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Jorge Caiado

Personal Details

First Name:Jorge
Middle Name:
Last Name:Caiado
Suffix:
RePEc Short-ID:pca349
https://jcaiado100.wixsite.com/jorgecaiado
CEMAPRE, ISEG Rua do Quelhas, 6 1200 Lisboa Portugal

Affiliation

Centro de Matemática Aplicada à Previsão e Decisão Económica (CEMAPRE)
Research in Economics and Mathematics (REM)
Instituto Superior de Economia e Gestão (ISEG)
Universidade de Lisboa

Lisboa, Portugal
http://cemapre.iseg.ulisboa.pt/
RePEc:edi:cmutlpt (more details at EDIRC)

Research output

as
Jump to: Working papers Articles Chapters

Working papers

  1. Carla Fernandes & Maria Rosa Borges & Esselina Macome & Jorge Caiado, 2021. "The relationship between Financial Inclusion and Monetary Stability in Mozambique: Analysis based on an Error Correction Model (VECM)," Working Papers Department of Economics 2021/01, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
  2. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
  3. António Afonso, & Jorge Caiado, & Miguel St. Aubyn, 2015. "The macro impact of the Portuguese Constitutional Court decisions regarding the budgetary proposals of the Portuguese Budget Law (2012, 2013, 2014)," Working Papers Department of Economics 2015/06, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
  4. J. Augusto Felicio & Eduardo Couto & Jorge Caiado, 2013. "Human capital, social capital and organizational performance: A structural modeling approach," CEMAPRE Working Papers 1302, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  5. Luisa Carvalho & Teresa Costa & Jorge Caiado, 2012. "Determinants of innovation in a small open economy: A multidimensional perspective," CEMAPRE Working Papers 1201, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  6. Joao A. Bastos & Jorge Caiado, 2010. "Recurrence quantification analysis of global stock markets," CEMAPRE Working Papers 1006, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  7. Joao A. Bastos & Jorge Caiado, 2010. "The structure of international stock market returns," CEMAPRE Working Papers 1002, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  8. J. Augusto Felicio & Eduardo Couto & Jorge Caiado, 2009. "Interrelationships between human capital and social capital in small and medium sized firms: The effect of age and sector of activity," CEMAPRE Working Papers 0905, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  9. Antonio Samagaio & Eduardo Couto & Jorge Caiado, 2009. "Sporting, financial and stock market performance in English football: an empirical analysis of structural relationships," CEMAPRE Working Papers 0906, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  10. Jorge Caiado & Nuno Crato, 2009. "Identifying common dynamic features in stock returns," CEMAPRE Working Papers 0902, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  11. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2009. "Comparison of time series with unequal length in the frequency domain," MPRA Paper 15310, University Library of Munich, Germany.
  12. Joao A. Bastos & Jorge Caiado, 2009. "Clustering financial time series with variance ratio statistics," CEMAPRE Working Papers 0904, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  13. Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.
  14. Caiado, Jorge & Crato, Nuno, 2008. "Identifying the evolution of stock markets stochastic structure after the euro," MPRA Paper 6609, University Library of Munich, Germany.
  15. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Comparison of time series with unequal length," MPRA Paper 6605, University Library of Munich, Germany.
  16. Caiado, Jorge, 2007. "Forecasting water consumption in Spain using univariate time series models," MPRA Paper 6610, University Library of Munich, Germany.
  17. Caiado, Jorge & Crato, Nuno, 2007. "A GARCH-based method for clustering of financial time series: International stock markets evidence," MPRA Paper 2074, University Library of Munich, Germany.
  18. Caiado, Jorge & Crato, Nuno, 2007. "Identifying common spectral and asymmetric features in stock returns," MPRA Paper 6607, University Library of Munich, Germany.
  19. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Is there an identity within international stock market volatilities?," MPRA Paper 2069, University Library of Munich, Germany.
  20. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2006. "An interpolated periodogram-based metric for comparison of time series with unequal lengths," MPRA Paper 2075, University Library of Munich, Germany.
  21. Caiado, Jorge & Vieira, Aníbal & Bonito, Ana & Reis, Carlos & Fernandes, Francisco, 2006. "Previsão da eficácia ofensiva do futebol profissional: Um caso Português," MPRA Paper 2185, University Library of Munich, Germany.
  22. Caiado, Jorge & Crato, Nuno, 2005. "Discrimination between deterministic trend and stochastic trend processes," MPRA Paper 2076, University Library of Munich, Germany.
  23. Caiado, Jorge, 2004. "Modelling and forecasting the volatility of the portuguese stock index PSI-20," MPRA Paper 2077, University Library of Munich, Germany.
  24. Caiado, Jorge & Madeira, Paulo, 2002. "Determinantes do desempenho académico nos cursos de contabilidade [Determinants of the academic performance in undergraduate courses of accounting]," MPRA Paper 2199, University Library of Munich, Germany.

Articles

  1. Carla Fernandes & Maria Rosa Borges & Jorge Caiado, 2021. "The contribution of digital financial services to financial inclusion in Mozambique: an ARDL model approach," Applied Economics, Taylor & Francis Journals, vol. 53(3), pages 400-409, January.
  2. Paula C. A. M. de Albuquerque & Jorge Caiado & Andreia Pereira, 2020. "Population aging and inflation: evidence from panel cointegration," Journal of Applied Economics, Taylor & Francis Journals, vol. 23(1), pages 469-484, January.
  3. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
  4. Coelho do Vale, Rita & Verga Matos, Pedro & Caiado, Jorge, 2016. "The impact of private labels on consumer store loyalty: An integrative perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 179-188.
  5. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
  6. Luísa Carvalho & Teresa Costa & Jorge Caiado, 2013. "Determinants of innovation in a small open economy: a multidimensional perspective," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(3), pages 583-600, June.
  7. J. Augusto Felício & Eduardo Couto & Jorge Caiado, 2011. "Human capital and social capital in entrepreneurs and managers of small and medium enterprises," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 13(3), pages 395-420, June.
  8. Bastos, João A. & Caiado, Jorge, 2011. "Recurrence quantification analysis of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1315-1325.
  9. Jorge Caiado & Nuno Crato, 2010. "Identifying common dynamic features in stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 797-807.
  10. Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June.
  11. Jorge Caiado, 2004. "Modelling And Forecasting The Volatility Of The Portuguese Stock Index Psi-20," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 3-21.

