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## RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction

#### Eren UNLU [1]

We present a novel intuitive graphical representation for daily stock prices, which we refer as RGBSticks, a variation of classical candle sticks. This representation allows the usage of complex deep learning based techniques, such as deep convolutional autoencoders and deep convolutional generative adversarial networks to produce insightful visualizations for market's past and future states. We believe RGBStick representation has great potential to integrate human decision process and deep learning for stock market analysis and forecasting. The traders who are highly familiar with candlesticks are able to evaluate the results generated by deep learning algorithms by inspecting the varying color shades in a compact, instinctual and rapid fashion
artificial intelligence, stock market, time series
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Birincil Dil en Bilgisayar Bilimleri, Yapay Zeka Research Articles Yazar: Eren UNLU (Sorumlu Yazar)Kurum: supelecÜlke: France Başvuru Tarihi : 22 Eylül 2020 Kabul Tarihi : 9 Ekim 2020 Yayımlanma Tarihi : 29 Aralık 2020
 Bibtex @araştırma makalesi { jscai798545, journal = {Journal of Soft Computing and Artificial Intelligence}, issn = {2717-8226}, address = {Tecde Mah. Gulay Sok. No 6:10/Malatya}, publisher = {Mahmut DİRİK}, year = {2020}, volume = {1}, pages = {82 - 89}, doi = {}, title = {RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction}, key = {cite}, author = {Unlu, Eren} } APA Unlu, E . (2020). RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction . Journal of Soft Computing and Artificial Intelligence , 1 (2) , 82-89 . Retrieved from https://dergipark.org.tr/tr/pub/jscai/issue/56697/798545 MLA Unlu, E . "RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction" . Journal of Soft Computing and Artificial Intelligence 1 (2020 ): 82-89 Chicago Unlu, E . "RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction". Journal of Soft Computing and Artificial Intelligence 1 (2020 ): 82-89 RIS TY - JOUR T1 - RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction AU - Eren Unlu Y1 - 2020 PY - 2020 N1 - DO - T2 - Journal of Soft Computing and Artificial Intelligence JF - Journal JO - JOR SP - 82 EP - 89 VL - 1 IS - 2 SN - 2717-8226- M3 - UR - Y2 - 2020 ER - EndNote %0 Journal of Soft Computing and Artificial Intelligence RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction %A Eren Unlu %T RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction %D 2020 %J Journal of Soft Computing and Artificial Intelligence %P 2717-8226- %V 1 %N 2 %R %U ISNAD Unlu, Eren . "RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction". Journal of Soft Computing and Artificial Intelligence 1 / 2 (Aralık 2020): 82-89 . AMA Unlu E . RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction. JSCAI. 2020; 1(2): 82-89. Vancouver Unlu E . RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction. Journal of Soft Computing and Artificial Intelligence. 2020; 1(2): 82-89. IEEE E. Unlu , "RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction", Journal of Soft Computing and Artificial Intelligence, c. 1, sayı. 2, ss. 82-89, Ara. 2021

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