… This study utilized the forecasts as signals for stock dealing. The outcomes revealed that
the HMM functioned better than the naïve approach in stock price predicting. Furthermore, the …

… the learning ability between deep learning and classical machine learning methods in the
Chinese A-share market… They train models with price data and technical indicators, and …

… to conventional machine learning algorithms. In this paper, financial product price data are
… object in the experiments conducted in this study and trading days are used as observation …

… the stock market’s characteristics of noise and volatility. To address these challenges, we
propose a deep learning-based stock market … Therefore, the study of stock forecasts can guide …

… machine learning. A large number of areas remain in bank risk management that could
significantly benefit from the study of how machine learning … in the financial markets is important …

… That is the case, for example, when analyzing transactions in financial markets, and the costs
of … Addressing bias in machine learning algorithms: A pilot study on emotion recognition for …

… years, Machine Learning and especially its subfield Deep Learning have … the survey with a
short summary about the trend in this research and … 2 Machine Learning and Deep Learning …

… In this paper, we offer a review on attack detection methods involving strength of deep
learning … related applications using deep learning structure. On the basis of categorization on …

… analysis approaches based on deep learning are reviewed. … The focus of this research
was the deep learning approach; … study of the performance of the three most popular deep …

… market values. The main objective of this paper is to see in which precision a Machine learning
algorithm can … Also, some study has covered a large number of trends and Applications of …