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Jaqueson Kingeski Galimberti

Personal Details

First Name:Jaqueson
Middle Name:Kingeski
Last Name:Galimberti
Suffix:
RePEc Short-ID:pga316
http://sites.google.com/site/jkgeconoeng/
Twitter: @galimberti_jk
Terminal Degree:2013 School of Economics; University of Manchester (from RePEc Genealogy)

Affiliation

KOF Swiss Economic Institute
Department of Management, Technology and Economics (D-MTEC)
Eidgenössische Technische Hochschule Zürich (ETHZ)

Zürich, Switzerland
http://www.kof.ethz.ch/

: +41 44 632 42 39
+41 44 632 12 18
Leonhardstrasse 21, CH-8092 Zürich
RePEc:edi:koethch (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
  2. Jaqueson K Galimberti, 2017. "Forecasting GDP growth from the outer space," KOF Working papers 17-427, KOF Swiss Economic Institute, ETH Zurich.
  3. Galimberti, Jaqueson & Suhadolnik, Nicolas & Da Silva, Sergio, 2016. "Cowboying Stock Market Herds with Robot Traders," MPRA Paper 71758, University Library of Munich, Germany.
  4. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
  5. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.
  6. Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.
  7. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The Univeristy of Manchester.
  8. Galimberti, Jaqueson K., 2012. "A tutorial note on the properties of ARIMA optimal forecasts," MPRA Paper 40303, University Library of Munich, Germany, revised 27 Jul 2012.
  9. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.
  10. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The Univeristy of Manchester.
  11. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The Univeristy of Manchester.
  12. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," MPRA Paper 23923, University Library of Munich, Germany.
  13. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  14. Galimberti, Jaqueson K., 2009. "Conditioned Export-Led Growth Hypothesis: A Panel Threshold Regressions Approach," MPRA Paper 13417, University Library of Munich, Germany.
  15. Galimberti, Jaqueson Kingeski & Cupertino, César Medeiros, 2009. "Explaining earnings persistence: a threshold autoregressive panel unit root approach," MPRA Paper 14237, University Library of Munich, Germany.

Articles

  1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
  2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
  3. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
  4. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.
  5. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
  6. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
  7. Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, vol. 118(1), pages 139-142.
  8. Jaqueson K. Galimberti & Sergio da Silva, 2012. "An empirical case against the use of genetic-based learning classifier systems as forecasting devices," Economics Bulletin, AccessEcon, vol. 32(1), pages 354-369.
  9. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5182-5192.
  10. Jaqueson K. Galimberti, 2009. "A proxy-variable search procedure," Economics Bulletin, AccessEcon, vol. 29(4), pages 2531-2541.

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. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.

  2. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    2. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
    3. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.

  3. Michele Berardi & Jaqueson K. Galimberti, 2015. "Empirical Calibration of Adaptive Learning," KOF Working papers 15-392, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Michele Berardi, 2016. "Herding through learning in an asset pricing model," Centre for Growth and Business Cycle Research Discussion Paper Series 223, Economics, The Univeristy of Manchester.

  4. Michele Bernardi & Jaqueson K. Galimberti, 2014. "A Note on the Representative Adaptive Learning Algorithm," KOF Working papers 14-356, KOF Swiss Economic Institute, ETH Zurich.

    Cited by:

    1. Christina Strobach & Carin van der Cruijsen, 2015. "The formation of European inflation expectations: One learning rule does not fit all," DNB Working Papers 472, Netherlands Central Bank, Research Department.
    2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    3. Damjanovic, Tatiana & Girdėnas, Šarūnas & Liu, Keqing, 2015. "Stationarity of econometric learning with bounded memory and a predicted state variable," Economics Letters, Elsevier, vol. 130(C), pages 93-96.
    4. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.

  5. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The Univeristy of Manchester.

    Cited by:

    1. Christina Strobach & Carin van der Cruijsen, 2015. "The formation of European inflation expectations: One learning rule does not fit all," DNB Working Papers 472, Netherlands Central Bank, Research Department.
    2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    3. Singleton, Carl & Schaefer, Daniel, 2015. "Unemployment and econometric learning," MPRA Paper 63162, University Library of Munich, Germany.
    4. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The Univeristy of Manchester.
    5. Michele Berardi & Jaqueson K Galimberti, 2016. "On the Initialization of Adaptive Learning in Macroeconomic Models," KOF Working papers 16-422, KOF Swiss Economic Institute, ETH Zurich.
    6. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
    7. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.
    8. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The Univeristy of Manchester.

