ORCID ID: http://orcid.org/0000-0002-0405-1695
Scopus ID: http://www.scopus.com/authid/detail.url?authorId=13103216800
Researcher ID: http://www.researcherid.com/rid/D-4029-2009
IDEAS: http://ideas.repec.org/f/pca349.html
ISEG – School of Economics and Management, University of Lisbon and
CEMAPRE – Centre for Applied Mathematics and Economics
Rua do Quelhas, 6, 1200-781
Lisboa (Portugal)
RECENT SELECTED PUBLICATIONS
ALBINO, A., CAIADO, J. and CRATO, N. (2024). “Time series clustering using fragmented autocorrelations”, Physica A: Statistical Mechanics and its Applications, 650, 129981, https://doi.org/10.1016/j.physa.2024.129981
CAIADO, J. and LÚCIO, F. (2023). “Stock Market Forecasting Accuracy of Asymmetric GARCH Models during the COVID-19 Pandemic”, The North American Journal of Economics and Finance, Elsevier, https://doi.org/10.1016/j.najef.2023.101971
FERNANDES, C., BORGES, M. R., MACOMBE, E. and CAIADO, J. (2023). “Measuring an equilibrium long-run relationship between financial inclusion and monetary stability in Mozambique”, Applied Economics, Taylor & Francis, https://doi.org/10.1080/00036846.2023.2203457, Taylor & Francis.
LÚCIO, F. and CAIADO, J. (2022). "COVID-19 and Stock Market Volatility: A Clustering Approach for S&P 500 Industry Indices", Finance Research Letters, Elsevier, 49, 103141.
GRAÇA, J., CAIADO, J. and CORREIA, R. G. (2022). “On the Values and Attitudes of Economics Student in Portugal”, Revista de Sociologia e Política, 30, 1-19.
BASTOS, J. and CAIADO, J. (2021). “On the classification of financial data with domain agnostic features”, International Journal of Approximate Reasoning, 138, 1-11, Elsevier.
FRANCISCO, P., MOREIRA, S. and CAIADO, J. (2021). “Identifying differences and similarities between donors regarding the long-term allocation of official development assistance”, Development Studies Research, DOI: 10.1080/21665095.2021.1954965.
FERNANDES, C., BORGES, R. and CAIADO, J. (2020). “The Contribution of Digital Financial Services to Financial Inclusion in Mozambique: An ARDL Model Approach”, Applied Economics, Taylor & Francis. DOI: 10.1080/00036846.2020.1808177
ALBUQUERQUE, P, CAIADO, J. and PEREIRA, A. (2020). "Aging population and inflation: Evidence from panel cointegration", Journal of Applied Economics, Taylor & Francis. DOI: 10.1080/15140326.2020.1795518.
GRAÇA, J., CORREIA, R. G. and CAIADO, J. (2020): "Sociopolitical values, attitudes and behaviors of Portuguese economics students", Sociologia, Problemas e Práticas, 92, 111-132.
CAIADO, J., CRATO, N. and PONCELA, P. (2019). "A fragmented-periodogram approach for clustering big data time series", Advances in Data Analysis and Classification, Springer, 14, 117-146.
BOOKS AND CHAPTERS IN BOOKS
CAIADO, J. (2022). Métodos de Previsão em Gestão com Aplicações em Excel, Edições Sílabo, 3ª Edição, Lisboa. Dados em Excel disponíveis em https://silabo.pt/catalogo/gestao-organizacional/livro/metodos-de-previsao-em-gestao/
CAIADO, J. (2010). Classification and Clustering of Time Series, Lambert Academic Publishing, Saarbrücken (Germany). ISBN 978-3-8383-4181-1.
CAIADO, A. C. e J. CAIADO (2018). Gestão de Instituições Financeiras, Edições Sílabo, 3ª Edição, Lisboa.
E.A. MAHARAJ, P. D'URSO and CAIADO, J., (2019). "Time Series Classification and Clustering", CRC Press, Taylor & Francis Group, United States.
CAIADO, J., E.A. MAHARAJ and P. D'URSO (2015). "Time Series Clustering", in Handbook of Cluster Analysis, C. Henning, M. Meila, F. Murtagh, R. Rocci (eds.), 241-263, CRC Press, Taylor & Francis Group.