COMPARING NET PROFIT FORECASTS OF INDIAN BANKS USING OLS AND GARCH 1,1 FRAMEWORK

Abstract

In the present paper the Bi-variate Ordinary Least Square (OLS) and Generalized autoregressive conditional heteroskedasicity (GARCH 1, 1) model are applied to gather the fitted Net –Profit series of Two nationalized banks viz, State Bank of India SBI (being a leader) and ING Vysya bank (not a leader) in the Indian Banking sector. It is evident that OLS is non-parameterized method while QMLE or QML is a parameterized technique of coefficients estimation. The robustness must therefore need to see with respect to the data in consideration. The whole approach is to measure how both the models provide Earning forecasts and to analyze the behavior of regression coefficients. Also, the second objective could be to see how “Leader” bank earnings estimation process differs from the non-leader bank in the Indian banking setup. The results are clearly explaining differences in two banks in terms of their coefficient values, residual state and R-squared values.