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Julian Andrada-Felix

Personal Details

First Name:Julian
Middle Name:
Last Name:Andrada-Felix
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RePEc Short-ID:pan47
Dr. Julián Andrada Félix Departamento de Métodos Cuantitativos en Economía y Gestión Facultad de Ciencias Económicas y Empresariales Universidad de Las Palmas de Gran Canaria Campus Universitario de Tafira 35017- Las Palmas de Gran Canaria. España
+34 928 458 959

Affiliation

Departamento de Métodos Cuantitativos en la Economía y la Gestión
Facultad de Economía, Empresa y Turismo
Universidad de las Palmas de Gran Canaria

Las Palmas, Spain
http://www.ulpgc.es/index.php?pagina=dmc&ver=inicio
RePEc:edi:dmlpges (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. Julián Andrada-Félix & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2011. "Historical financial analogies of the current crisis," Working Papers 11-08, Asociación Española de Economía y Finanzas Internacionales.
  2. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
  3. Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical analysis in the Madrid stock exchange," Studies on the Spanish Economy 23, FEDEA.
  4. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical Analysis in Foreign Exchange Markets: Linear Versus Nonlinear Trading Rules," Working Papers on International Economics and Finance 00-02, FEDEA.

Articles

  1. Eduardo Acosta-Gonzalez & Julian Andrada-Felix & Fernando Fernandez-Rodriguez, 2009. "Estimating time-varying variances and covariances via nearest neighbour multivariate predictions: applications to the NYSE and the Madrid Stock Exchange Index," Applied Economics, Taylor & Francis Journals, vol. 41(26), pages 3437-3445.
  2. Julián Andrada-Félix & Fernando Fernández-Rodríguez, 2008. "Improving moving average trading rules with boosting and statistical learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 433-449.
  3. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.
  4. Simón Sosvilla-Rivero & Fernando Fernández-Rodriguez & Julián Andrada-Félix, 2005. "Testing chaotic dynamics via Lyapunov exponents," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 911-930.
  5. Jorge Perez-Rodriguez & Salvador Torra & Julian Andrada-Felix, 2005. "Are Spanish Ibex35 stock future index returns forecasted with non-linear models?," Applied Financial Economics, Taylor & Francis Journals, vol. 15(14), pages 963-975.
  6. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
  7. Simon Sosvilla-Rivero & Julian Andrada-Felix & Fernando Fernandez-Rodriguez, 2002. "Further evidence on technical trade profitability and foreign exchange intervention," Applied Economics Letters, Taylor & Francis Journals, vol. 9(12), pages 827-832.
  8. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.
  9. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero Julian, 1997. "Combining information in exchange rate forecasting: evidence from the EMS," Applied Economics Letters, Taylor & Francis Journals, vol. 4(7), pages 441-444.

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. Julián Andrada-Félix & Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero, 2011. "Historical financial analogies of the current crisis," Working Papers 11-08, Asociación Española de Economía y Finanzas Internacionales.

    Cited by:

    1. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "The Aftermath of Financial Crises," American Economic Review, American Economic Association, vol. 99(2), pages 466-472, May.

  2. Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical analysis in the Madrid stock exchange," Studies on the Spanish Economy 23, FEDEA.

    Cited by:

    1. Fernando Fernández-Rodríguez & Christian González-Martel & Simón Sosvilla-Rivero, "undated". "Optimisation of Technical Rules by Genetic Algorithms: Evidence from the Madrid Stock Market," Working Papers 2001-14, FEDEA.
    2. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    3. Walid Omrane & Hervé Oppens, 2006. "The performance analysis of chart patterns: Monte Carlo simulation and evidence from the euro/dollar foreign exchange market," Empirical Economics, Springer, vol. 30(4), pages 947-971, January.
    4. Nikolaos Eriotis & Dimitrios Vasiliou & Spyros Papathanasiou, 2006. "Testing Technical Anomalies in Athens Stock Exchange (ASE)," European Research Studies Journal, European Research Studies Journal, vol. 0(3-4), pages 75-90.
    5. BEN OMRANE, Walid & VAN OPPEN, Hervé, 2004. "The predictive success and profitability of chart patterns in the Euro/Dollar foreign exchange market," LIDAM Discussion Papers CORE 2004035, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Ahmad, Mashood & Ali, Syed Babar, 2008. "Technical Analysis in the Stock Markets of Pakistan: A Case of Commercial Banks," MPRA Paper 64521, University Library of Munich, Germany.