Chapters

  1. Rita Coelho Vale & Pedro Verga Matos & Jorge Caiado, 2015. "Do Private Labels Lead to Store Loyalty? An Integrated Framework of Analysis Using a Structural Equation Modeling Approach," Springer Proceedings in Business and Economics, in: Francisco J. Martínez-López & Juan Carlos Gázquez-Abad & Raj Sethuraman (ed.), Advances in National Brand and Private Label Marketing, edition 127, pages 167-175, Springer.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. J. Augusto Felicio & Eduardo Couto & Jorge Caiado, 2013. "Human capital, social capital and organizational performance: A structural modeling approach," CEMAPRE Working Papers 1302, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Andrea Rey-Martí & J. Augusto Felício & Ricardo Rodrigues, 2017. "Entrepreneurial attributes for success in the small hotel sector: a fuzzy-set QCA approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(5), pages 2085-2100, September.
    2. Sa'Adi Awang & Siti Arni Basir, 2016. "Challenges of Human Capital Development in Islamic Administration Institutes in Malaysia (IAM)," Proceedings of International Academic Conferences 3605499, International Institute of Social and Economic Sciences.

  2. Luisa Carvalho & Teresa Costa & Jorge Caiado, 2012. "Determinants of innovation in a small open economy: A multidimensional perspective," CEMAPRE Working Papers 1201, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Juana Sanchez, 2014. "Innovation Output Choices And Characteristics Of Firms In The U.S," Working Papers 14-42, Center for Economic Studies, U.S. Census Bureau.
    2. Ye Seul Choi & Up Lim, 2017. "Contextual Factors Affecting the Innovation Performance of Manufacturing SMEs in Korea: A Structural Equation Modeling Approach," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    3. Michael Pearson & Ignazio Cabras, 2014. "Innovation And Connectivity In Northern European Technical Cooperation Networks," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-24.
    4. Hannu Littunen & Timo Tohmo & Esa Storhammar, 2021. "Innovation among SMEs in Finland: The impact of stakeholder engagement and firm-level characteristics," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 17(4), pages 157-196.
    5. Egbetokun A. & Oluwatope O. & Adeyeye D. & Sanni M., 2014. "The role of industry and economic context in open innovation: Evidence from Nigeria," MERIT Working Papers 2014-073, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    6. Sanchez, Juana, 2014. "Non-technological and Mixed Modes of Innovation in the United States. Evidence from the Business Research and Development and Innovation Survey, 2008-2011," MPRA Paper 58719, University Library of Munich, Germany.
    7. Egbetokun, Abiodun A., 2015. "Interactive learning and firm-level capabilities in latecomer settings: The Nigerian manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 231-241.
    8. Luísa Carvalho & Maria José Madeira & João Carvalho & Dulcineia Catarina Moura & Filipe P. Duarte, 2018. "Cooperation for Innovation in the European Union: Outlook and Evidences Using CIS for 15 European Countries," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(2), pages 506-525, June.

