Comparative Study of Box-Jenkins ARIMA and KNN Algorithm for Stock Price Prediction in Pakistan.
Stock market is considered a vital part of modern economic systems in the world. The fluctuation in the stock prices is of complex nature because multiple causative factors control these movements. This study was carried out to forecast the stock prices by applying two different techniques of kneare...
| Publicado en: | Journal of Social Sciences & Humanities (1994-7046) Vol. 30; no. 1; pp. 101 - 123 |
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| Autores principales: | , |
| Formato: | Artículo |
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Allama Iqbal Open University
Spring2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=164714475&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 164714475 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 19947046 BESN jtl: Journal of Social Sciences & Humanities (1994-7046) issn: 19947046 maglogo: N pubinfo: dt: Spring2022 vid: 30 iid: 1 pid: 67612 pub: Allama Iqbal Open University artinfo: ui: 164714475 ppf: 101 ppct: 22 formats: fmt: @attributes: type: P size: 5.8MB tig: atl: Comparative Study of Box-Jenkins ARIMA and KNN Algorithm for Stock Price Prediction in Pakistan. aug: au: Ahmad, Bilal Zakria, Muhammad affil: Allama Iqbal Open University, Islamabad Associate Professor, Allama Iqbal Open University, Islamabad su: Pakistan Stock Exchange Ltd. K-nearest neighbor classification Stock prices Stock price forecasting Box-Jenkins forecasting Standard deviations Pakistan sug: subj: Pakistan Pakistan Stock Exchange Ltd. K-nearest neighbor classification Stock prices Stock price forecasting Box-Jenkins forecasting Standard deviations keyword: ARIMA Forecasting KNN algorithm Pakistan Stock Exchange ab: Stock market is considered a vital part of modern economic systems in the world. The fluctuation in the stock prices is of complex nature because multiple causative factors control these movements. This study was carried out to forecast the stock prices by applying two different techniques of knearest neighbors algorithm and Box-Jenkins ARIMA to compare their effectiveness. Three major contributing companies in Pakistan Stock Exchange were selected and the daily stock price data during the period 2014-2018 were used. In the first phase, Box-Jenkins methodology was adopted to build parsimonious ARIMA model for each series separately. The k-nearest neighbors algorithm was also performed and forecasts were calculated. Lastly, Root Mean Square Error, Mean Absolute Error and Mean Absolute Percentage Error were used for comparison purpose of both techniques. It was observed that machine learning technique of k-nearest neighbors algorithm provided more accurate results as compared to ARIMA. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Journal of Social Sciences & Humanities (1994-7046) is the property of Allama Iqbal Open University and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Journal of Social Sciences & Humanities (1994-7046) holder: Allama Iqbal Open University dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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