X1 + 3.26X2 + 6.72X3 + 1.05X4 Where, X1 = (Current Assets − Current Liabilities) / Total Assets X2 = Retained Earnings / Total Assets X3 = Earnings before Interest and Taxes / Total Assets X4 = Book Value of Equity / Total Liabilities Zones of discriminations: Z > 2.6 -“Safe” Zone 1.1 < Z < 2.6 -“Grey” Zone Z < 1.1 -“Distress” Zone DATA ANALYSIS AND INTERPRETATION The study will evaluate the financial health of three different players individual for the period of 2014-2018. Table 1 :‘Z’ Score value of Vodafone Idea Limited Year 2018 2017 2016 2015 2014 X1 -0.20108737 0.141331273 0.703868979 0.741126929 0.894994134 1.03393202 X2 0.718248924 0.684883296 0.87720719 0.908944918 4 0.68145108 X3 0.2186321 0.80519894 0.164809212 0.166465969 9 0.64228580 X4 0.379333518 0.345786026 0.482528379 0.576100813 1 2.35766891 Z 0.93277323 0.864203353 1.578367669 2.290244672 5 Zones of Distress Distress Discriminatio Grey Zone Grey Zone Grey Zone Zone Zone n P a g e | 8799 Copyright ⓒ 2019Authors THINK INDIA JOURNAL ISSN: 0971-1260 Vol-22-Issue-10-November-2019 It is evident from the Table 1 that Vodafone idea limited financial position was not satisfactory and as per the Z score model, it was marked under Grey Zone in the 2014, 2015 and 2016 but in the year 2017 and 2018 the financial worsened and it was labelled under the Distress Zone.The financial position worsened after the entry of Reliance Jio. During the entire study period, the Z' Score value is Lesser than 2.6 in all the years. Hence, the financial position / strength is not satisfactory. Table 2 :‘Z’ Score value of R COM Year 2018 2017 2016 2015 2014 X1 -0.2221881 -1.007762 -0.44306 0.308795 -0.38578 X2 0.4622349 1.0077062 1.153545 1.498089 1.287386 X3 0.007687 0.0058206 0.011887 0.037635 0.004458 X4 0.2097613 0.5077442 0.618376 0.953992 0.724202 Z 0.4574952 0.5135085 1.340746 2.798511 1.630263 Zones of Distress Distress Grey Safe Grey Discrimination Zone Zone Zone Zone Zone It is evident form the Table 2 that the financial health of RCOM is satisfactory from 2014 to 2016 and thereafter in the year 2017 &2018, the financial health deteriorated. The Z score was 1.63 in the year 2014 but deteriorated to 0.45 by the end of 2018. Table 3 :‘Z’ Score value of BhartiAirtel Year 2018 2017 2016 2015 X1 -0.708841 -0.70196 -0.58236 -0.43042 X2 1.6044457 1.687665 1.933335 1.966776 X3 0.163687 0.175047 0.423979 0.620516 X4 1.0580697 1.175133 1.600509 1.706857 Z 2.1173616 2.335888 3.375461 3.863724 Zones of Discrimination Grey Zone Grey Zone Safe Zone Safe Zone 2014 -0.82626 2.148695 0.883335 2.225956 4.431728 Safe Zone Itis evident form the Table 3 that the financial health of BhartiAirtelis satisfactory during the study period. The financial health of Bharati Airtel was very healthy and sound till the year 2016 but with the entry of Jio, the financial position weakened. The financial scores moved from safe zone to grey zone by the end of the study period. Among the three companies, only Bharati Airtel managed to sustain its market share and generate revenues after the Jio. The entry of Reliance Jio have initiated price wars and the smaller companies had no option to exit the telecom industry. The big competitors such as Vodafone India and Idea have merger to survive the impact of disruption in the market. CONCLUSION Fiscal strength of the company is essential for each and every shareholder of the company. For measuring the financial health Altman‟s Z score plays a significant part in judging the financial accuracy of the company. The contemporary study analysed the financial soundness of the selected companies.It concludes that RCOM‟s and Vodafone‟s financial position is not P a g e | 8800 Copyright ⓒ 2019Authors THINK INDIA JOURNAL ISSN: 0971-1260 Vol-22-Issue-10-November-2019 satisfactory but BharatiAirtel‟s financial position is satisfactory. The entry of such service provider or plan can completely disrupt the telecom industry. Hence, the government should intervene and attempt to control such shock to the existing players. Further studies can be carried out using different techniques for evaluating the financial health. REFERENCES: 1 AlAli, Musaed S. (2018) Predicting financial distress for mobile telecommunication companies listed in Kuwait stock exchange using Altman‟s model, Journal of Economics Finance and Accounting, Vol. 5, Issue 3 2 Altman, (1968). “Financial ratios discriminate analysis and prediction of corporate bankruptcy”, Journal of Finance, Sep. pp. 598-609. 3 Azhar, Syed and Ramesh, B., (2017) Predicting Financial Insolvency of Listed Power Generation/Distribution Companies in India Using Z–Score (December 14, 2017).IOSR Journal of Business and Management (IOSR-JBM) (2017). Available at SSRN: https://ssrn.com/abstract=3087896. 4 Deakin, E. 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