  3. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical Analysis in Foreign Exchange Markets: Linear Versus Nonlinear Trading Rules," Working Papers on International Economics and Finance 00-02, FEDEA.

    Cited by:

    1. Subbiah, Mohan & Fabozzi, Frank J., 2016. "Hedge fund allocation: Evaluating parametric and nonparametric forecasts using alternative portfolio construction techniques," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 189-201.

Articles

  1. Julián Andrada-Félix & Fernando Fernández-Rodríguez, 2008. "Improving moving average trading rules with boosting and statistical learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(5), pages 433-449.

    Cited by:

    1. Teresa Buchen & Klaus Wohlrabe, 2013. "Assessing the Macroeconomic Forecasting Performance of Boosting - Evidence for the United States, the Euro Area, and Germany," CESifo Working Paper Series 4148, CESifo.
    2. Jacinta Chan Phooi M’ng & Rozaimah Zainudin, 2016. "Assessing the Efficacy of Adjustable Moving Averages Using ASEAN-5 Currencies," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-19, August.
    3. Lijun Wang & Haizhong An & Xiaohua Xia & Xiaojia Liu & Xiaoqi Sun & Xuan Huang, 2014. "Generating Moving Average Trading Rules on the Oil Futures Market with Genetic Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, May.
    4. Jacinta Chan Phooi M'ng & Azmin Azliza Aziz, 2016. "Using Neural Networks to Enhance Technical Trading Rule Returns: A Case with KLCI," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 2(1), pages 63-70, January.
    5. Phooi M’ng, Jacinta Chan, 2018. "Dynamically Adjustable Moving Average (AMA’) technical analysis indicator to forecast Asian Tigers’ futures markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 336-345.

  2. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.

    Cited by:

    1. Jin, Xiaoye, 2022. "Performance of intraday technical trading in China’s gold market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    2. Kizilaslan, Recep & Freund, Steven & Iseri, Ali, 2016. "A data analytic approach to forecasting daily stock returns in an emerging marketAuthor-Name: Oztekin, Asil," European Journal of Operational Research, Elsevier, vol. 253(3), pages 697-710.
    3. Firat Melih Yilmaz & Engin Yildiztepe, 2024. "Statistical Evaluation of Deep Learning Models for Stock Return Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 221-244, January.
    4. Seyed Mehrzad Asaad Sajadi & Pouya Khodaee & Ehsan Hajizadeh & Sabri Farhadi & Sohaib Dastgoshade & Bo Du, 2022. "Deep Learning-Based Methods for Forecasting Brent Crude Oil Return Considering COVID-19 Pandemic Effect," Energies, MDPI, vol. 15(21), pages 1-23, October.
    5. Lukas Ryll & Sebastian Seidens, 2019. "Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey," Papers 1906.07786, arXiv.org, revised Jul 2019.
    6. Ciner, Cetin, 2019. "Do industry returns predict the stock market? A reprise using the random forest," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 152-158.
    7. Yan, Isabel K. & Chong, Terence & Lam, Tau-Hing, 2011. "Is the Chinese Stock Market Really Efficient," MPRA Paper 35219, University Library of Munich, Germany.
    8. Ilias Lekkos & Costas Milas & Theodore Panagiotidis, 2005. "On the predictability of common risk factors in the US and UK interest rate swap markets:Evidence from non-linear and linear models," Keele Economics Research Papers KERP 2005/13, Centre for Economic Research, Keele University.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    10. Tan, Siow-Hooi & Lai, Ming-Ming & Tey, Eng-Xin & Chong, Lee-Lee, 2020. "Testing the performance of technical analysis and sentiment-TAR trading rules in the Malaysian stock market," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    11. I. Marta Miranda García & María‐Jesús Segovia‐Vargas & Usue Mori & José A. Lozano, 2023. "Early prediction of Ibex 35 movements," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1150-1166, August.
    12. Lawrence Xaba & Ntebogang Moroke & Johnson Arkaah & Charlemagne Pooe, 2015. "A Comparative Study of Stock Price Forecasting using nonlinear models," Proceedings of International Academic Conferences 2704207, International Institute of Social and Economic Sciences.
    13. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.
    14. Terence Tai-Leung Chong & Sheung Tat Chan, 2008. "Structural Change in the Efficiency of the Japanese Stock Market after the Millennium," Economics Bulletin, AccessEcon, vol. 7(7), pages 1-7.
    15. Juan Reboredo & José Matías & Raquel Garcia-Rubio, 2012. "Nonlinearity in Forecasting of High-Frequency Stock Returns," Computational Economics, Springer;Society for Computational Economics, vol. 40(3), pages 245-264, October.
    16. Kim, Sei-Wan & Mollick, André V. & Nam, Kiseok, 2008. "Common nonlinearities in long-horizon stock returns: Evidence from the G-7 stock markets," Global Finance Journal, Elsevier, vol. 19(1), pages 19-31.
    17. Elsy Gómez-Ramos & Francisco Venegas-Martínez, 2013. "A Review of Artificial Neural Networks: How Well Do They Perform in Forecasting Time Series?," Analítika, Analítika - Revista de Análisis Estadístico/Journal of Statistical Analysis, vol. 6(2), pages 7-15, Diciembre.
    18. Jaydip Sen & Tamal Datta Chaudhuri, 2017. "A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector," Papers 1705.01144, arXiv.org.
    19. Jaydip SEN & Tamal DATTA CHAUDHURI, 2016. "An Alternative Framework for Time Series Decomposition and Forecastingand its Relevance for Portfolio Choice – A Comparative Study of the Indian Consumer Durable and Small Cap Sectors," Journal of Economics Library, KSP Journals, vol. 3(2), pages 303-326, June.
    20. Duan, Wen-Qi & Stanley, H. Eugene, 2011. "Cross-correlation and the predictability of financial return series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 290-296.

