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Annals of Data Science

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

  • 01-07-2022
Published in:
Authors
Asif Pervez
Irfan Ali
Published in
Annals of Data Science | Issue 2/2024

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Abstract

The article delves into the challenges of analyzing financial data due to volatility and economic factors, highlighting the importance of robust regression techniques. It focuses on the financial performance of public sector banks in India, particularly the impact of Basel norms and other variables such as bank size, risk, and liquidity. The study employs robust regression methods like LMS, LTS, and M-estimators to provide a more reliable analysis of financial data. The findings reveal significant relationships between bank performance and variables such as bank risk, capital adequacy, and income diversification. The article concludes with implications for banks and policymakers, suggesting the adoption of advanced data management systems and cost-efficient compliance with Basel III norms. It also outlines potential future research directions in robust regression analysis for financial data.
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Title
Robust Regression Analysis in Analyzing Financial Performance of Public Sector Banks: A Case Study of India
Authors
Asif Pervez
Irfan Ali
Publication date
01-07-2022
Publisher
Springer Berlin Heidelberg
Published in
Annals of Data Science / Issue 2/2024
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI
https://doi.org/10.1007/s40745-022-00427-3
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