{"title":"单变量时间序列动态建模与预测的ARIMA模型——以摩洛哥通货膨胀率为例","authors":"Jouilil Youness, Mentagui Driss","doi":"10.1109/ISCV54655.2022.9806073","DOIUrl":null,"url":null,"abstract":"The objective of this research paper is to compute the Autoregressive Integrated Moving Average model ARIMA(p,d,q) to forecast the dynamic of the Moroccan inflation rate. To this end, we have used the Box Jenkins approach on historical information series.Empirical findings revealed that ARIMA’s adapted specification is raised as an ARIMA (0,1,1) since its model provides better forecasting for our target process. This model could be utilized to forecast the future inflation rate. This result can be used by public decision-makers to better adapt their future decisions to the country’s economic situation.","PeriodicalId":426665,"journal":{"name":"2022 International Conference on Intelligent Systems and Computer Vision (ISCV)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"An ARIMA Model for Modeling and Forecasting the Dynamic of Univariate Time Series: The case of Moroccan Inflation Rate\",\"authors\":\"Jouilil Youness, Mentagui Driss\",\"doi\":\"10.1109/ISCV54655.2022.9806073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this research paper is to compute the Autoregressive Integrated Moving Average model ARIMA(p,d,q) to forecast the dynamic of the Moroccan inflation rate. To this end, we have used the Box Jenkins approach on historical information series.Empirical findings revealed that ARIMA’s adapted specification is raised as an ARIMA (0,1,1) since its model provides better forecasting for our target process. This model could be utilized to forecast the future inflation rate. This result can be used by public decision-makers to better adapt their future decisions to the country’s economic situation.\",\"PeriodicalId\":426665,\"journal\":{\"name\":\"2022 International Conference on Intelligent Systems and Computer Vision (ISCV)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Intelligent Systems and Computer Vision (ISCV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCV54655.2022.9806073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Systems and Computer Vision (ISCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCV54655.2022.9806073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An ARIMA Model for Modeling and Forecasting the Dynamic of Univariate Time Series: The case of Moroccan Inflation Rate
The objective of this research paper is to compute the Autoregressive Integrated Moving Average model ARIMA(p,d,q) to forecast the dynamic of the Moroccan inflation rate. To this end, we have used the Box Jenkins approach on historical information series.Empirical findings revealed that ARIMA’s adapted specification is raised as an ARIMA (0,1,1) since its model provides better forecasting for our target process. This model could be utilized to forecast the future inflation rate. This result can be used by public decision-makers to better adapt their future decisions to the country’s economic situation.