In this paper, we propose multifactor models for the pan-European Equity Market using a block-bootstrap method and compare the results with those of traditional inferential techniques. The new factors are built from statistical measurements on stock prices - in particular, coefficient of...

We define the nagging predictor, which, instead of using bootstrapping to produce a series of i.i.d. predictors, exploits the randomness of neural network calibrations to provide a more stable and accurate predictor than is available from a single neural network run. Convergence results for the...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies’ expenditures, so even small improvement in new approaches can considerably reduce these items’ total inventory. This paper aims to present a new hybrid forecasting...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies' expenditures, so even small improvement in new approaches can considerably reduce these items' total inventory. This paper aims to present a new hybrid forecasting method...

This paper presents an optimization approach-residual-based bootstrap averaging (RBBA)-for different types of forecast ensembles. Unlike traditional residual-mean-square-error-based ensemble forecast averaging approaches, the RBBA method attempts to find optimal forecast weights in an ensemble...

Suicides represent an encompassing measure of psychological wellbeing, emotional stability as well as life satisfaction, and they have been recently identified by the World Health Organization (WHO) as a major global health concern. The G20 countries represent the powerhouse of global economic...

While there is increasing interest in crypto assets, the credit risk of these exchanges is still relatively unexplored. To fill this gap, we considered a unique dataset of 144 exchanges, active from the first quarter of 2018 to the first quarter of 2021. We analyzed the determinants surrounding...

The purpose of this paper is to compare the accuracy of the three types of models: Autoregressive Integrated Moving Average (ARIMA) models, Holt-Winters models and Neural Network Auto-Regressive (NNAR) models in forcasting the Harmonized Index of Consumer Prices (HICP) for the countries of...

The disruption of supply chain due to Covid-19 and the war in Ukraine, render the prediction of agricultural output a determinant factor of economic life. We consider the predictability of agricultural output based on a set of explanatory variables, that include agricultural input, prices and...