Combination models are regarded as a popular approach to improve forecasting accuracy.
Determining how to select optimal sub-models from all possible candidate models is …

This paper is devoted to the development of an innovative fragility index designed to capture
comprehensively the dynamics of financial stability during periods characterized by asset …

This paper decomposes the term spread into the expectation and the term premium
components using a fractional integration approach and subsequently uses same with the …

This paper examines the validity of forecasting economic variables by using machine
learning. AI (artificial intelligence) has been improved and entering our society rapidly, and …

We design a novel, nonlinear single-source-of-error model for analysis of multiple business
cycles. The model's specification is intended to capture key empirical characteristics of …

Aiming at the problems that the Chinese Navy still needs experienced support, less staffing,
and lack of intelligent decision-making methods to predict the failure of carrier-based aircraft …

Three combination methods commonly used in tourism forecasting are the simple average
method, the variance-covariance method and the discounted MSFE method. These methods …

[eng] The main objective of this study was to develop a new forecasting method ie
SutteARIMA method. SutteARIMA was developed by using a combination and/or …

Modern American business culture heavily depends on microbusiness. Defined as a specific
type of small business with an online presence and no more than ten employees …

A forecast combination is produced by taking a weighted average of forecasts from different
sources, such as different statistical models. This thesis proposes a novel method for the …