{"title":"基于决策树的汽车行业股价走势预测","authors":"","doi":"10.35940/ijrte.f9882.059120","DOIUrl":null,"url":null,"abstract":"The auto sector stock price trend is based on many national and international uncertain factors. It is challenging to predict the impact of such a factor on the stock price trend as the impact of the same factor varies at different points of time. In this research work, we are predicting the auto sector stock price trend using patterns in the historical data using a machine learning method.","PeriodicalId":220909,"journal":{"name":"International Journal of Recent Technology and Engineering","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Auto Sector Stock Price Trend Prediction using Decision Tree\",\"authors\":\"\",\"doi\":\"10.35940/ijrte.f9882.059120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The auto sector stock price trend is based on many national and international uncertain factors. It is challenging to predict the impact of such a factor on the stock price trend as the impact of the same factor varies at different points of time. In this research work, we are predicting the auto sector stock price trend using patterns in the historical data using a machine learning method.\",\"PeriodicalId\":220909,\"journal\":{\"name\":\"International Journal of Recent Technology and Engineering\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Recent Technology and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35940/ijrte.f9882.059120\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Recent Technology and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35940/ijrte.f9882.059120","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Auto Sector Stock Price Trend Prediction using Decision Tree
The auto sector stock price trend is based on many national and international uncertain factors. It is challenging to predict the impact of such a factor on the stock price trend as the impact of the same factor varies at different points of time. In this research work, we are predicting the auto sector stock price trend using patterns in the historical data using a machine learning method.
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