  6. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.

    Cited by:

    1. Agnieszka Markiewicz & Andreas Pick, 2013. "Adaptive Learning and Survey Data," CDMA Working Paper Series 201305, Centre for Dynamic Macroeconomic Analysis.
    2. Singleton, Carl & Schaefer, Daniel, 2015. "Unemployment and econometric learning," MPRA Paper 63162, University Library of Munich, Germany.

  7. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The Univeristy of Manchester.

    Cited by:

    1. Agnieszka Markiewicz & Andreas Pick, 2013. "Adaptive Learning and Survey Data," CDMA Working Paper Series 201305, Centre for Dynamic Macroeconomic Analysis.
    2. Christina Strobach & Carin van der Cruijsen, 2015. "The formation of European inflation expectations: One learning rule does not fit all," DNB Working Papers 472, Netherlands Central Bank, Research Department.
    3. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
    4. Michele Berardi & Jaqueson K Galimberti, 2017. "Smoothing-based Initialization for Learning-to-Forecast Algorithms," KOF Working papers 17-425, KOF Swiss Economic Institute, ETH Zurich.
    5. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.

  8. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The Univeristy of Manchester.

    Cited by:

    1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
    2. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

  9. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," MPRA Paper 23923, University Library of Munich, Germany.

    Cited by:

    1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
    2. Da Silva, Sergio, 2014. "Why Not Use Robots to Stabilize Stock Markets?," MPRA Paper 60567, University Library of Munich, Germany.
    3. Da Silva, Sergio, 2013. "Time to abandon group thinking in economics," MPRA Paper 45660, University Library of Munich, Germany.

  10. Galimberti, Jaqueson K. & Moura, Marcelo L., 2010. "Taylor Rules and Exchange Rate Predictability in Emerging Economies," Insper Working Papers wpe_214, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.

    Cited by:

    1. Guglielmo Maria Caporale & Abdurrahman Nazif Catik & Mohamad Husam Helmi & Faek Nemla Ali & Coskun Akdeniz, 2016. "Monetary Policy Rules in Emerging Countries: Is there an Augmented Nonlinear Taylor Rule?," CESifo Working Paper Series 5965, CESifo Group Munich.
    2. Emerson Fernandes Marçal & Eli Hadad Junior, 2016. "Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case," Brazilian Review of Finance, Brazilian Society of Finance, vol. 14(1), pages 65-88.
    3. Rossi Junior, Jose Luiz & Felicio, Wilson Rafael de Oliveira, 2014. "Common Factors and the Exchange Rate: Results From the Brazilian Case," Revista Brasileira de Economia - RBE, FGV/EPGE - Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil), vol. 68(1), April.
    4. Felício, Wilson Rafael de Oliveira & Rossi, José Luiz Júnior, 2013. "Common factors and the exchange rate: results from the Brazilian case," Insper Working Papers wpe_318, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    5. Moura, Marcelo L. & Pereira, Fatima R. & Attuy, Guilherme de Moraes, 2013. "Currency Wars in Action: How Foreign Exchange Interventions Work in an Emerging Economy," Insper Working Papers wpe_304, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    6. Cuiabano, Simone, 2017. "Long-run equilibrium exchange rate in Latin America and Asia: a comparison using cointegrated vector," TSE Working Papers 17-837, Toulouse School of Economics (TSE).
    7. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    8. Jaqueson K. Galimberti & Marcelo L. Moura, 2011. "Improving the reliability of real-time Hodrick-Prescott filtering using survey forecasts," Centre for Growth and Business Cycle Research Discussion Paper Series 159, Economics, The Univeristy of Manchester.
    9. Chen, Chuanglian & Yao, Shujie & Ou, Jinghua, 2017. "Exchange rate dynamics in a Taylor rule framework," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 158-173.

