COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX)
ISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric kernel regression. The kernel regression meth...
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Universitas Pattimura
2022-03-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5127 |
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| author | Yuniar Farida Ida Purwanti Nurissaidah Ulinnuha |
| author_facet | Yuniar Farida Ida Purwanti Nurissaidah Ulinnuha |
| author_sort | Yuniar Farida |
| collection | DOAJ |
| description | ISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric kernel regression. The kernel regression method is one of the nonparametric regression methods used to estimate conditional expectations using kernel functions. Kernel functions used in this study are gaussian and Epanechnikov kernel functions. The estimator used is the estimator Nadaraya-Watson. This study aims to compare the two kernel functions to predict the value of ISSI in the period from January 2016 to October 2019. The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. Independent variables that significantly affect ISSI are interest rates, exchange rates, and inflation. Curve smoothing is done using bandwidth value (h) searched by the Silverman rule. The calculation result with the Silverman rule obtained a bandwidth value of 101832.7431. |
| format | Article |
| id | doaj-art-a9a4fa7de025483d9dbc8e73d6a112e0 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-a9a4fa7de025483d9dbc8e73d6a112e02025-08-20T03:36:12ZengUniversitas PattimuraBarekeng1978-72272615-30172022-03-0116132333210.30598/barekengvol16iss1pp321-3305127COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX)Yuniar Farida0Ida Purwanti1Nurissaidah Ulinnuha2Department of Mathematics, Science and Technology Faculty, UIN Sunan Ampel SurabayaDepartment of Mathematics, Science and Technology Faculty, UIN Sunan Ampel SurabayaDepartment of Mathematics, Science and Technology Faculty, UIN Sunan Ampel SurabayaISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric kernel regression. The kernel regression method is one of the nonparametric regression methods used to estimate conditional expectations using kernel functions. Kernel functions used in this study are gaussian and Epanechnikov kernel functions. The estimator used is the estimator Nadaraya-Watson. This study aims to compare the two kernel functions to predict the value of ISSI in the period from January 2016 to October 2019. The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. Independent variables that significantly affect ISSI are interest rates, exchange rates, and inflation. Curve smoothing is done using bandwidth value (h) searched by the Silverman rule. The calculation result with the Silverman rule obtained a bandwidth value of 101832.7431.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5127epanechnikov kernelgaussian kernelnadaraya-watson estimatornonparametric regressionissi |
| spellingShingle | Yuniar Farida Ida Purwanti Nurissaidah Ulinnuha COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) Barekeng epanechnikov kernel gaussian kernel nadaraya-watson estimator nonparametric regression issi |
| title | COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) |
| title_full | COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) |
| title_fullStr | COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) |
| title_full_unstemmed | COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) |
| title_short | COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) |
| title_sort | comparing gaussian and epanechnikov kernel of nonparametric regression in forecasting issi indonesia sharia stock index |
| topic | epanechnikov kernel gaussian kernel nadaraya-watson estimator nonparametric regression issi |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/5127 |
| work_keys_str_mv | AT yuniarfarida comparinggaussianandepanechnikovkernelofnonparametricregressioninforecastingissiindonesiashariastockindex AT idapurwanti comparinggaussianandepanechnikovkernelofnonparametricregressioninforecastingissiindonesiashariastockindex AT nurissaidahulinnuha comparinggaussianandepanechnikovkernelofnonparametricregressioninforecastingissiindonesiashariastockindex |