  3. Joao A. Bastos & Jorge Caiado, 2010. "Recurrence quantification analysis of global stock markets," CEMAPRE Working Papers 1006, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Kiran Sharma & Shreyansh Shah & Anindya S. Chakrabarti & Anirban Chakraborti, 2016. "Sectoral co-movements in the Indian stock market: A mesoscopic network analysis," Papers 1607.05514, arXiv.org.
    2. Xu, Mengjia & Shang, Pengjian & Lin, Aijing, 2017. "Multiscale recurrence quantification analysis of order recurrence plots," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 381-389.
    3. Yao, Can-Zhong & Lin, Qing-Wen, 2017. "Recurrence plots analysis of the CNY exchange markets based on phase space reconstruction," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 584-596.
    4. Sergii Piskun & Oleksandr Piskun & Dmitry Chabanenko, 2011. "RQA Application for the Monitoring of Financial and Commodity markets state," Papers 1112.0297, arXiv.org.
    5. Juan Benjamín Duarte Duarte & Juan Manuel Mascare?nas Pérez-Iñigo, 2014. "Comprobación de la eficiencia débil en los principales mercados financieros latinoamericanos," Estudios Gerenciales, Universidad Icesi, November.
    6. Krishnadas M. & K. P. Harikrishnan & G. Ambika, 2022. "Recurrence measures and transitions in stock market dynamics," Papers 2208.03456, arXiv.org.
    7. Froguel, Lucas Belasque & de Lima Prado, Thiago & Corso, Gilberto & dos Santos Lima, Gustavo Zampier & Lopes, Sergio Roberto, 2022. "Efficient computation of recurrence quantification analysis via microstates," Applied Mathematics and Computation, Elsevier, vol. 428(C).
    8. Marisa Faggini, 2011. "Chaotic Time Series Analysis in Economics: Balance and Perspectives," Working papers 25, Former Department of Economics and Public Finance "G. Prato", University of Torino.
    9. Marisa Faggini & Bruna Bruno & Anna Parziale, 2019. "Does Chaos Matter in Financial Time Series Analysis?," International Journal of Economics and Financial Issues, Econjournals, vol. 9(4), pages 18-24.
    10. Halari, Anwar & Helliar, Christine & Power, David M. & Tantisantiwong, Nongnuch, 2019. "Taking advantage of Ramadan and January in Muslim countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 85-96.
    11. B. Goswami & G. Ambika & N. Marwan & J. Kurths, 2011. "On interrelations of recurrences and connectivity trends between stock indices," Papers 1103.5189, arXiv.org.
    12. Fatoorehchi, Hooman & Zarghami, Reza & Abolghasemi, Hossein & Rach, Randolph, 2015. "Chaos control in the cerium-catalyzed Belousov–Zhabotinsky reaction using recurrence quantification analysis measures," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 121-129.
    13. Teresa Aparicio & Dulce Saura, 2013. "Do Exchange Rate Series Present General Dependence? Some Results using Recurrence Quantification Analysis," Journal of Economics and Behavioral Studies, AMH International, vol. 5(10), pages 678-686.
    14. Sandoval, Leonidas Junior, 2013. "To lag or not to lag? How to compare indices of stock markets that operate at different times," Insper Working Papers wpe_319, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    15. Goswami, B. & Ambika, G. & Marwan, N. & Kurths, J., 2012. "On interrelations of recurrences and connectivity trends between stock indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(18), pages 4364-4376.
    16. Tantisantiwong, Nongnuch & Halari, Anwar & Helliar, Christine & Power, David, 2018. "East meets West: When the Islamic and Gregorian calendars coincide," The British Accounting Review, Elsevier, vol. 50(4), pages 402-424.
    17. Orlando, Giuseppe & Zimatore, Giovanna, 2018. "Recurrence quantification analysis of business cycles," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 82-94.
    18. Vinodh Madhavan, 2014. "Investigating the nature of nonlinearity in Indian Exchange Traded Funds (ETFs)," Managerial Finance, Emerald Group Publishing, vol. 40(4), pages 395-415, March.

  4. Joao A. Bastos & Jorge Caiado, 2010. "The structure of international stock market returns," CEMAPRE Working Papers 1002, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Guglielmo Maria Caporale & Luis A. Gil-Alana & C. James Orlando, 2015. "Linkages between the US and European Stock Markets: A Fractional Cointegration Approach," CESifo Working Paper Series 5523, CESifo.
    2. Srinivasan Palamalai & Kalaivani M. & Christopher Devakumar, 2013. "Stock Market Linkages in Emerging Asia-Pacific Markets," SAGE Open, , vol. 3(4), pages 21582440135, November.
    3. P., Srinivasan & M., Kalaivani, 2013. "Stock Market Linkages in Emerging Asia-Pacific Markets," MPRA Paper 45871, University Library of Munich, Germany.
    4. Andile Khula & Ntebogang Dinah Moroke, 2017. "The Performance of Maximum Likelihood Factor Analysis on South African Stock Price Performance," Journal of Economics and Behavioral Studies, AMH International, vol. 8(6), pages 40-51.

  5. Antonio Samagaio & Eduardo Couto & Jorge Caiado, 2009. "Sporting, financial and stock market performance in English football: an empirical analysis of structural relationships," CEMAPRE Working Papers 0906, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Robert Ślepaczuk & Igor Wabik, 2020. "The impact of the results of football matches on the stock prices of soccer clubs," Working Papers 2020-35, Faculty of Economic Sciences, University of Warsaw.
    2. Celine Gimet & Sandra Montchaud, 2016. "What Drives European Football Clubs’ Stock Returns and Volatility?," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 23(3), pages 351-390, September.
    3. Eukasz Leksowski, 2021. "Relationship between sport and financial performance in top European football clubs," Zeszyty Naukowe Małopolskiej Wyższej Szkoły Ekonomicznej w Tarnowie / The Malopolska School of Economics in Tarnow Research Papers Collection, Malopolska School of Economics in Tarnow, vol. 49(1), pages 41-59, March.
    4. Ender Demir & Ugo Rigoni, 2017. "You Lose, I Feel Better," Journal of Sports Economics, , vol. 18(1), pages 58-76, January.
    5. Altuğ Tanaltay & Amirreza Safari Langroudi & Raha Akhavan-Tabatabaei & Nihat Kasap, 2021. "Can Social Media Predict Soccer Clubs’ Stock Prices? The Case of Turkish Teams and Twitter," SAGE Open, , vol. 11(2), pages 21582440211, April.
    6. Giampiero Maci & Vincenzo Pacelli & Elisabetta D'Apolito, 2021. "Societ〠Di Calcio Europee Quotate E Mercati Finanziari: Un'Analisi Empirica Sulle Determinanti Dei Corsi Azionari," Rivista di Diritto ed Economia dello Sport, Centro di diritto e business dello Sport, vol. 17(2), pages 69-90, novembre.
    7. Alexandro Barbosa & Marke Geisy da Silva Dantas & Yuri Gomes Paiva Azevedo & Victor Branco de Holanda, 2017. "Fiscal Responsibility Strategy in Brazilian Football Clubs: A Dynamic Efficiency Analysis," Brazilian Business Review, Fucape Business School, vol. 14(Special I), pages 45-66, January.
    8. Carmine Zoccali, 2012. "The Role Of Financial Indicators In The Life Of Italian Football Clubs," Rivista di Diritto ed Economia dello Sport, Centro di diritto e business dello Sport, vol. 7(3), pages 83-101, gennaio.

