Journal of Soft Computing and Artificial Intelligence

Journal of Soft Computing and Artificial Intelligence

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

Yazarlar: Eren UNLU

Cilt 1 , Sayı 2 , 2020 , Sayfalar 78 - 85

Konular:Bilgisayar Bilimleri, Yapay Zeka

Anahtar Kelimeler:Artificial intelligence,Stock market,Time series

Özet: 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


ATIFLAR
Atıf Yapan Eserler
Henüz Atıf Yapılmamıştır

KAYNAK GÖSTER
BibTex
KOPYALA
@article{2020, title={RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction}, volume={1}, number={78–85}, publisher={Journal of Soft Computing and Artificial Intelligence}, author={Eren UNLU}, year={2020} }
APA
KOPYALA
Eren UNLU. (2020). RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction (Vol. 1). Vol. 1. Journal of Soft Computing and Artificial Intelligence.
MLA
KOPYALA
Eren UNLU. RGBSticks : A New Deep Learning Based Framework for Stock Market Analysis and Prediction. no. 78–85, Journal of Soft Computing and Artificial Intelligence, 2020.