Bankruptcy prediction is currently a widely researched topic, as it typically results from a chain of negative events. Logistic Regression (LR) is one of the standard prediction tools; however, with advances in technology, machine learning (ML) methods are gaining prominence and demonstrating...

Mexico liberalized natural gas prices in 2017 by establishing the National Wholesale Natural Gas Price Index (IPGN). This institutional change created observable conditions where prices could deviate from efficiency. We classified these deviations into three regimes: stability, overestimation...

This paper develops an early warning system for predicting distress for large European banks. Using a novel definition of distress derived from banks' headroom above regulatory requirements, we investigate the performance of three machine learning techniques against the traditional logistic...

The untapped potential of wave energy offers another alternative to diversifying renewable energy sources and addressing climate change by reducing CO2 emissions. However, development costs to mature the technology remain significant hurdles to adoption at scale and the technology often must...

This study evaluates the predictive performance of four models-Decision Tree, Random Forest, Prophet, and LSTM-in forecasting container freight rates, a key metric for strategic decision-making in the shipping industry. To address data heterogeneity, Min-Max normalization was applied, and the...