ISSN 3057-6601 · Diamond Open Access · No APCs
JDMFID · ISSN 3057-6601

Journal of Dependence Modelling in Finance, Insurance and Demography

An international Diamond Open Access scholarly journal for dependence modelling and quantitative research across finance, insurance, actuarial science and demography.

  • ISSN 3057-6601
  • Diamond Open Access
  • No APCs
  • Double-Blind Peer Review
  • Authors Retain Copyright
  • CC BY 4.0
Inaugural Issue

Volume 1, Issue 1 (2026)

Published

The journal's first published issue presents five openly available scholarly articles in dependence modelling across finance, insurance and demography.

Journal at a Glance

Journal
Journal of Dependence Modelling in Finance, Insurance and Demography
Abbreviation
JDMFID
ISSN
3057-6601
Access
Diamond Open Access
Submission Fee
€0
Publication Fee
€0
APC
€0
Peer Review
Double-Blind External Peer Review
Language
English
Publisher
Anastasios-Tsampikos Statiou – Independent Scholarly Publisher
Place of Publication
Rhodes, Greece
Copyright
Authors retain copyright
Licence
CC BY 4.0

Why Publish with JDMFID?

Diamond Open Access

No submission charges, publication fees or Article Processing Charges.

External Peer Review

Research manuscripts undergo independent scholarly peer review according to the journal's editorial policies.

Authors Retain Copyright

Authors retain copyright to their scholarly work.

Open Licensing

Published articles are distributed under CC BY 4.0 unless otherwise stated.

Interdisciplinary Scope

The journal connects finance, insurance, actuarial science, statistics, mortality, demography and dependence modelling.

Reproducible Research

JDMFID encourages transparent methodology, reproducible analysis, code and research data where appropriate.

Journal Focus

The journal welcomes theoretical, methodological, computational and applied research within the following areas.

Dependence Modelling
Financial Risk
Insurance and Actuarial Science
Demographic Statistics
Mortality and Longevity
Survival Analysis
Systemic Risk
Risk Forecasting
Reproducible Computational Methods