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Amal Al Ali, Ahmed M. Khedr, Magdi El Bannany and Sakeena Kanakkayil
Despite the obvious benefits and growing popularity of Machine Learning (ML) technology, there are still concerns regarding its ability to provide Financial Distress Prediction (FDP). An accurate FDP model is required to avoid financial risk at the lowes...
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Ashish Sedai, Rabin Dhakal, Shishir Gautam, Anibesh Dhamala, Argenis Bilbao, Qin Wang, Adam Wigington and Suhas Pol
The Machine Learning/Deep Learning (ML/DL) forecasting model has helped stakeholders overcome uncertainties associated with renewable energy resources and time planning for probable near-term power fluctuations. Nevertheless, the effectiveness of long-te...
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Abdellilah Nafia, Abdellah Yousfi and Abdellah Echaoui
In recent years, a great deal of attention has been devoted to the use of neural networks in portfolio management, particularly in the prediction of stock prices. Building a more profitable portfolio with less risk has always been a challenging task. In ...
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Muhamad Jumaa, Mohammed Saqib, Arif Attar
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Phuong Lan Le, Anh Tuan Do and Anh Ngoc Pham
This study focused on testing the existence of an apartment price bubble in Hanoi (Vietnam) and on determining the factors that affected it in the period between 2010 and 2021. Using the fundamental factor approach, the authors applied VAR regression usi...
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