Statistics and Risk Management

NOVA Math > Research Groups > Statistics and Risk Management

and Risk Management


The Statistics and Risk Management group activity covers a wide range of subjects that are encompassed in three main research lines: Statistical Inference, Distribution Theory and Actuarial and Financial Mathematics. Within Statistical Inference we study various extensions of linear models with special focus in analysis of variance for models with a random number of observations. Concerning Distribution Theory there are two main research areas: near-exact distributions for likelihood ratio test statistics and extreme value theory. In Actuarial and Financial Mathematics we spread over the classical actuarial problems in risk theory, to new models for pricing and hedging derivative products, passing through Markov chain models applications to credit scoring and insurance bonus-malus models.

Frederico Almeida Gião Gonçalves Caeiro

Statistics and Risk Management Coordinator



Capacity and Internal Resistance of lithium-ion batteries: Full degradation curve prediction from Voltage response at constant Current at discharge
2023, Journal of Power Sources, Ibraheem,R;Strange,C;dos Reis,G
Noncentral Wishart matrices, asymptotic normality of vec and smooth statistics
2023, STATISTICS, Nunes,C;Ferreira,D;Ferreira,SS;Fonseca,M;Oliveira,MM;Mexia,JT
Spectral Analysis for Comparing Bitcoin to Currencies and Assets
2023, Mathematics, Pocelli,MC;Esquível,ML;Krasii,NP
VIII Workshop on Computational Data Analysis and Numerical Methods – Book of abstracts
2023, Polytechnic Institute of Tomar, Grilo, L. M., Nata, A., Grilo, H. L. e Fernandes, M. M.
Health Line Saúde24: An Econometric Spatial Analysis of Its Use
2022, , Simões P., Natário I., Carvalho M.L., Aleixo S., Gomes, S.
Bases de Dados e Big Data
2022, , Isabel Natário & Marta Belchior Lopes
Matrix Multiplication without Size Restrictions
2022, Journal of Mathematics and Statistics Research, Carla Santos, Cristina Dias
Statistical Analysis of Traffic Volume in the 25 de Abril Bridge.
2022, Data Analysis and Related Applications 1 - Computational, Algorithmic and Applied Economic Data Analysis, Caeiro, F., Mateus, A. and Veiga de Almeida, C.
Black Scabbardfish species distribution: Geostatistical Inference under Preferential Sampling
2022, Universidade Leida, Espanha, Simões, P., Carvalho, M.L, Figueiredo, I..,Monteiro, A., Natário, I.;
Using a constructed covariate that accounts for preferential sampling
2022, Universidade Leida, Espanha, Monteiro, A., Carvalho, M.L, Figueiredo, I.., Simões, P., Natário, I.;


HEATMan – Gestão do calor em equipas NRBQ
Exército Português – CINAMIL, Paula Simões
Link Me Up – 1000 ideias
ERASMUS+/União Europeia, Cristina Dias
MoSBurn: Modeling the multifactorial burnout syndrome in college students
FCT - Fundação para a Ciência e a Tecnologia, I.P., Luís Miguel Grilo
Project n.: 2018-1-PL01-KA203-051137 Erasmus + Programme Key Action 2: Strategic Partnerships for higher...
PerMediK: Personalized medicine in chronic kidney disease: improved outcome based on Big Data
COST - European Cooperation in Science and Technology (EU), Marta Belchior Lopes
PrISAEx-Proteção de Infraestruturas Sujeitas a Ações Extremas
Exército Português – CINAMIL, Paula Simões
SHIFT - Sustainability-oriented, Highly-interactive and Innovation-based Framework for Tourism Marketing
FCT - Fundação para a Ciência e a Tecnologia, I.P., Sandra Nunes
SmartVest - Vestuário inteligente para monitorização em tempo real dos parâmetros fisiológicos das Equipas NBQR
Exército Português – CINAMIL, Paula Simões
VOOmics: OMICs approaches to reveal the anticancer properties of Virgin Olive Oil
FCT - Fundação para a Ciência e a Tecnologia, I.P., Marta Belchior Lopes
“OMNI - BE Aware STudent”
ERASMUS+, Cristina Dias


    • Sá Ferreira M, Bispo R (2023). RWgraph: Random Walks on Graphs Representing a Transactional Network. R package version 1.0.0,
    • Caeiro F,  Mateus A (2022). randtests: Testing Randomness in R. R package version 1.0.1,
    • a computational module with the implementation of the exact distribution and approximations for the Bartels randomness test statistic: see Appendix
    • a package with the implementation of the main threshold selection methods: see here