Forecasting MDPI

08/11/2024

📢Highly Cited Paper in
Title: " the in in "
✍️by Jakub Horák and Michaela Jannová

The price of oil is nowadays a hot topic as it affects many areas of the world economy. The price of oil also plays an essential role in how the economic situation is currently developing (such as the COVID-19 pandemic, inflation and others) or the political situation in surrounding countries. The p...

08/11/2024

📢Highly Cited Paper in

Title: "Improvement on of of the COVID-19 through Combining Oscillations in "
✍️by Eunju Hwang

Daily data on COVID-19 infections and deaths tend to possess weekly oscillations. The purpose of this work is to forecast COVID-19 data with partially cyclical fluctuations. A partially periodic oscillating ARIMA model is suggested to enhance the predictive performance. The model, optimized for impr...

07/11/2024

📢New Publication in
📖Transforming with - : Innovations in and Supply Chain Optimization
✍️by Sambandh Bhusan Dhal and Debashish Kar

Global food security is under significant threat from climate change, population growth, and resource scarcity. This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming ...

07/11/2024

📢New Publication in
📖Does Improve the of ?
✍️by Ilsé Botha and Andrea Saayman

Research shows that Google Trend indices can improve tourism-demand forecasts. Given the impact of the recent pandemic, this may prove to be an important predictor of tourism recovery in countries that are still struggling to recover, including South Africa. The purpose of this paper is firstly, to ...

06/11/2024

📢New Publication in
📖Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory
✍️by Kgothatso Makubyane and Daniel Maposa

This study investigates wind speed prediction using advanced machine learning techniques, comparing the performance of Vanilla long short-term memory (LSTM) and convolutional neural network (CNN) models, alongside the application of extreme value theory (EVT) using the r-largest order generalised ex...

06/11/2024

📢New Publication in
📖Climate Risks and Real Gold Returns over 750 Years
✍️by Rangan Gupta, Anandamayee Majumdar, Christian Pierdzioch and Onur Polat

Using data that cover the annual period from 1258 to 2023, we studied the link between real gold returns and climate risks. We documented a positive contemporaneous link and a negative predictive link. Our findings further show that the predictive link historically gave rise to significant out-of-sa...

05/11/2024

📢New Publication in
📖Using Machine Deep Learning AI to Improve Forecasting of Tax Payments for Corporations
✍️by Charles Swenson

This paper aims to demonstrate how machine deep learning techniques lead to relatively accurate forecasts of quarterly corporate income tax payments. Using quarterly data from Compustat for all U.S. publicly traded corporations from 2000 to 2024, I show that neural nets, the tree method, and random ...

05/11/2024

📢New Publication in

📖A Foresight Framework for the Labor Market with Special Reference to Managerial Roles—Toward Diversified Skill Portfolios

✍️by Anna-Maria Kanzola and Panagiotis E. Petrakis

This study introduces a methodology for labor market foresight through alternative futures. It discusses three alternative scenarios for managerial roles, each exploring varying levels of technological advancement and economic growth, to provide insights into the evolving demands for managerial role...

04/11/2024

📢 Special Issue " of 2024", edited by Prof. Dr. Sonia Leva, is open for submissions in Forecasting MDPI

https://www.mdpi.com/journal/forecasting/special_issues/QC918GFBDS

📆 31 December 2024

04/11/2024

📢 Special Issue " : Trends and Forecasting", edited by Prof. Dr. Julien Chevallier, is open for submissions in Forecasting MDPI

https://www.mdpi.com/journal/forecasting/special_issues/green_finance_forecasting

📆 1 December 2024

01/11/2024

📢Most Viewed Paper in
📖 Models for Using with Gradient-Specific Optimization
✍️by Amina Ladhari and Heni Boubaker

Since cryptocurrencies are among the most extensively traded financial instruments globally, predicting their price has become a crucial topic for investors. Our dataset, which includes fluctuations in Bitcoin’s hourly prices from 15 May 2018 to 19 January 2024, was gathered from Crypto Data Downl...

01/11/2024

📢Most Viewed Paper in
📖Can Enhance Accuracy of Learning Models? A Case of Approach
✍️by C. Tamilselvi, Md Yeasin, Ranjit Kumar Paul and Amrit Kumar Paul

Denoising is an integral part of the data pre-processing pipeline that often works in conjunction with model development for enhancing the quality of data, improving model accuracy, preventing overfitting, and contributing to the overall robustness of predictive models. Algorithms based on a combina...

31/10/2024

📢Most Viewed Paper in
📖A Composite Tool for Forecasting El Niño: The Case of the 2023–2024 Event
✍️by Costas Varotsos, Nicholas V. Sarlis, Yuri Mazei, Damir Saldaev and Maria Efstathiou

https://bit.ly/3AmpcvM

Remotely sensed data play a crucial role in monitoring the El Niño/La Niña Southern Oscillation (ENSO), which is an oceanic-atmospheric phenomenon occurring quasi-periodically with several impacts worldwide, such as specific biological and global climate responses. Since 1980, Earth has witnessed ...

31/10/2024

Article

"Systematic Assessment of the Effects of Space Averaging and Time Averaging on Weather Forecast Skill"

https://www.mdpi.com/2571-9394/4/4/52

Intuitively, one would expect a more skillful forecast if predicting weather averaged over one week instead of the weather averaged over one day, and similarly for different spatial averaging areas. However, there are few systematic studies of averaging and forecast skill with modern forecasts, and....

30/10/2024

Article

"Spatial Dependence of Average Prices for Product Categories and Its Change over Time: Evidence from Daily Data"

https://www.mdpi.com/2571-9394/5/1/4

The price of market products is the result of the interaction of supply and demand. However, within the same country, prices can vary significantly, especially during crisis periods. The purpose of this study is to identify patterns in the changing spatial dependence of the prices of certain product...

30/10/2024

Article

"Switching Coefficients or Automatic Variable Selection: An Application in Forecasting Commodity Returns"

https://www.mdpi.com/2571-9394/4/1/16

In this paper, we conduct a thorough investigation of the predictive ability of forward and backward stepwise regressions and hidden Markov models for the futures returns of several commodities. The predictive performance relative a standard AR(1) benchmark is assessed under both statistical and eco...

29/10/2024

Article

"Solving Linear Integer Models with Variable Bounding"

https://www.mdpi.com/2571-9394/5/2/24

We present a technique to solve the linear integer model with variable bounding. By using the continuous optimal solution of the linear integer model, the variable bounds for the basic variables are approximated and then used to calculate the optimal integer solution. With the variable bounds of the...

29/10/2024

Article

"Shrinking the Variance in Experts’ “Classical” Weights Used in Expert Judgment Aggregation"

https://www.mdpi.com/2571-9394/5/3/29

Mathematical aggregation of probabilistic expert judgments often involves weighted linear combinations of experts’ elicited probability distributions of uncertain quantities. Experts’ weights are commonly derived from calibration experiments based on the experts’ performance scores, where perf...