@conference {Berradi2020367,
	title = {A comprehensive review of artificial intelligence techniques in financial market},
	booktitle = {Colloquium in Information Science and Technology, CIST},
	volume = {2020-June},
	year = {2020},
	note = {cited By 0},
	pages = {367-371},
	abstract = {Artificial intelligence is a vast and promising domain that helps improving people{\textquoteright}s lives in different areas such as, medicine, education, telecommunication, finance, and economy. The financial market is an important aspect of the economics of any country, by having a clear idea about how it functions, it helps to improve the economy of the country radically and, therefore, the people{\textquoteright}s lives. In this paper, we suggest giving the latest research of deep learning techniques applied on the financial market field that can help investors to make an accurate decision. This paper gathered all the recent articles related to deep learning techniques applied on forecasting the financial market, which includes stock market, stock index, commodity forecasting and Forex. The main goal is to find the most models used recently to solve the prediction problem using RNN, their characteristic and novelty. We will give all aspects that involve the process of forecasting beginning with preprocessing, the input features, the deep learning techniques, and the evaluation metrics employed. {\textcopyright} 2021 IEEE.},
	keywords = {Artificial intelligence techniques, Commerce, Deep learning, Electronic trading, Evaluation metrics, Financial markets, Fintech, Forecasting, Input features, Investments, It functions, Learning systems, Learning techniques, Prediction problem, Stock indices},
	doi = {10.1109/CiSt49399.2021.9357175},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103852221\&doi=10.1109\%2fCiSt49399.2021.9357175\&partnerID=40\&md5=b8ae02858f3f66114efcfced0ae9f173},
	author = {Berradi, Z. and Lazaar, M. and Mahboub, O. and Omara, H.}
}