  3. Simón Sosvilla-Rivero & Fernando Fernández-Rodriguez & Julián Andrada-Félix, 2005. "Testing chaotic dynamics via Lyapunov exponents," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 911-930.

    Cited by:

    1. Loretta Mastroeni & Pierluigi Vellucci, 2016. "“Butterfly Effect" vs Chaos in Energy Futures Markets," Departmental Working Papers of Economics - University 'Roma Tre' 0209, Department of Economics - University Roma Tre.
    2. Hartwell, Christopher A., 2019. "Short waves in Hungary, 1923 and 1946: Persistence, chaos, and (lack of) control," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 532-550.
    3. Park, Joon Y. & Whang, Yoon-Jae, 2012. "Random walk or chaos: A formal test on the Lyapunov exponent," Journal of Econometrics, Elsevier, vol. 169(1), pages 61-74.
    4. Matilla-García, Mariano & Marín, Manuel Ruiz, 2010. "A new test for chaos and determinism based on symbolic dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 76(3), pages 600-614, December.
    5. Vogl, Markus, 2022. "Controversy in financial chaos research and nonlinear dynamics: A short literature review," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    6. Resende, Marcelo & Zeidan, Rodrigo M., 2008. "Expectations and chaotic dynamics: Empirical evidence on exchange rates," Economics Letters, Elsevier, vol. 99(1), pages 33-35, April.
    7. Bask, Mikael & Widerberg, Anna, 2009. "Market structure and the stability and volatility of electricity prices," Energy Economics, Elsevier, vol. 31(2), pages 278-288, March.
    8. Bask, Mikael, 2007. "Measuring potential market risk," Bank of Finland Research Discussion Papers 20/2007, Bank of Finland.
    9. Belaire-Franch, Jorge, 2018. "Exchange rates expectations and chaotic dynamics: A replication study," Economics Discussion Papers 2018-34, Kiel Institute for the World Economy (IfW Kiel).
    10. Bashkirtseva, Irina A. & Ryashko, Lev B. & Pisarchik, Alexander N., 2020. "Ring of map-based neural oscillators: From order to chaos and back," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    11. Bask, Miia & Bask, Mikael, 2010. "Inequality Generating Processes and Measurement of the Matthew Effect," Working Paper Series 2010:19, Uppsala University, Department of Economics.
    12. Matilla-Garcia, Mariano, 2007. "A non-parametric test for independence based on symbolic dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 31(12), pages 3889-3903, December.
    13. Mikael Bask, 2024. "Skill, status and the Matthew effect: a theoretical framework," Journal of Computational Social Science, Springer, vol. 7(3), pages 2221-2253, December.
    14. Mariano Matilla-García & Manuel Ruiz Marín & Mohammed Dore & Rina Ojeda, 2014. "Nonparametric correlation integral–based tests for linear and nonlinear stochastic processes," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 37(1), pages 181-193, April.
    15. Loretta Mastroeni & Pierluigi Vellucci, 2016. ""Butterfly Effect" vs Chaos in Energy Futures Markets," Papers 1610.05697, arXiv.org.
    16. Matilla-Garci­a, Mariano & Ruiz Mari­n, Manuel, 2008. "A non-parametric independence test using permutation entropy," Journal of Econometrics, Elsevier, vol. 144(1), pages 139-155, May.
    17. Demos, Guilherme & Da Silva, Sergio & Matsushita, Raul, 2015. "Some Statistical Properties of the Mini Flash Crashes," MPRA Paper 65473, University Library of Munich, Germany.