  6. Jorge Caiado & Nuno Crato, 2009. "Identifying common dynamic features in stock returns," CEMAPRE Working Papers 0902, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    2. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 359-376, December.
    3. Galagedera, Don U.A., 2013. "A new perspective of equity market performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 333-357.
    4. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    5. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    6. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
    7. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

  7. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2009. "Comparison of time series with unequal length in the frequency domain," MPRA Paper 15310, University Library of Munich, Germany.

    Cited by:

    1. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    2. Jonathan Decowski & Linyuan Li, 2015. "Wavelet-Based Tests for Comparing Two Time Series with Unequal Lengths," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 189-208, March.
    3. Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.
    4. Jentsch, Carsten & Pauly, Markus, 2012. "A note on using periodogram-based distances for comparing spectral densities," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 158-164.
    5. Caiado, Jorge & Crato, Nuno, 2009. "Identifying common dynamic features in stock returns," MPRA Paper 15241, University Library of Munich, Germany.
    6. Preuß, Philip & Hildebrandt, Thimo, 2013. "Comparing spectral densities of stationary time series with unequal sample sizes," Statistics & Probability Letters, Elsevier, vol. 83(4), pages 1174-1183.
    7. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    8. Mahdi Massahi & Masoud Mahootchi & Alireza Arshadi Khamseh, 2020. "Development of an efficient cluster-based portfolio optimization model under realistic market conditions," Empirical Economics, Springer, vol. 59(5), pages 2423-2442, November.
    9. Lei Jin & Suojin Wang, 2016. "A New Test for Checking the Equality of the Correlation Structures of two time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 355-368, May.
    10. Carolina Euán & Hernando Ombao & Joaquín Ortega, 2018. "The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 71-99, April.
    11. Jin, Lei, 2011. "A data-driven test to compare two or multiple time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2183-2196, June.
    12. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    13. Harvill, Jane L. & Ravishanker, Nalini & Ray, Bonnie K., 2013. "Bispectral-based methods for clustering time series," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 113-131.
    14. Goffinet, Etienne & Lebbah, Mustapha & Azzag, Hanane & Loïc, Giraldi & Coutant, Anthony, 2022. "Functional non-parametric latent block model: A multivariate time series clustering approach for autonomous driving validation," Computational Statistics & Data Analysis, Elsevier, vol. 176(C).
    15. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
    16. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    17. Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).

  8. Joao A. Bastos & Jorge Caiado, 2009. "Clustering financial time series with variance ratio statistics," CEMAPRE Working Papers 0904, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Sipan Aslan & Ceylan Yozgatligil & Cem Iyigun, 2018. "Temporal clustering of time series via threshold autoregressive models: application to commodity prices," Annals of Operations Research, Springer, vol. 260(1), pages 51-77, January.
    2. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2015. "Clustering of time series via non-parametric tail dependence estimation," Statistical Papers, Springer, vol. 56(3), pages 701-721, August.
    3. Fabrizio Durante & Roberta Pappadà & Nicola Torelli, 2014. "Clustering of financial time series in risky scenarios," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 8(4), pages 359-376, December.
    4. Anna CZAPKIEWICZ & Pawel MAJDOSZ, 2014. "Grouping Stock Markets with Time-Varying Copula-GARCH Model," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 144-159, March.
    5. Galagedera, Don U.A., 2013. "A new perspective of equity market performance," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 26(C), pages 333-357.
    6. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    7. Erniel B. Barrios & Paolo Victor T. Redondo, 2021. "Nonparametric Test for Volatility in Clustered Multiple Time Series," Papers 2104.14412, arXiv.org.
    8. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    9. Dias, José G. & Vermunt, Jeroen K. & Ramos, Sofia, 2015. "Clustering financial time series: New insights from an extended hidden Markov model," European Journal of Operational Research, Elsevier, vol. 243(3), pages 852-864.
    10. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari, 2021. "Trimmed fuzzy clustering of financial time series based on dynamic time warping," Annals of Operations Research, Springer, vol. 299(1), pages 1379-1395, April.
    11. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
    12. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    13. Ekaterina Dorodnykh, 2013. "What Drives Stock Exchange Integration?," International Journal of Business and Economic Sciences Applied Research (IJBESAR), International Hellenic University (IHU), Kavala Campus, Greece (formerly Eastern Macedonia and Thrace Institute of Technology - EMaTTech), vol. 6(2), pages 47-79, September.

  9. Jorge Caiado, 2009. "Performance of combined double seasonal univariate time series models for forecasting water demand," CEMAPRE Working Papers 0903, Centre for Applied Mathematics and Economics (CEMAPRE), School of Economics and Management (ISEG), Technical University of Lisbon.

    Cited by:

    1. Rafael Benítez & Carmen Ortiz-Caraballo & Juan Carlos Preciado & José M. Conejero & Fernando Sánchez Figueroa & Alvaro Rubio-Largo, 2019. "A Short-Term Data Based Water Consumption Prediction Approach," Energies, MDPI, vol. 12(12), pages 1-24, June.
    2. Xiao-jun Wang & Jian-yun Zhang & Shahid Shamsuddin & Ru-lin Oyang & Tie-sheng Guan & Jian-guo Xue & Xu Zhang, 2017. "Impacts of climate variability and changes on domestic water use in the Yellow River Basin of China," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(4), pages 595-608, April.
    3. E. Pacchin & F. Gagliardi & S. Alvisi & M. Franchini, 2019. "A Comparison of Short-Term Water Demand Forecasting Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(4), pages 1481-1497, March.
    4. Xiao-jun Wang & Jian-yun Zhang & Shamsuddin Shahid & En-hong Guan & Yong-xiang Wu & Juan Gao & Rui-min He, 2016. "Adaptation to climate change impacts on water demand," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 81-99, January.
    5. Xiao-Jun Wang & Jian-Yun Zhang & Shamsuddin Shahid & Wei Xie & Chao-Yang Du & Xiao-Chuan Shang & Xu Zhang, 2018. "Modeling domestic water demand in Huaihe River Basin of China under climate change and population dynamics," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 20(2), pages 911-924, April.
    6. Jens Kley-Holsteg & Florian Ziel, 2020. "Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso," Papers 2005.04522, arXiv.org.