  11. Galimberti, Jaqueson K., 2009. "Conditioned Export-Led Growth Hypothesis: A Panel Threshold Regressions Approach," MPRA Paper 13417, University Library of Munich, Germany.

    Cited by:

    1. Anca Maria GHERMAN & George ȘTEFAN, 2015. "Exports – trends and impacts on Romania’s economic growth process," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(603), S), pages 43-54, Summer.
    2. Fatma Zeren & Burcu Kilinc Savrul, 2013. "Revisited Export-Led Growth Hypothesis For Selected European Countries: A Panel Hidden Cointegration Approach," Istanbul University Econometrics and Statistics e-Journal, Department of Econometrics, Faculty of Economics, Istanbul University, vol. 18(1), pages 134-151, May.

  12. Galimberti, Jaqueson Kingeski & Cupertino, César Medeiros, 2009. "Explaining earnings persistence: a threshold autoregressive panel unit root approach," MPRA Paper 14237, University Library of Munich, Germany.

    Cited by:

    1. Timothy P. Sharpe, 2013. "Institutional arrangements and public debt threshold limits," International Review of Applied Economics, Taylor & Francis Journals, vol. 27(6), pages 707-728, November.
    2. Timothy P. Sharpe, 2013. "A Modern Money Perspective on Financial Crowding-out," Review of Political Economy, Taylor & Francis Journals, vol. 25(4), pages 586-606, October.

Articles

  1. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    See citations under working paper version above.
  2. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
    See citations under working paper version above.
  3. Galimberti, Jaqueson K. & Moura, Marcelo L., 2016. "Improving the reliability of real-time output gap estimates using survey forecasts," International Journal of Forecasting, Elsevier, vol. 32(2), pages 358-373.

    Cited by:

    1. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.

  4. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
    See citations under working paper version above.
  5. Galimberti, Jaqueson K. & Moura, Marcelo L., 2013. "Taylor rules and exchange rate predictability in emerging economies," Journal of International Money and Finance, Elsevier, vol. 32(C), pages 1008-1031.
    See citations under working paper version above.
  6. Berardi, Michele & Galimberti, Jaqueson K., 2013. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Economics Letters, Elsevier, vol. 118(1), pages 139-142. See citations under working paper version above.
  7. Suhadolnik, Nicolas & Galimberti, Jaqueson & Da Silva, Sergio, 2010. "Robot traders can prevent extreme events in complex stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(22), pages 5182-5192.
    See citations under working paper version above.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

List Editorship

This author manages the following RePEc Biblio topics, reading lists or publication compilations:
  1. Learning and Expectations Macroeconomists

Featured entries

This author is featured on the following reading lists, publication compilations or Wikipedia entries:
  1. Learning and Expectations Macroeconomists

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 18 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-FOR: Forecasting (7) 2011-09-16 2012-08-23 2012-11-17 2014-05-04 2014-07-28 2015-09-18 2017-07-02. Author is listed
  2. NEP-CMP: Computational Economics (3) 2012-10-20 2016-06-18 2017-07-02
  3. NEP-MAC: Macroeconomics (3) 2014-05-04 2014-07-28 2015-09-18
  4. NEP-ECM: Econometrics (2) 2011-09-16 2017-03-05
  5. NEP-ORE: Operations Research (2) 2014-05-04 2016-06-18
  6. NEP-ACC: Accounting & Auditing (1) 2009-03-28
  7. NEP-BIG: Big Data (1) 2017-07-02
  8. NEP-CBA: Central Banking (1) 2011-09-16
  9. NEP-CBE: Cognitive & Behavioural Economics (1) 2012-11-17
  10. NEP-DEV: Development (1) 2009-02-22
  11. NEP-ETS: Econometric Time Series (1) 2012-08-23
  12. NEP-EVO: Evolutionary Economics (1) 2015-09-18
  13. NEP-FDG: Financial Development & Growth (1) 2009-02-22
  14. NEP-FMK: Financial Markets (1) 2016-06-18
  15. NEP-HME: Heterodox Microeconomics (1) 2016-06-18
  16. NEP-LAB: Labour Economics (1) 2009-03-28
  17. NEP-RMG: Risk Management (1) 2010-07-24
  18. NEP-UPT: Utility Models & Prospect Theory (1) 2012-11-17

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