  4. Jorge Perez-Rodriguez & Salvador Torra & Julian Andrada-Felix, 2005. "Are Spanish Ibex35 stock future index returns forecasted with non-linear models?," Applied Financial Economics, Taylor & Francis Journals, vol. 15(14), pages 963-975.

    Cited by:

    1. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Degiannakis, Stavros & Xekalaki, Evdokia, 2007. "Assessing the Performance of a Prediction Error Criterion Model Selection Algorithm in the Context of ARCH Models," MPRA Paper 96324, University Library of Munich, Germany.
    3. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, October.
    4. Christos Avdoulas & Stelios Bekiros & Sabri Boubaker, 2018. "Evolutionary-based return forecasting with nonlinear STAR models: evidence from the Eurozone peripheral stock markets," Annals of Operations Research, Springer, vol. 262(2), pages 307-333, March.

  5. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.

    Cited by:

    1. Elaine Y. L. Loh, 2007. "An alternative test for weak form efficiency based on technical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(12), pages 1003-1012.
    2. Jia Wang & Hongwei Zhu & Jiancheng Shen & Yu Cao & Benyuan Liu, 2022. "Dual-CLVSA: a Novel Deep Learning Approach to Predict Financial Markets with Sentiment Measurements," Papers 2202.03158, arXiv.org.
    3. Jia Wang & Tong Sun & Benyuan Liu & Yu Cao & Degang Wang, 2021. "Financial Markets Prediction with Deep Learning," Papers 2104.05413, arXiv.org.
    4. Alexandros Milionis & Evangelia Papanagiotou, 2009. "A study of the predictive performance of the moving average trading rule as applied to NYSE, the Athens Stock Exchange and the Vienna Stock Exchange: sensitivity analysis and implications for weak-for," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1171-1186.
    5. Reyes Maroto Illera & Francisco Pérez Bermejo & Simón Sosvilla-Rivero, "undated". "An Eclectic Approach to Currency Crises: Drawing Lessons from the EMS Experience," Working Papers 2002-22, FEDEA.
    6. Alexandros E. Milionis & Evangelia Papanagiotou, 2011. "Decomposing the predictive performance of the moving average trading rule of technical analysis: the contribution of linear and non linear dependencies in stock returns," Working Papers 134, Bank of Greece.
    7. Giuseppe Galloppo, 2009. "Dynamic Asset Allocation Using a Combined Criteria Decision System," Accounting & Taxation, The Institute for Business and Finance Research, vol. 1(1), pages 29-44.
    8. Robert Kremer & Sherrill Shaffer, 2007. "Improving the accuracy of forward exchange rate forecasts by correcting for prior bias," Applied Financial Economics, Taylor & Francis Journals, vol. 17(18), pages 1469-1478.
    9. Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
    10. Marta Gómez-Puig & Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2014. "An update on EMU sovereign yield spread drivers in time of crisis: A panel data analysis," Working Papers 2014-04, Universitat de Barcelona, UB Riskcenter.
    11. Alexandros E. Milionis & Evangelia Papanagiotou, 2008. "A Note on the Use of Moving Average Trading Rules to Test For Weak from Efficiency in Capital Markets," Working Papers 91, Bank of Greece.
    12. Emma Garcia & Simón Sosvilla-rivero, 2005. "Forecasting the dollar|euro exchange rate: are international parities useful?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(5), pages 369-377.
    13. Simón Sosvilla-Rivero & Emma García, "undated". "Forecasting the Dollar/Euro Exchange Rate: Can International Parities Help?," Working Papers 2003-15, FEDEA.
    14. Muhammad Arif & Muddasar Hasan & Abu Bakr & Muhammad Ziaullah & Muhammad Ali Tarer, 2018. "Profitability Of The Moving Averages Technical Trading Rules In An Emerging Stock Market-A Study Of Individual Stocks Listed On Pakistan Stock Exchange," IBT Journal of Business Studies (JBS), Ilma University, Faculty of Management Science, vol. 14(2), pages 67-76.
    15. Simón Sosvilla-Rivero & Reyes Maroto Illera, 2002. "Regimen changes and duration in the European Monetary System," Working Papers 02-05, Asociación Española de Economía y Finanzas Internacionales.
    16. Yan, Isabel K. & Chong, Terence & Lam, Tau-Hing, 2011. "Is the Chinese Stock Market Really Efficient," MPRA Paper 35219, University Library of Munich, Germany.
    17. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    18. Jia Wang & Tong Sun & Benyuan Liu & Yu Cao & Hongwei Zhu, 2021. "CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets," Papers 2104.04041, arXiv.org.
    19. Perez-Rodriguez, Jorge V. & Torra, Salvador & Andrada-Felix, Julian, 2005. "STAR and ANN models: forecasting performance on the Spanish "Ibex-35" stock index," Journal of Empirical Finance, Elsevier, vol. 12(3), pages 490-509, June.
    20. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    21. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    22. Sermpinis, Georgios & Stasinakis, Charalampos & Dunis, Christian, 2014. "Stochastic and genetic neural network combinations in trading and hybrid time-varying leverage effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 21-54.

