{"title":"基于自动回归综合移动平均(ARIMA)模型的马鲁蒂铃木股价预测","authors":"K. Khan, Dileep Singh","doi":"10.1177/09728686221099285","DOIUrl":null,"url":null,"abstract":"Forecasting of stock prices is a very important subject in the financial world and economics. For many years, investors have been interested in making better forecasting models. The autoregressive integrated moving average (ARIMA) model was used previously for time series forecasting. This article shows the process of stock price forecasting using an ARIMA model. Historical stock data for analysis is obtained from the National Stock Exchange (NSE) and is used along with the stock price for forecasting using an ARIMA model. The result obtained from an ARIMA model is better for short-term forecasting and can be proven with existing methods for stock price prediction.","PeriodicalId":399076,"journal":{"name":"Review of Professional Management","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Stock Price Forecasting of Maruti Suzuki using Auto Regressive Integrated Moving Average (ARIMA) Model\",\"authors\":\"K. Khan, Dileep Singh\",\"doi\":\"10.1177/09728686221099285\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forecasting of stock prices is a very important subject in the financial world and economics. For many years, investors have been interested in making better forecasting models. The autoregressive integrated moving average (ARIMA) model was used previously for time series forecasting. This article shows the process of stock price forecasting using an ARIMA model. Historical stock data for analysis is obtained from the National Stock Exchange (NSE) and is used along with the stock price for forecasting using an ARIMA model. The result obtained from an ARIMA model is better for short-term forecasting and can be proven with existing methods for stock price prediction.\",\"PeriodicalId\":399076,\"journal\":{\"name\":\"Review of Professional Management\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Review of Professional Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/09728686221099285\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Professional Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/09728686221099285","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stock Price Forecasting of Maruti Suzuki using Auto Regressive Integrated Moving Average (ARIMA) Model
Forecasting of stock prices is a very important subject in the financial world and economics. For many years, investors have been interested in making better forecasting models. The autoregressive integrated moving average (ARIMA) model was used previously for time series forecasting. This article shows the process of stock price forecasting using an ARIMA model. Historical stock data for analysis is obtained from the National Stock Exchange (NSE) and is used along with the stock price for forecasting using an ARIMA model. The result obtained from an ARIMA model is better for short-term forecasting and can be proven with existing methods for stock price prediction.