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Bio
Jorge Caiado, after receiving his Ph.D. in Applied Mathematics to Economics and Management from the Technical University of Lisbon, joined the School of Economics and Management at Technical University of Lisbon where he is currently Professor of Econometrics and Time Series Analysis. From 1995 to 2003 he was Lecture at the Portuguese Bank Training Institute. During 2004-2005, he was visiting researcher of the Department of Statistics at University Carlos III of Madrid (Spain). He is now Vice-President of the Centre for Applied Mathematics and Economics (CEMAPRE) and member of the American Statistical Association (ASA). His research in econometrics, finance, time series analysis, forecasting methods and statistical software (EViews, Stata, and Lingo) has led to numerous publications in journals such as Quantitative Finance, Computational Statistics & Data Analysis, Management Decision, Journal of Business Economics and Management, Journal of Statistical Computation and Simulation, Communications in Statistics: Simulation and Computation, Physica A: Statistical Mechanics and its Applications, Journal of Hydrologic Engineering, Portuguese Journal of Management Studies, and others. He is also author and co-author of several books and chapters in books such as “Classification and Clustering of Time Series” (Lambert Academic Publishing, 2010), “Computational Statistics” (Physica-Verlag, 2008), “Recent Advances in Stochastic Modeling and Data Analysis” (World Scientific Publishing, 2007), "Handbook of Cluster Analysis (Taylor & Francis , in press). He is serving as econometric and statistical consultant and trainer for numerous companies and organizations including central banks, commercial and investment banks, bureau of statistics, bureau of economic analysis, transportation and logistic companies, health companies and insurance companies.
Research Interests
Papers共 65 篇Author StatisticsCo-AuthorSimilar Experts
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APPLIED ECONOMICSno. 24 (2024): 2915-2930
The North American Journal of Economics and Finance (2023): 101971-101971
crossref(2023)
Development Studies Researchno. 1 (2021): 181-198
Time Series Clustering and Classificationpp.68-110, (2019)
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