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Calendar anomalies in CNX Finance index which consist of 15 Finance-Housing, Banks, Financial Institution, CNX IT index consist of 20 Computer-Software companies, CNX Pharmaceutical index consist of 10 Pharmaceutical companies. This study tests the presence of the 'quarter of the year effect', 'month of the year effect' on stock market indices volatility by using the CNX Finance index, CNX IT index, CNX Pharmaceutical index during the period of 1st January 2004 to 31st March 2013. Data was analysed using descriptive statistics and inferential statistics. Thus findings revealed that quarter of the year effect, month of the year effect is present in all 3 indices volatility i.e. risk and returns. The maximum returns of CNX Finance index, CNX Pharmaceutical index are observed in 2nd Quarter and minimum returns are observed in 4th Quarter. Whereas maximum returns of CNX IT index is observed in the Quarter 2 and minimum returns in the Quarter 1. CNX Finance and CNX IT both are showing maximum volatility in 1st quarter, Quarter 4 is highly volatile for CNX Pharmaceutical index. Finance index maximum returns in the month of September. Whereas IT index shows maximum returns in December month. Pharmaceutical index shows maximum returns in the month of April. Finance index shows minimum returns in the month of October, IT index shows minimum returns in the month of May, Pharmaceutical index shows minimum returns in the month of January. Finance and IT index shows maximum volatility in the month of May, whereas Pharmaceutical index shows maximum volatility in the month of October.

Keywords

CNX Finance Index, CNX it Index, CNX Pharmaceutical Index, Month of the Year Effect, Quarter of the Year Effect, Volatility

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Performance Evaluation of Public Sector Banks with Reference to 'CAMEL Model' for the Period of 2006-2013

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Authors

Shailaja P. Yadav ¹

Affiliations
1 Indira Institute of Business Management, Sanpada, Navi-Mumbai, IN

Source

Asian Journal of Management, Vol 5, No 4 (2014), Pagination: 374-379

Abstract

A 'CAMEL' is basically a ratio based model for evaluating the performance of banks. It is a management tool that measures capital adequacy, asset quality and efficiency of management, quality of earnings and liquidity position of Banks. In the present study, the financial performance of the public sector banks is measured and compared to ascertain which bank work efficiently. All the banks were first individually ranked based on the sub-parameters of each parameter. The sum of these ranks is then taken to arrive at the group average of individual banks for each parameter. Final the composite rankings for the banks were arrived at after computing the average of these group averages. Banks were ranked in the ascending/descending order based on the individual sub-parameter. Economic development of any country is mainly influenced by the growth of the banking industry in that country. The overall performance table in the study clearly shows that the Bank of Baroda is ranked at top position, followed by Indian Bank, Andhra Bank, Punjab National Bank, Syndicate Bank, Bank of India.

Keywords

Banking Supervision, Capital Adequacy, Asset Quality, Management Efficiency, Earning Quality, Liquidity, Financial Performance.

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References

Zumwalt, K. (2002). The Changing Relationship Between CAMEL Ratings and Bank Soundness during the Indonesian Banking Crisis. Review of Quantitative Finance and Accounting, 19(3), 247-260

Kapil, S. and Kapil, K, N, (2005). CAEL's Ratings and its Correlation to Pricing Stocks - An Analysis of Indian Banks. University Journal of Bank Management, 4(1), 64-78.

Singh, D., and Kohli, G. (2006). Evaluation of Private Sector Banks in India: A SWOT Analysis. Journal of Management Research, 6(2), 84-101.

Gupta, R. (2008). A CAMEL Model Analysis of Private Sector Banks in India. Journal of Gyan Management, 2(1), 3-8.

Satish D, Jutur Sharath and Surender V Indian Banking Performance and Development 2004-05, Chartered Financial Analyst, 11 (10), 6-15.

Derviz, A., and Podpiera, J. (2008). Predicting Bank CAMEL and SandP Ratings: The Case of the Czech Republic. Emerging Markets, Finance and Trade, 44(1), 117.

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