  6. Simon Sosvilla-Rivero & Julian Andrada-Felix & Fernando Fernandez-Rodriguez, 2002. "Further evidence on technical trade profitability and foreign exchange intervention," Applied Economics Letters, Taylor & Francis Journals, vol. 9(12), pages 827-832.

    Cited by:

    1. Elaine Y. L. Loh, 2007. "An alternative test for weak form efficiency based on technical analysis," Applied Financial Economics, Taylor & Francis Journals, vol. 17(12), pages 1003-1012.
    2. Michael D. McKenzie, 2007. "Technical Trading Rules in Emerging Markets and the 1997 Asian Currency Crises," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 43(4), pages 46-73, August.
    3. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    4. Robert Ślepaczuk & Grzegorz Zakrzewski & Paweł Sakowski, 2012. "Investment strategies beating the market. What can we squeeze from the market?," Working Papers 2012-04, Faculty of Economic Sciences, University of Warsaw.
    5. Yung-Ho Chang & Massoud Metghalchi & Chia-Chung Chan, 2006. "Technical trading strategies and cross-national information linkage: the case of Taiwan stock market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(10), pages 731-743.
    6. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 131-157.
    7. Ślepaczuk Robert & Sakowski Paweł & Zakrzewski Grzegorz, 2018. "Investment Strategies that Beat the Market. What Can We Squeeze from the Market?," Financial Internet Quarterly (formerly e-Finanse), Sciendo, vol. 14(4), pages 36-55, December.

  7. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon & Andrada-Felix, Julian, 1999. "Exchange-rate forecasts with simultaneous nearest-neighbour methods: evidence from the EMS," International Journal of Forecasting, Elsevier, vol. 15(4), pages 383-392, October.

    Cited by:

