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Robust Regression Analysis in Analyzing Financial Performance of Public Sector Banks: A Case Study of India

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  • Asif Pervez

    (Jamia Millia Islamia)

  • Irfan Ali

    (Aligarh Muslim University)

Abstract

Regression analysis is a statistical method to analyze financial data, commonly using the least square regression technique. The regression analysis has significance for all the fields of study, and almost all the fields apply least square regression methods for data analysis. However, the ordinary least square regression technique can give misleading and wrong results in the presence of outliers and influential observations in the data. Robust estimation is a statistical method to analyze such financial data with outliers. It is an alternative method for the least square regression for such data. It is necessary to elaborate on the applications of the robust regression model in analyzing real-world financial data that do not fulfil the assumptions of most statistical methods of data analysis to get reliable results. Public sector banks are the backbone of the Indian financial system. The present study analyzed the financial performance of public sector banks in India by applying a robust linear regression technique for more reliable outcomes. Twenty-one public sector banks were selected to study based on the importance of public sector banks in India.

Suggested Citation

  • Asif Pervez & Irfan Ali, 2024. "Robust Regression Analysis in Analyzing Financial Performance of Public Sector Banks: A Case Study of India," Annals of Data Science, Springer, vol. 11(2), pages 677-691, April.
    • Handle: RePEc:spr:aodasc:v:11:y:2024:i:2:d:10.1007_s40745-022-00427-3
    DOI: 10.1007/s40745-022-00427-3
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