Ridge regression model using Kibria parameter

Aziz, Abdul ORCID: https://orcid.org/0000-0003-1506-1597, Royani, Mega Nur and Chamidah, Nur (2022) Ridge regression model using Kibria parameter. Presented at The 12th International Conference on Green Technology (ICGT 2022), 26-27 Oct 2022, Malang, Indonesia.

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Abstract

Stock prices in the economy, especially in Indonesia, is very important that so many people want to get benefits from investing stocks. The rate of return that owned by investor is called return investment. In this research, we are looking for return of stock model, which is useful for predicting return of stock at a certain time. Method that used forecasting of return is ridge regression using tuning parameter Kibria. The purpose of using this method is for eliminate multicollinearity that cannot be in OLS method. Model of return of JKSE is searched by following the steps in regression method and using tests to get the best model. Based on the result of the study, it was obtained that the equation of the ridge regression model with all the independent variables had a significant effect on return of stock. The tests that perfomed are normality test, multicollinearity test and parameter significant test. The VIF value obtained is also less than 10, namely

Item Type:	Conference (Other)
Keywords:	ols; ridge; kibria; return of stock; multicollinearity
Subjects:	01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics 14 ECONOMICS > 1402 Applied Economics
Divisions:	Faculty of Mathematics and Sciences > Department of Mathematics
Depositing User:	Mr. Abdul Aziz
Date Deposited:	29 Sep 2026 13:55

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