  10. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Comparison of time series with unequal length," MPRA Paper 6605, University Library of Munich, Germany.

    Cited by:

    1. Lei Jin & Suojin Wang, 2016. "A New Test for Checking the Equality of the Correlation Structures of two time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 37(3), pages 355-368, May.
    2. Caiado, Jorge & Crato, Nuno, 2008. "Identifying the evolution of stock markets stochastic structure after the euro," MPRA Paper 6609, University Library of Munich, Germany.
    3. Caiado, Jorge & Crato, Nuno, 2007. "A GARCH-based method for clustering of financial time series: International stock markets evidence," MPRA Paper 2074, University Library of Munich, Germany.
    4. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Is there an identity within international stock market volatilities?," MPRA Paper 2069, University Library of Munich, Germany.

  11. Caiado, Jorge & Crato, Nuno, 2007. "A GARCH-based method for clustering of financial time series: International stock markets evidence," MPRA Paper 2074, University Library of Munich, Germany.

    Cited by:

    1. Giampiero M. Gallo & Demetrio Lacava & Edoardo Otranto, 2020. "On Classifying the Effects of Policy Announcements on Volatility," Papers 2011.14094, arXiv.org, revised Feb 2021.
    2. Lior Sidi, 2020. "Improving S&P stock prediction with time series stock similarity," Papers 2002.05784, arXiv.org.
    3. D’Urso, Pierpaolo & Cappelli, Carmela & Di Lallo, Dario & Massari, Riccardo, 2013. "Clustering of financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2114-2129.
    4. Anna CZAPKIEWICZ & Pawel MAJDOSZ, 2014. "Grouping Stock Markets with Time-Varying Copula-GARCH Model," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(2), pages 144-159, March.
    5. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    6. Luca De Angelis, 2013. "Latent class models for financial data analysis: some statistical developments," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 22(2), pages 227-242, June.
    7. F. Lisi & E. Otranto, 2008. "Clustering Mutual Funds by Return and Risk Levels," Working Paper CRENoS 200813, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    8. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

  12. Caiado, Jorge, 2004. "Modelling and forecasting the volatility of the portuguese stock index PSI-20," MPRA Paper 2077, University Library of Munich, Germany.

    Cited by:

    1. Sergey SVESHNIKOV & Victor BOCHARNIKOV, 2009. "Eforecasting Financial Indexes With Model Of Composite Events Influence," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 4(3(9)_Fall).
    2. Amir Rafique, 2011. "Comparing the Leverage Effect of Different Frequencies of Stock Returns in an Emerging Market: A Case Study of Pakistan," Information Management and Business Review, AMH International, vol. 3(6), pages 283-288.
    3. Amir Rafique, 2011. "Comparing the Volatility Clustering Of Different Frequencies of Stock Returns in an Emerging Market: A Case Study of Pakistan," Journal of Economics and Behavioral Studies, AMH International, vol. 3(6), pages 332-336.
    4. Yaya, OlaOluwa S. & Gil-Alana, Luis A., 2014. "The persistence and asymmetric volatility in the Nigerian stock bull and bear markets," Economic Modelling, Elsevier, vol. 38(C), pages 463-469.
    5. Ioannis A. Tampakoudis & Demetres N. Subeniotis & Ioannis G. Kroustalis, 2012. "Modelling volatility during the current financial crisis: an empirical analysis of the US and the UK stock markets," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(3/4), pages 171-194.

Articles

  1. Paula C. A. M. de Albuquerque & Jorge Caiado & Andreia Pereira, 2020. "Population aging and inflation: evidence from panel cointegration," Journal of Applied Economics, Taylor & Francis Journals, vol. 23(1), pages 469-484, January.

    Cited by:

    1. Joseph Kopecky, 2021. "Okay Boomer... Excess Money Growth, Inflation, and Population Aging," Trinity Economics Papers tep0721, Trinity College Dublin, Department of Economics, revised Oct 2021.

  2. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.

    Cited by:

    1. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.

  3. Coelho do Vale, Rita & Verga Matos, Pedro & Caiado, Jorge, 2016. "The impact of private labels on consumer store loyalty: An integrative perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 28(C), pages 179-188.

    Cited by:

