This systematic literature review analyses the recent advances of machine learning and
deep learning in finance. The study considers six financial domains: stock markets, portfolio …

This review explores the dynamic field of predictive modelling for disease outbreaks,
focusing on the data sources, modelling techniques, accuracy, challenges, and future …

Manufacturing is transformed towards smart manufacturing, entering a new data-driven era
fueled by digital technologies. The resulting Smart Manufacturing Systems (SMS) gather …

Portfolio theory underpins portfolio management, a much-researched yet uncharted field.
This research suggests a collective framework combined with the essence of deep learning …

Financial markets are highly complex and volatile; thus, accurate forecasting of such
markets is vital to make early alerts about crashes and subsequent recoveries. People have …

Stock price prediction is a prevalent research field in both industry and academia. There is a
pressing demand to develop a prediction model that captures the pattern of the financial …

Incorporating return prediction in portfolio optimization can make portfolio optimization more
efficient by selecting the stocks expected to perform well in the future. This paper proposes a …

Various deep learning techniques have recently been developed in many fields due to the
rapid advancement of technology and computing power. These techniques have been …

Intelligent forecasting model of stock price is an effective way to obtain ideal investment
returns. Due to the impact of quantitative transactions, traditional forecasting methods face …

This research explores the application of Long Short-Term Memory (LSTM) networks for
stock market analysis and prediction, focusing on four major technology stocks: Apple …