Autocorrelation for time series with linear trend
dc.contributor.author | Kamalov, Firuz | |
dc.contributor.author | Thabtah, Fadi | |
dc.contributor.author | Gurrib, Ikhlaas | |
dc.date.accessioned | 2021-12-29T10:37:55Z | |
dc.date.available | 2021-12-29T10:37:55Z | |
dc.date.copyright | © 2021 | |
dc.date.issued | 2021-09-29 | |
dc.description | This conference paper is not available at CUD collection. The version of scholarly record of this conference paper is published in2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2021 (2021), available online at: https://doi.org/10.1109/3ICT53449.2021.9581809 | en_US |
dc.description.abstract | The autocorrelation function (ACF) is a fundamental concept in time series analysis including financial forecasting. In this note, we investigate the properties of the sample ACF for a time series with linear trend. In particular, we show that the sample ACF of the time series approaches 1 for all lags as the number of time steps increases. The theoretical results are supported by numerical experiments. Our result helps researchers better understand the ACF patterns and make correct ARMA selection. © 2021 IEEE. | en_US |
dc.identifier.citation | Kamalov, F., Thabtah, F., & Gurrib, I. (2021). Autocorrelation for time series with linear trend. Paper presented at the 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2021, 181-185. https://doi.org/10.1109/3ICT53449.2021.9581809 | en_US |
dc.identifier.isbn | 978-166544032-5 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12519/486 | |
dc.identifier.uri | https://doi.org/10.1109/3ICT53449.2021.9581809 | |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation | Authors Affiliations : Kamalov, F., Canadian University Dubai, Department of Electrical Engineering, Dubai, United Arab Emirates; Thabtah, F., School of Digital Technologies, Manukau Institute of Technology, Manukau, New Zealand; Gurrib, I., Canadian University Dubai, Department of Finance, Dubai, United Arab Emirates | |
dc.relation.ispartofseries | 2021 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2021; | |
dc.rights | Permission to reuse abstract has been secured from Institute of Electrical and Electronics Engineers Inc. | |
dc.rights.holder | Copyright : Copyright : © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |
dc.rights.uri | https://www.ieee.org/publications/rights/rights-policies.html | |
dc.subject | acf | en_US |
dc.subject | arima | en_US |
dc.subject | autocorrelation | en_US |
dc.subject | forecasting | en_US |
dc.subject | linear trend | en_US |
dc.subject | time series | en_US |
dc.title | Autocorrelation for time series with linear trend | en_US |
dc.type | Conference Paper | en_US |
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