    1. Lacœuilhe, Jérôme & Louis, Didier & Lombart, Cindy, 2017. "Impacts of product, store and retailer perceptions on consumers’ relationship to terroir store brand," Journal of Retailing and Consumer Services, Elsevier, vol. 39(C), pages 43-53.
    2. Maksymilian Czeczotko & Hanna Górska-Warsewicz & Wacław Laskowski & Barbara Rostecka, 2021. "Towards Sustainable Private Labels in an Autonomous Community during COVID-19—Analysis of Consumer Behavior and Perception on the Example of Tenerife," Sustainability, MDPI, vol. 13(13), pages 1-22, July.
    3. Florez-Acosta, Jorge, 2021. "Do preferences for private labels respond to supermarket loyalty programs?," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 183-208.
    4. Fuduric, Morana & Varga, Akos & Horvat, Sandra & Skare, Vatroslav, 2022. "The ways we perceive: A comparative analysis of manufacturer brands and private labels using implicit and explicit measures," Journal of Business Research, Elsevier, vol. 142(C), pages 221-241.
    5. İpek, İlayda & Aşkın, Nilay & İlter, Burcu, 2016. "Private label usage and store loyalty: The moderating impact of shopping value," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 72-79.
    6. Assarzadegan, Parisa & Hejazi, Seyed Reza, 2021. "A game theoretic approach for analyzing the competition between national and store brands by considering store loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    7. Jérôme Lacoeuilhe & Didier Louis & Cindy Lombart, 2017. "Impacts of product, store and retailer perceptions on consumers’ relationship to terroir store brand," Post-Print hal-01672920, HAL.
    8. Lin, Chen & Bowman, Douglas, 2022. "The impact of introducing a customer loyalty program on category sales and profitability," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    9. Maksymilian Czeczotko & Hanna Górska-Warsewicz & Robert Zaremba, 2022. "Health and Non-Health Determinants of Consumer Behavior toward Private Label Products—A Systematic Literature Review," IJERPH, MDPI, vol. 19(3), pages 1-36, February.
    10. Bhat Ishfaq Hussain & Singh Sapna, 2018. "Examining the moderating effect of shopping value on private-label and loyalty in Indian grocery stores," Management & Marketing, Sciendo, vol. 13(1), pages 748-760, March.
    11. Dawes, John, 2022. "Factors that influence manufacturer and store brand behavioral loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    12. Ratula Chakraborty, 2018. "Do Retailers Manipulate Prices to Favour Private Label over Brands?," Working Paper series, University of East Anglia, Centre for Competition Policy (CCP) 2018-02, Centre for Competition Policy, University of East Anglia, Norwich, UK..
    13. Samy Belaïd & Jérôme Lacoeuilhe, 2018. "Purchase motivations and levers to revitalize the core market store brands [Les motivations d’achat et leviers pour redynamiser l’offre des marques de distributeurs cœur de gamme]," Post-Print hal-01841502, HAL.
    14. Rokonuzzaman, Md & Harun, Ahasan & Al-Emran, Md & Prybutok, Victor R., 2020. "An investigation into the link between consumer's product involvement and store loyalty: The roles of shopping value goals and information search as the mediating factors," Journal of Retailing and Consumer Services, Elsevier, vol. 52(C).
    15. Ellen J. Van Loo & Fien Minnens & Wim Verbeke, 2021. "Consumer Preferences for Private Label Brand vs. National Brand Organic Juice and Eggs: A Latent Class Approach," Sustainability, MDPI, vol. 13(13), pages 1-12, June.
    16. Konuk, Faruk Anıl, 2018. "The role of store image, perceived quality, trust and perceived value in predicting consumers’ purchase intentions towards organic private label food," Journal of Retailing and Consumer Services, Elsevier, vol. 43(C), pages 304-310.
    17. Hanna Górska-Warsewicz & Sylwia Żakowska-Biemans & Maksymilian Czeczotko & Monika Świątkowska & Dagmara Stangierska & Ewa Świstak & Agnieszka Bobola & Julita Szlachciuk & Karol Krajewski, 2018. "Organic Private Labels as Sources of Competitive Advantage—The Case of International Retailers Operating on the Polish Market," Sustainability, MDPI, vol. 10(7), pages 1-28, July.

  4. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    See citations under working paper version above.
  5. Luísa Carvalho & Teresa Costa & Jorge Caiado, 2013. "Determinants of innovation in a small open economy: a multidimensional perspective," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 14(3), pages 583-600, June.
    See citations under working paper version above.
  6. J. Augusto Felício & Eduardo Couto & Jorge Caiado, 2011. "Human capital and social capital in entrepreneurs and managers of small and medium enterprises," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 13(3), pages 395-420, June.

    Cited by:

    1. María José Rodríguez-Gutiérrez & Isidoro Romero & Zhikun Yu, 2020. "Guanxi and risk-taking propensity in Chinese immigrants’ businesses," International Entrepreneurship and Management Journal, Springer, vol. 16(1), pages 305-325, March.
    2. Ashraf Elsafty & Dalia Abadir & Ashraf Shaarawy, 2020. "How Does the Entrepreneurs’ Financial, Human, Social and Psychological Capitals Impact Entrepreneur’S Success?," Business and Management Studies, Redfame publishing, vol. 6(3), pages 55-71, September.

  7. Bastos, João A. & Caiado, Jorge, 2011. "Recurrence quantification analysis of global stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(7), pages 1315-1325.
    See citations under working paper version above.
  8. Jorge Caiado & Nuno Crato, 2010. "Identifying common dynamic features in stock returns," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 797-807.
    See citations under working paper version above.
  9. Caiado, Jorge & Crato, Nuno & Pena, Daniel, 2006. "A periodogram-based metric for time series classification," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2668-2684, June.

    Cited by:

