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In this article, we challenge this existing notion of the literature and propose an online kernel adaptive filtering\u2010based approach to predict stock prices. We experiment with ten different KAF algorithms to analyze stocks\u2019 performance and show the efficacy of the work presented here. In addition to this, and in contrast to the current literature, we look at granular level data. The experiments are performed with quotes gathered at the window of one minute, five minutes, ten minutes, fifteen minutes, twenty minutes, thirty minutes, one hour, and one day. These time windows represent some of the common windows frequently used by traders. The proposed framework is tested on 50 different stocks making up the Indian stock index: Nifty\u201050. The experimental results show that online learning and KAF is not only a good option, but practically speaking, they can be deployed in high\u2010frequency trading as well.<\/jats:p>","DOI":"10.1155\/2021\/6400045","type":"journal-article","created":{"date-parts":[[2021,12,18]],"date-time":"2021-12-18T04:20:08Z","timestamp":1639801208000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9593-4820","authenticated-orcid":false,"given":"Shambhavi","family":"Mishra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0732-3016","authenticated-orcid":false,"given":"Tanveer","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3649-1388","authenticated-orcid":false,"given":"Vipul","family":"Mishra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6259-2046","authenticated-orcid":false,"given":"Manjit","family":"Kaur","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4539-4475","authenticated-orcid":false,"given":"Thomas","family":"Martinetz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7939-7810","authenticated-orcid":false,"given":"Amit Kumar","family":"Jain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9942-8642","authenticated-orcid":false,"given":"Hammam","family":"Alshazly","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,12,17]]},"reference":[{"volume-title":"Prediction Machines: The Simple Economics of Artificial Intelligence","year":"2018","author":"Agrawal A.","key":"e_1_2_8_1_2"},{"key":"e_1_2_8_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2009.12.020"},{"key":"e_1_2_8_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.12.030"},{"key":"e_1_2_8_4_2","unstructured":"AbrahamA. 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