    1. Golan, Amos & Perloff, Jeffrey M., 2002. "Superior Forecasts of the U.S. Unemployment Rate Using a Nonparametric Method," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt2bw559zk, Department of Agricultural & Resource Economics, UC Berkeley.
    2. Gil Pareja, Salvador & Sosvilla Rivero, Simon, 2004. "Export market integration in the European Union," Journal of Applied Economics, Universidad del CEMA, vol. 7(2), pages 1-31, November.
    3. Simón Sosvilla-Rivero & Julián Andrada-Félix & Fernando Fernández-Rodríguez, "undated". "Further evidence on technical analysis and profitability of foreign exchange intervention," Working Papers 99-01, FEDEA.
    4. Angelos Kanas, 2003. "Non-linear forecasts of stock returns," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 299-315.
    5. Kenneth W Clements & Yihui Lan, 2006. "A New Approach to Forecasting Exchange Rates," Economics Discussion / Working Papers 06-29, The University of Western Australia, Department of Economics.
    6. Meade, Nigel, 2002. "A comparison of the accuracy of short term foreign exchange forecasting methods," International Journal of Forecasting, Elsevier, vol. 18(1), pages 67-83.
    7. Lior Cohen & Marta Gómez-Puig & Simón Sosvilla-Rivero, 2019. "“Has the ECB’s Monetary Policy Prompted Companies to Invest or Pay Dividends?”," IREA Working Papers 201901, University of Barcelona, Research Institute of Applied Economics, revised Jan 2019.
    8. Reyes Maroto Illera & Francisco Pérez Bermejo & Simón Sosvilla-Rivero, "undated". "An Eclectic Approach to Currency Crises: Drawing Lessons from the EMS Experience," Working Papers 2002-22, FEDEA.
    9. Robert Kremer & Sherrill Shaffer, 2007. "Improving the accuracy of forward exchange rate forecasts by correcting for prior bias," Applied Financial Economics, Taylor & Francis Journals, vol. 17(18), pages 1469-1478.
    10. Andrada-Félix Julián & Fernadez-Rodriguez Fernando & Garcia-Artiles Maria-Dolores & Sosvilla-Rivero Simon, 2003. "An Empirical Evaluation of Non-Linear Trading Rules," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(3), pages 1-32, October.
    11. Oscar Bajo-Rubio & Simón Sosvilla-Rivero & Fernando Fernández-Rodríguez, "undated". "Non-Linear Forecasting Methods: Some Applications to the Analysis of Financial Series," Working Papers 2002-01, FEDEA.
    12. Marta Gómez-Puig & Simón Sosvilla-Rivero & María del Carmen Ramos-Herrera, 2014. "An update on EMU sovereign yield spread drivers in time of crisis: A panel data analysis," Working Papers 2014-04, Universitat de Barcelona, UB Riskcenter.
    13. Gómez-Puig, Marta & Sosvilla-Rivero, Simón & Martínez-Zarzoso, Inmaculada, 2022. "On the heterogeneous link between public debt and economic growth," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 77(C).
    14. Andrada-Félix, Julián & Fernández-Rodríguez, Fernando & Fuertes, Ana-Maria, 2016. "Combining nearest neighbor predictions and model-based predictions of realized variance: Does it pay?," International Journal of Forecasting, Elsevier, vol. 32(3), pages 695-715.
    15. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    16. Peter Sephton, 2001. "Forecasting recessions: can we do better on MARS?," Review, Federal Reserve Bank of St. Louis, vol. 83(Mar), pages 39-49.
    17. Kück, Mirko & Freitag, Michael, 2021. "Forecasting of customer demands for production planning by local k-nearest neighbor models," International Journal of Production Economics, Elsevier, vol. 231(C).
    18. Simón Sosvilla-Rivero & Reyes Maroto Illera, 2002. "Regimen changes and duration in the European Monetary System," Working Papers 02-05, Asociación Española de Economía y Finanzas Internacionales.
    19. Gómez Puig, Marta & Sosvilla-Rivero, Simón & Martínez-Zarzoso, Inmaculada, 2019. "Re-examining the debt-growth nexus: A grouped fixed-effect approach," University of Göttingen Working Papers in Economics 374, University of Goettingen, Department of Economics.
    20. Pablo Guerróon‐Quintana & Molin Zhong, 2023. "Macroeconomic forecasting in times of crises," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 295-320, April.
    21. Y. Shi & A. N. Gorban & T. Y. Yang, 2013. "Is it possible to predict long-term success with k-NN? Case Study of four market indices (FTSE100, DAX, HANGSENG, NASDAQ)," Papers 1307.8308, arXiv.org.
    22. Paolo Fornaro & Henri Luomaranta, 2020. "Nowcasting Finnish real economic activity: a machine learning approach," Empirical Economics, Springer, vol. 58(1), pages 55-71, January.
    23. Simón Sosvilla-Rivero & Emma García, "undated". "Purchasing Power Parity Revisited," Working Papers 2003-20, FEDEA.
    24. Heinz, Adrian & Jamaloodeen, Mohamed & Saxena, Atul & Pollacia, Lissa, 2021. "Bullish and Bearish Engulfing Japanese Candlestick patterns: A statistical analysis on the S&P 500 index," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 221-244.
    25. Óscar Bajo Rubio & Simón Sosvilla Rivero & Fernando Fernández Rodríguez, 2000. "Asymmetry In The Ems: New Evidence Based On Non-Linear Forecasts," Documentos de Trabajo - Lan Gaiak Departamento de Economía - Universidad Pública de Navarra 0001, Departamento de Economía - Universidad Pública de Navarra.
    26. Reick, Christian H & Page, Bernd, 2000. "Time series prediction by multivariate next neighbor methods with application to zooplankton forecasts," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 52(3), pages 289-310.
    27. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Nearest-Neighbour Predictions in Foreign Exchange Markets," Working Papers 2002-05, FEDEA.
    28. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    29. Rodríguez-Vargas, Adolfo, 2020. "Forecasting Costa Rican inflation with machine learning methods," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    30. F. FernAndez-RodrIguez & S. Sosvilla-Rivero & J. Andrada-FElix, 2003. "Technical analysis in foreign exchange markets: evidence from the EMS," Applied Financial Economics, Taylor & Francis Journals, vol. 13(2), pages 113-122.
    31. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Technical Analysis in Foreign Exchange Markets: Linear Versus Nonlinear Trading Rules," Working Papers on International Economics and Finance 00-02, FEDEA.
    32. Julián Andrada-Félix & Adrian Fernandez-Perez & Fernando Fernández-Rodríguez, 2015. "Fixed income strategies based on the prediction of parameters in the NS model for the Spanish public debt market," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 6(2), pages 207-245, June.
    33. Julián Andrada Félix & Fernando Fernández Rodríguez & María Dolores García Artiles, 2004. "Non-linear trading rules in the New York Stock Exchange," Documentos de trabajo conjunto ULL-ULPGC 2004-05, Facultad de Ciencias Económicas de la ULPGC.
    34. Arora Siddharth & Little Max A. & McSharry Patrick E., 2013. "Nonlinear and nonparametric modeling approaches for probabilistic forecasting of the US gross national product," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 395-420, September.
    35. Zhang, Ningning & Lin, Aijing & Shang, Pengjian, 2017. "Multidimensional k-nearest neighbor model based on EEMD for financial time series forecasting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 477(C), pages 161-173.
    36. Klender Cortez & Martha del Pilar Rodríguez-García & Samuel Mongrut, 2020. "Exchange Market Liquidity Prediction with the K-Nearest Neighbor Approach: Crypto vs. Fiat Currencies," Mathematics, MDPI, vol. 9(1), pages 1-15, December.
    37. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2010. "Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1652-1669, December.
    38. Simon Sosvilla-Rivero & Julian Andrada-Felix & Fernando Fernandez-Rodriguez, 2002. "Further evidence on technical trade profitability and foreign exchange intervention," Applied Economics Letters, Taylor & Francis Journals, vol. 9(12), pages 827-832.
    39. Arroyo, Javier & Maté, Carlos, 2009. "Forecasting histogram time series with k-nearest neighbours methods," International Journal of Forecasting, Elsevier, vol. 25(1), pages 192-207.

