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The data used in the predictive model consists of 1-hour past price values of 4 different currency pairs, between 2003 and 2016. Prediction performances of state-of-the-art methods; Extreme Gradient Boosting, Artificial Neural Network and Support Vector Machines are compared over the same data with the same sets of features. Results show that density based visual features contribute considerably to prediction performance.<\/jats:p>","DOI":"10.4018\/ijcini.2020040104","type":"journal-article","created":{"date-parts":[[2020,2,28]],"date-time":"2020-02-28T07:51:44Z","timestamp":1582876304000},"page":"61-76","source":"Crossref","is-referenced-by-count":3,"title":["Exploiting Visual Features in Financial Time Series Prediction"],"prefix":"10.4018","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2179-2417","authenticated-orcid":true,"given":"Adil G\u00fcrsel","family":"Kara\u00e7or","sequence":"first","affiliation":[{"name":"Atilim University, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Turan Erman","family":"Erkan","sequence":"additional","affiliation":[{"name":"Atilim University, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"issue":"6","key":"IJCINI.2020040104-0","first-page":"264","article-title":"A Quantitative Performance Evaluation Model Based on a Job Satisfaction - Performance Matrix and Application in a Manufacturing Company.","volume":"19","author":"A.Aktepe","year":"2012","journal-title":"International Journal of Industrial Engineering"},{"key":"IJCINI.2020040104-1","doi-asserted-by":"publisher","DOI":"10.1093\/rfs\/12.2.405"},{"key":"IJCINI.2020040104-2","doi-asserted-by":"publisher","DOI":"10.1093\/rfs\/hhm055"},{"key":"IJCINI.2020040104-3","unstructured":"Chandler, M. 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