Amid concerns about financial social responsibility, the significance of ethical standards in
trading has grown. Recent years have seen increased focus on exploring diverse ethics in …

Purpose The study aims to explore how integrating recent fundamental values (RFVs) from
conventional accounting studies enhances the accuracy of a machine learning (ML) model …

Integrating machine learning and data mining is crucial for processing big data and
extracting valuable insights to enhance decision-making. However, imbalanced target …

A new Forex multi-criteria trading model based on the Belief-Plausibility (B el− P l) extension
is developed and validated. The B el− P l approach is, in fact, a meta-theory in relation to the …

This study evaluates the performance of 41 machine learning models, including 21
classifiers and 20 regressors, in predicting Bitcoin prices for algorithmic trading. By …

In a company, operational performance must be achieved to fulfill the company's strategy.
The main objective of this systematic literature review is to explore and identify the role of …

Research background: Big data-driven artificial Internet of Things (IoT) fintech algorithms
can provide real-time personalized financial service access, strengthen risk management …

Artificial intelligence plays a crucial role in financial sectors, especially in investment
planning. It enhanced or replaced traditional investment planning by applying AI techniques …

This study aims to develop a dynamic portfolio trading system for high-risk profiles of
cryptocurrencies in two phases: 1) portfolio selection and 2) portfolio construction. In the first …

Abstract “Asset pricing” in the context of financial economics pertains to the investigation and
formulation of two fundamental pricing ideas and the models that go along with them …