  8. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero Julian, 1997. "Combining information in exchange rate forecasting: evidence from the EMS," Applied Economics Letters, Taylor & Francis Journals, vol. 4(7), pages 441-444.

    Cited by:

    1. Fernandez-Rodriguez, Fernando & Sosvilla-Rivero, Simon, 1998. "Testing nonlinear forecastability in time series: Theory and evidence from the EMS," Economics Letters, Elsevier, vol. 59(1), pages 49-63, April.
    2. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada, "undated". "Exchange-rate forecasts with simultaneous nearest-neighbour methods: Evidence from the EMS," Working Papers 98-17, FEDEA.
    3. Fernando Fernández-Rodríguez & Simón Sosvilla-Rivero & Julián Andrada-Félix, "undated". "Nearest-Neighbour Predictions in Foreign Exchange Markets," Working Papers 2002-05, FEDEA.
    4. Fernando Fernandez-Rodriguez & Simon Sosvilla-Rivero & Maria Dolores Garcia-Artiles, 1997. "Using nearest neighbour predictors to forecast the Spanish stock market," Investigaciones Economicas, Fundación SEPI, vol. 21(1), pages 75-91, January.

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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 3 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-FMK: Financial Markets (2) 2001-05-16 2004-05-26
  2. NEP-FIN: Finance (1) 2004-05-26
  3. NEP-HIS: Business, Economic and Financial History (1) 2011-11-21
  4. NEP-PKE: Post Keynesian Economics (1) 2011-11-21
  5. NEP-RMG: Risk Management (1) 2011-11-21

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