Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan

Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan

Stock is one of the investment instruments that is very popular among investors. One indicator of stock price movements in Indonesia is the Jakarta Composite Index (JCI). JCI data is a time series data about joint stock prices which can be analyzed by time series analysis method. However, with this...

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Bibliographic Details
Main Author: Nur Azizah Komara Rifai
Format: Article
Language:Indonesian
Published: Universitas Islam Bandung 2019-06-01
Series:Statistika
Subjects:
Bandwidth
Jakarta Composite Index
Kernel Regression
Nadaraya-Watson Estimator
Time Series Analysis
Online Access:https://ejournal.unisba.ac.id/index.php/statistika/article/view/4775
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spelling doaj-bf1e5267f6124217b54e2bdc7b9b05952020-11-24T22:11:22ZindUniversitas Islam BandungStatistika1411-58912019-06-01191536110.29313/jstat.v19i1.47752777Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham GabunganNur Azizah Komara Rifai0Bandung Islamic UniversityStock is one of the investment instruments that is very popular among investors. One indicator of stock price movements in Indonesia is the Jakarta Composite Index (JCI). JCI data is a time series data about joint stock prices which can be analyzed by time series analysis method. However, with this method there are assumptions that cannot be fulfilled. In this study, JCI data will be analyzed by a nonparametric method namely kernel regression with Nadaraya-Watson estimator. The weekly JCI closing price data from January 2015 to December 2015 is applied using various kernel functions that minimize the value of cross validation to get the optimal bandwidth. The results show that the biweight kernel regression with Mean Square Error = 9030,63 and bandwidth = 108,2 is the best model for predictions.https://ejournal.unisba.ac.id/index.php/statistika/article/view/4775BandwidthJakarta Composite IndexKernel RegressionNadaraya-Watson EstimatorTime Series Analysis
collection DOAJ
language Indonesian
format Article
sources DOAJ
author Nur Azizah Komara Rifai
spellingShingle Nur Azizah Komara Rifai
Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
Statistika
Bandwidth
Jakarta Composite Index
Kernel Regression
Nadaraya-Watson Estimator
Time Series Analysis
author_facet Nur Azizah Komara Rifai
author_sort Nur Azizah Komara Rifai
title Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
title_short Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
title_full Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
title_fullStr Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
title_full_unstemmed Pendekatan Regresi Nonparametrik Kernel pada Data Indeks Harga Saham Gabungan
title_sort pendekatan regresi nonparametrik kernel pada data indeks harga saham gabungan
publisher Universitas Islam Bandung
series Statistika
issn 1411-5891
publishDate 2019-06-01
description Stock is one of the investment instruments that is very popular among investors. One indicator of stock price movements in Indonesia is the Jakarta Composite Index (JCI). JCI data is a time series data about joint stock prices which can be analyzed by time series analysis method. However, with this method there are assumptions that cannot be fulfilled. In this study, JCI data will be analyzed by a nonparametric method namely kernel regression with Nadaraya-Watson estimator. The weekly JCI closing price data from January 2015 to December 2015 is applied using various kernel functions that minimize the value of cross validation to get the optimal bandwidth. The results show that the biweight kernel regression with Mean Square Error = 9030,63 and bandwidth = 108,2 is the best model for predictions.
topic Bandwidth
Jakarta Composite Index
Kernel Regression
Nadaraya-Watson Estimator
Time Series Analysis
url https://ejournal.unisba.ac.id/index.php/statistika/article/view/4775
work_keys_str_mv AT nurazizahkomararifai pendekatanregresinonparametrikkernelpadadataindekshargasahamgabungan
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