    1. Sipan Aslan & Ceylan Yozgatligil & Cem Iyigun, 2018. "Temporal clustering of time series via threshold autoregressive models: application to commodity prices," Annals of Operations Research, Springer, vol. 260(1), pages 51-77, January.
    2. Francesca Di Iorio & Umberto Triacca, 2022. "A comparison between VAR processes jointly modeling GDP and Unemployment rate in France and Germany," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(3), pages 617-635, September.
    3. Zhaoxing Gao & Ruey S. Tsay, 2021. "Divide-and-Conquer: A Distributed Hierarchical Factor Approach to Modeling Large-Scale Time Series Data," Papers 2103.14626, arXiv.org.
    4. João A. Bastos & Jorge Caiado, 2014. "Clustering financial time series with variance ratio statistics," Quantitative Finance, Taylor & Francis Journals, vol. 14(12), pages 2121-2133, December.
    5. Giulio Palomba & Emma Sarno & Alberto Zazzaro, 2009. "Testing similarities of short-run inflation dynamics among EU-25 countries after the Euro," Empirical Economics, Springer, vol. 37(2), pages 231-270, October.
    6. Elizabeth Ann Maharaj & Pierpaolo D’Urso & Don Galagedera, 2010. "Wavelet-based Fuzzy Clustering of Time Series," Journal of Classification, Springer;The Classification Society, vol. 27(2), pages 231-275, September.
    7. Umberto Triacca, 2016. "Measuring the Distance between Sets of ARMA Models," Econometrics, MDPI, vol. 4(3), pages 1-11, July.
    8. Tyler Roick & Dimitris Karlis & Paul D. McNicholas, 2021. "Clustering discrete-valued time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(1), pages 209-229, March.
    9. Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.
    10. Alessandro De Gregorio & Stefano Iacus, 2008. "Clustering of discretely observed diffusion processes," UNIMI - Research Papers in Economics, Business, and Statistics unimi-1077, Universitá degli Studi di Milano.
    11. Jentsch, Carsten & Pauly, Markus, 2012. "A note on using periodogram-based distances for comparing spectral densities," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 158-164.
    12. Sonia Díaz & José Vilar, 2010. "Comparing Several Parametric and Nonparametric Approaches to Time Series Clustering: A Simulation Study," Journal of Classification, Springer;The Classification Society, vol. 27(3), pages 333-362, November.
    13. Caiado, Jorge & Crato, Nuno, 2005. "Discrimination between deterministic trend and stochastic trend processes," MPRA Paper 2076, University Library of Munich, Germany.
    14. Mahmoudi, Mohammad Reza & Heydari, Mohammad Hossein & Roohi, Reza, 2019. "A new method to compare the spectral densities of two independent periodically correlated time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 160(C), pages 103-110.
    15. Caiado, Jorge & Crato, Nuno, 2009. "Identifying common dynamic features in stock returns," MPRA Paper 15241, University Library of Munich, Germany.
    16. Juan Vilar & José Vilar & Sonia Pértega, 2009. "Classifying Time Series Data: A Nonparametric Approach," Journal of Classification, Springer;The Classification Society, vol. 26(1), pages 3-28, April.
    17. Mahdi Massahi & Masoud Mahootchi & Alireza Arshadi Khamseh, 2020. "Development of an efficient cluster-based portfolio optimization model under realistic market conditions," Empirical Economics, Springer, vol. 59(5), pages 2423-2442, November.
    18. Tianbo Chen & Ying Sun & Carolina Euan & Hernando Ombao, 2021. "Clustering Brain Signals: a Robust Approach Using Functional Data Ranking," Journal of Classification, Springer;The Classification Society, vol. 38(3), pages 425-442, October.
    19. Douzal-Chouakria, Ahlame & Diallo, Alpha & Giroud, Françoise, 2009. "Adaptive clustering for time series: Application for identifying cell cycle expressed genes," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1414-1426, February.
    20. Heung-gu Son & Yunsun Kim & Sahm Kim, 2020. "Time Series Clustering of Electricity Demand for Industrial Areas on Smart Grid," Energies, MDPI, vol. 13(9), pages 1-14, May.
    21. Dette, Holger & Paparoditis, Efstathios, 2008. "Bootstrapping frequency domain tests in multivariate time series with an application to comparing spectral densities," Technical Reports 2008,28, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    22. Ozan Cinar & Ozlem Ilk & Cem Iyigun, 2018. "Clustering of short time-course gene expression data with dissimilar replicates," Annals of Operations Research, Springer, vol. 263(1), pages 405-428, April.
    23. Beibei Zhang & Rong Chen, 2018. "Nonlinear Time Series Clustering Based on Kolmogorov-Smirnov 2D Statistic," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 394-421, October.
    24. Xu Gao & Babak Shahbaba & Hernando Ombao, 2018. "Modeling Binary Time Series Using Gaussian Processes with Application to Predicting Sleep States," Journal of Classification, Springer;The Classification Society, vol. 35(3), pages 549-579, October.
    25. Carolina Euán & Hernando Ombao & Joaquín Ortega, 2018. "The Hierarchical Spectral Merger Algorithm: A New Time Series Clustering Procedure," Journal of Classification, Springer;The Classification Society, vol. 35(1), pages 71-99, April.
    26. Jin, Lei, 2011. "A data-driven test to compare two or multiple time series," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2183-2196, June.
    27. Caiado, Jorge & Crato, Nuno, 2008. "Identifying the evolution of stock markets stochastic structure after the euro," MPRA Paper 6609, University Library of Munich, Germany.
    28. B. Lafuente-Rego & P. D’Urso & J. A. Vilar, 2020. "Robust fuzzy clustering based on quantile autocovariances," Statistical Papers, Springer, vol. 61(6), pages 2393-2448, December.
    29. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Comparison of time series with unequal length," MPRA Paper 6605, University Library of Munich, Germany.
    30. Bertsch, Valentin & Devine, Mel & Sweeney, Conor & Parnell, Andrew C., 2018. "Analysing long-term interactions between demand response and different electricity markets using a stochastic market equilibrium model," Papers WP585, Economic and Social Research Institute (ESRI).
    31. Harvill, Jane L. & Ravishanker, Nalini & Ray, Bonnie K., 2013. "Bispectral-based methods for clustering time series," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 113-131.
    32. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2009. "Comparison of time series with unequal length in the frequency domain," MPRA Paper 15310, University Library of Munich, Germany.
    33. Maharaj, Elizabeth A. & Alonso, Andres M., 2007. "Discrimination of locally stationary time series using wavelets," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 879-895, October.
    34. Caiado, Jorge & Crato, Nuno, 2007. "Identifying common spectral and asymmetric features in stock returns," MPRA Paper 6607, University Library of Munich, Germany.
    35. Vilar, J.A. & Alonso, A.M. & Vilar, J.M., 2010. "Non-linear time series clustering based on non-parametric forecast densities," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2850-2865, November.
    36. Pierpaolo D’Urso & Livia Giovanni & Riccardo Massari & Dario Lallo, 2013. "Noise fuzzy clustering of time series by autoregressive metric," METRON, Springer;Sapienza Università di Roma, vol. 71(3), pages 217-243, November.
    37. Liu, Shen & Maharaj, Elizabeth Ann, 2013. "A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 60(C), pages 32-49.
    38. E. Otranto, 2008. "Clustering Heteroskedastic Time Series by Model-Based Procedures," Working Paper CRENoS 200801, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    39. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2006. "An interpolated periodogram-based metric for comparison of time series with unequal lengths," MPRA Paper 2075, University Library of Munich, Germany.
    40. Giovanni De Luca & Paola Zuccolotto, 2011. "A tail dependence-based dissimilarity measure for financial time series clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(4), pages 323-340, December.
    41. Irene Mariñas-Collado & Ana E. Sipols & M. Teresa Santos-Martín & Elisa Frutos-Bernal, 2022. "Clustering and Forecasting Urban Bus Passenger Demand with a Combination of Time Series Models," Mathematics, MDPI, vol. 10(15), pages 1-16, July.
    42. Robert Lund & Hany Bassily & Brani Vidakovic, 2009. "Testing equality of stationary autocovariances," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(3), pages 332-348, May.
    43. E. Otranto, 2011. "Classification of Volatility in Presence of Changes in Model Parameters," Working Paper CRENoS 201113, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    44. Giulio PALOMBA & Emma SARNO & Alberto ZAZZARO, 2007. "Testing similarities of short-run inflation dynamics among EU countries after the Euro," Working Papers 289, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    45. Jorge Caiado & Nuno Crato & Pilar Poncela, 2020. "A fragmented-periodogram approach for clustering big data time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(1), pages 117-146, March.
    46. João A. Bastos & Jorge Caiado, 2021. "On the classification of financial data with domain agnostic features," Working Papers REM 2021/0185, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    47. Montero, Pablo & Vilar, José A., 2014. "TSclust: An R Package for Time Series Clustering," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 62(i01).
    48. Krzysztof Gajowniczek & Tomasz Ząbkowski, 2018. "Simulation Study on Clustering Approaches for Short-Term Electricity Forecasting," Complexity, Hindawi, vol. 2018, pages 1-21, April.
    49. Mahmoudi, Mohammad Reza, 2021. "A computational technique to classify several fractional Brownian motion processes," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    50. Corduas, Marcella & Piccolo, Domenico, 2008. "Time series clustering and classification by the autoregressive metric," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1860-1872, January.
    51. Caiado, Jorge & Crato, Nuno & Peña, Daniel, 2007. "Is there an identity within international stock market volatilities?," MPRA Paper 2069, University Library of Munich, Germany.

