Computer Sciences & Mathematics Forum, Volume 11, Issue 1

This paper explores the forecasting of aluminum prices using various predictive models dealing with variable uncertainty. A diverse set of economic and market indicators is considered as potential price predictors. The performance of models including...

This study analyzes the evolution of the Mexico–U.S. trade balance as a seasonally adjusted time series, comparing the Hodrick–Prescott (HP) filter and wavelet analysis. The HP filter allowed the trend and cycle to be extracted from the series, while...

Time series forecasting is a cornerstone of decision-making in energy and finance, yet many studies fail to rigorously analyse the underlying dataset characteristics, leading to suboptimal model selection and unreliable outcomes. This paper addresses...

Extreme value theory comprises a set of techniques for inference at the tail of distributions, where data are scarce or non-existent. The tail index is the main parameter, with risk measures such as value at risk or expected shortfall depending on it...

This paper develops a novel entropy-based framework to quantify tail risk and detect speculative bubbles in financial markets. By integrating extreme value theory with information theory, I introduce the Tail-Weighted Entropy (TWE) measure, which cap...

The formulation of touristic policies is a time-consuming process that consists of a wide range of steps and procedures. These policies are highly dependent on the number of tourists and visitors to an area to be as effective as possible. The estimat...

In this work, we propose a nonlinear dynamic inverse solution to the diffusion problem based on Krylov Subspace Methods with spatiotemporal constraints. The proposed approach is applied by considering, as a forward problem, a 1D diffusion problem wit...

Sales forecasting in make-to-order (MTO) production is particularly challenging for small- and medium-sized enterprises (SMEs) due to high product customization, volatile demand, and limited historical data. This study evaluates the practical feasibi...

Demand forecasting is different from traditional forecasting because it is a process of forecasting multiple time series collectively. It is challenging to implement models that can generalise and perform well while forecasting many time series altog...

Oil, as a key commodity in international markets, bears an importance for both producers and consumers. For oil-exporting countries, periodic fluctuations have a considerable impact on the economic status and the way monetary and fiscal policies shou...