Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

Traditional machine learning methods suffer from the curse of dimensionality. Here, Ryan Samson, Jeffrey Berger, Luca Candelori, Vahagn Kirakosyan, Kharen Musaelian and Dario Villani introduce a novel ...

One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a ...

Modern forex trading heavily depends on advanced analytics, machine learning, and real-time data processing. Big data platforms are boosting forecasting ...

Dengue is a mosquito-borne disease which infects about 390 million people globally each year. Case numbers have grown ...

The goal of this paper is to forecast future firm performance with machine learning techniques. Using data on over one million Japanese firms with supply-chain linkage information provided by a credit ...