S. Supriyanto, Aisyah Putri Utami, Najmah Istikanaah
{"title":"股票价格模型采用ARIMA - GARCH方法(印尼股份有限公司案例研究)","authors":"S. Supriyanto, Aisyah Putri Utami, Najmah Istikanaah","doi":"10.20884/1.jmp.2023.15.1.8658","DOIUrl":null,"url":null,"abstract":"PT Unilever Indonesia's stock price swings. This has a heteroscedasticity impact due to the substantial volatility of stock prices. The Box-Jenkins ARIMA method can produce accurate predictions, but it is less precise when used to predict data that has a heteroscedasticity effect. Therefore, this study uses the ARIMA-GARCH method because this model has the advantage of not seeing heteroscedasticity as a problem but instead using it to create a model. The purpose of this study is to estimate parameters using the ARIMA-GARCH technique to develop the best model using PT Unilever Indonesia's share price data and to forecast PT Unilever Indonesia's share price for the period January 20 to January 28, 2021, using the best ARIMA-GARCH model created. Forecasting results for 7 periods using the best ARIMA-GARCH model are Rp. 7,535.00, Rp. 7,511.00, Rp. 7,497.00, Rp. 7,489.00, and Rp. 7,485, respectively.","PeriodicalId":31699,"journal":{"name":"JMPM Jurnal Matematika dan Pendidikan Matematika","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MODEL PERAMALAN HARGA SAHAM MENGGUNAKAN METODE ARIMA – GARCH (STUDI KASUS SAHAM PT. UNILEVER INDONESIA)\",\"authors\":\"S. Supriyanto, Aisyah Putri Utami, Najmah Istikanaah\",\"doi\":\"10.20884/1.jmp.2023.15.1.8658\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PT Unilever Indonesia's stock price swings. This has a heteroscedasticity impact due to the substantial volatility of stock prices. The Box-Jenkins ARIMA method can produce accurate predictions, but it is less precise when used to predict data that has a heteroscedasticity effect. Therefore, this study uses the ARIMA-GARCH method because this model has the advantage of not seeing heteroscedasticity as a problem but instead using it to create a model. The purpose of this study is to estimate parameters using the ARIMA-GARCH technique to develop the best model using PT Unilever Indonesia's share price data and to forecast PT Unilever Indonesia's share price for the period January 20 to January 28, 2021, using the best ARIMA-GARCH model created. Forecasting results for 7 periods using the best ARIMA-GARCH model are Rp. 7,535.00, Rp. 7,511.00, Rp. 7,497.00, Rp. 7,489.00, and Rp. 7,485, respectively.\",\"PeriodicalId\":31699,\"journal\":{\"name\":\"JMPM Jurnal Matematika dan Pendidikan Matematika\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMPM Jurnal Matematika dan Pendidikan Matematika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.20884/1.jmp.2023.15.1.8658\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMPM Jurnal Matematika dan Pendidikan Matematika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20884/1.jmp.2023.15.1.8658","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MODEL PERAMALAN HARGA SAHAM MENGGUNAKAN METODE ARIMA – GARCH (STUDI KASUS SAHAM PT. UNILEVER INDONESIA)
PT Unilever Indonesia's stock price swings. This has a heteroscedasticity impact due to the substantial volatility of stock prices. The Box-Jenkins ARIMA method can produce accurate predictions, but it is less precise when used to predict data that has a heteroscedasticity effect. Therefore, this study uses the ARIMA-GARCH method because this model has the advantage of not seeing heteroscedasticity as a problem but instead using it to create a model. The purpose of this study is to estimate parameters using the ARIMA-GARCH technique to develop the best model using PT Unilever Indonesia's share price data and to forecast PT Unilever Indonesia's share price for the period January 20 to January 28, 2021, using the best ARIMA-GARCH model created. Forecasting results for 7 periods using the best ARIMA-GARCH model are Rp. 7,535.00, Rp. 7,511.00, Rp. 7,497.00, Rp. 7,489.00, and Rp. 7,485, respectively.