Background When you make a forex transaction, you sell one currency and buy another. If
the currency you buy increases against the currency you sell, you profit, and you do this …

The main objective of the present work is to estimate the load-carrying capacity of concrete-
filled steel tubes (CFST) under axial compression using hybrid artificial intelligence (AI) …

The prediction of a volatile stock market is a challenging task. While various neural networks
are integrated to address stock trend prediction problems, the weight initialization of such …

1. Executive summary This discussion document follows upon work led by the ACPR on
Artificial Intelligence (AI) since 2018. In March 2019, after an initial report and a first public …

The relationships between crude oil prices and exchange rates have always been of interest
to academics and policy analysts. There are theoretical transmission channels that justify …

Support vector regression is a promising method for time-series prediction, as it has good
generalisability and an overall stable behaviour. Recent studies have shown that it can …

Recent crises, recessions and bubbles have stressed the non-stationary nature and the
presence of drastic structural changes in the financial domain. The most recent literature …

The paper explores the potential role of Machine learning (ML) in supporting the
development of a company's Performance Management System (PMS). In more details, it …

This research paper explores the performance of Machine Learning (ML) algorithms and
techniques that can be used for financial asset price forecasting. The prediction and …

This article considers nine different predictive techniques, including state-of-the-art machine
learning methods for forecasting corporate bond yield spreads with other input variables. We …