  10. Jorge Caiado, 2004. "Modelling And Forecasting The Volatility Of The Portuguese Stock Index Psi-20," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(1), pages 3-21.
    See citations under working paper version above.

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 20 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ECM: Econometrics (8) 2007-03-17 2007-03-17 2008-01-12 2008-01-12 2008-01-12 2009-05-16 2009-05-16 2009-05-30. Author is listed
  2. NEP-ETS: Econometric Time Series (8) 2007-03-17 2007-03-17 2008-01-12 2008-01-12 2009-05-16 2009-05-16 2009-05-30 2021-08-09. Author is listed
  3. NEP-FMK: Financial Markets (4) 2009-05-16 2009-10-03 2010-07-31 2010-12-18
  4. NEP-FOR: Forecasting (4) 2007-03-17 2008-01-12 2009-05-16 2009-05-30
  5. NEP-CSE: Economics of Strategic Management (3) 2009-12-05 2012-10-13 2013-08-31
  6. NEP-RMG: Risk Management (3) 2007-03-17 2007-03-17 2008-01-12
  7. NEP-SBM: Small Business Management (3) 2009-12-05 2012-10-13 2013-08-31
  8. NEP-EEC: European Economics (2) 2007-03-17 2008-01-12
  9. NEP-ENT: Entrepreneurship (2) 2009-12-05 2013-08-31
  10. NEP-HRM: Human Capital & Human Resource Management (2) 2009-12-05 2013-08-31
  11. NEP-KNM: Knowledge Management & Knowledge Economy (2) 2009-12-05 2012-10-13
  12. NEP-SOC: Social Norms & Social Capital (2) 2009-12-05 2013-08-31
  13. NEP-SPO: Sports & Economics (2) 2007-03-17 2009-12-05
  14. NEP-BAN: Banking (1) 2021-11-01
  15. NEP-CBA: Central Banking (1) 2021-11-01
  16. NEP-CMP: Computational Economics (1) 2021-08-09
  17. NEP-FDG: Financial Development & Growth (1) 2021-11-01
  18. NEP-FLE: Financial Literacy & Education (1) 2021-11-01
  19. NEP-IFN: International Finance (1) 2007-03-17
  20. NEP-INO: Innovation (1) 2012-10-13
  21. NEP-MON: Monetary Economics (1) 2021-11-01
  22. NEP-ORE: Operations Research (1) 2008-01-12
  23. NEP-TID: Technology & Industrial Dynamics (1) 2012-10-13

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