[AISWorld] MFGEI 2024

[diwt at dirf.org]

Second International Conference on Modeling and Forecasting Global 
Economic Issues (MFGEI 2024)
October 17-19, 2024
Tien Giang University, My Tho (Near Ho-Chi-Minh)
Vietnam
www.socio.org.uk/mfgei

The growth of global networks and data-driven analyses have greatly 
fostered the evolution of business and economic services with e-mode 
operations in the past few decades. Recent advances in cloud 
environments, economic indicators, artificial intelligence, and risk 
management have driven the development of the next generation of 
economic services featuring resilient, scalable, reliable, and 
intelligent services across diverse global institutions. The spurt in 
volume and size led to several challenges.

Firstly, the broad adoption of many business and economic platforms 
leads to massive and heterogeneous economic data, which brings enormous 
value and technical challenges. Secondly, decentralising economic 
services creates challenges in reliable and secure services. 
Specifically, existing information granaries across different financial 
services institutions also deteriorate this situation. Thirdly, it is a 
big task to implement resilient, scalable, and automatic financial 
services. Moreover, the recent advent of big financial data processing 
also brings the potential to develop traceable and reliable financial 
services. Thus, fusing the above technologies to accelerate data-based 
intelligent financial services has become a trend.

The global economy has recently witnessed significant structural changes 
that have profoundly impacted how prices are determined on the market. 
Events like market liberalization, adoption of cost-efficiency 
regulation, increased production from large businesses and economic data 
have made the demand and supply less predictable and the prices more 
volatile. Accurately modelling and forecasting financial demand and 
prices have become paramount to financial management groups and 
financial analysts focusing on the economic sector. The statistical 
features of financial data, which follow periodic patterns and exhibit 
spikes, non-constant means, and non-constant variances, render 
forecasting and modelling economic data somewhat of an uphill task. 
Researchers autonomously conduct financial and economic analyses. 
Researchers can evaluate which economic analysis model is more 
appropriate to the task and the robustness of the results obtained.

At this conference, the themes focus on society's unique challenges and 
will present novel solutions for optimizing collaborative and 
forecasting models. More specifically, we aim to welcome papers in the 
following areas:

Economic data analysis
Time Series Models
Volatility Models
Financial Demand Models
Time Series forecasting
Outlook Indicators
Forecast Indicators
Data-driven analysis
Business Cycle Analysis
National Economic Forecasts
Fiscal and monetary policies
Economic Transition
Social Issues
Supply chain studies
Economic Forecasting in different sectors
Regulatory planning and scenario analysis
Risk identification and prioritization

All the accepted papers will be published in the proceedings with ISBN 
and DOI. Selected papers will be published after modification in the 
journals below.

Journal of Digital Information Management

Important Dates

Submission of papers: August 05, 2024
Notification: September 01, 2024
Camera-ready: October 01, 2024
Registration: October 01, 2024
Conference Dates: October 17-19, 2024

Honorary Chair
Dương Văn Hiếu, Tien Giang University, Vietnam

General Chair
Ezendu Ariwa, University of Wales Trinity, UK

Program Chairs
K.Shivachithappa, University of Mysore. India
Rita Li, Hong Kong Shue Yan University. Hong Kong

Program Co-Chair
Pit Pichappan, Digital Information Research Labs, India
P Paramasiviah, Tumkur University, India

Contact- stm at socio.org.uk