Research classified by Journal of Economic Literature (JEL) codes

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Top JEL
/ C: Mathematical and Quantitative Methods
/ / C4: Econometric and Statistical Methods: Special Topics
/ / / C45: Neural Networks and Related Topics

2017

• León, C. & Moreno, José Fernando & Cely, Jorge, 2017, "Whose Balance Sheet is this? Neural Networks for Banks' Pattern Recognition," Other publications TiSEM, Tilburg University, School of Economics and Management, number 75d8648e-9855-4c5c-9aa9-0.
• Jaime Tinto Arandes & Kléber Antonio Luna Altamirano & William Henry Sarmiento Espinoza & Diego Patricio Cisneros Quintanilla, 2017, "STIM12 creativity model for the design lady shoes under the approach of fuzzy subsets," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, volume 42, issue 44, pages 129-152, july-dece.
• Vasilios Plakandaras & Periklis Gogas & Theophilos Papadimitriou & Rangan Gupta, 2017, "The Informational Content of the Term Spread in Forecasting the US Inflation Rate: A Nonlinear Approach," Journal of Forecasting, John Wiley & Sons, Ltd., volume 36, issue 2, pages 109-121, March.
• Grzegorz Marcjasz & Bartosz Uniejewski & Rafal Weron, 2017, "Importance of the long-term seasonal component in day-ahead electricity price forecasting revisited: Neural network models," HSC Research Reports, Hugo Steinhaus Center, Wroclaw University of Science and Technology, number HSC/17/03, Jul.
• Altgelt, Friederike & Koetter, Michael, 2017, "Too connected to fail? Wie die Vernetzung der Banken staatliche Rettungsmaßnahmen vorhersagen kann," Wirtschaft im Wandel, Halle Institute for Economic Research (IWH), volume 23, issue 4, pages 75-78.
• Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Okhrin, Yarema, 2017, "Tail event driven networks of SIFIs," SFB 649 Discussion Papers, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk, number 2017-004.

2016

• Anne Péguin-Feissolle & Bilel Sanhaji, 2016, "Tests of the Constancy of Conditional Correlations of Unknown Functional Form in Multivariate GARCH Models," Annals of Economics and Statistics, GENES, issue 123-124, pages 77-101, DOI: 10.15609/annaeconstat2009.123-124.0.
• Borghesi, Simone & Flori, Andrea, , "EU ETS Facets in the Net: How Account Types Influence the Structure of the System," MITP: Mitigation, Innovation and Transformation Pathways, Fondazione Eni Enrico Mattei (FEEM), number 232214, DOI: 10.22004/ag.econ.232214.
• Jozwiak, Akos & Milkovics, Matyas & Lakner, Zoltan, None, "A Network-Science Support System for Food Chain Safety: A Case from Hungarian Cattle Production," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, volume 19, issue A, pages 1-26, DOI: 10.22004/ag.econ.240694.
• Yaroslav I. VYKLYUK & Valeriy K. YEVDOKYMENKO & Ihor V. YASKAL, 2016, "The Proportions And Rates Of Economic Activities As A Factor Of Gross Value Added Maximization In Transition Economy," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, volume 63, issue 1, pages 55-64, March.
• Gintaras CERNIUS & Liucija BIRSKYTE & Arturas BALKEVICIUS, 2016, "Influence Of Rules For Computing Corporate Income Tax On The Accuracy Of Financial Statements Of Lithuanian Companies," Scientific Annals of Economics and Business (continues Analele Stiintifice), Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, volume 63, issue 1, pages 65-81, March.
• Özcan Mutlu & Muhammed Ordu & Olcay Polat, 2016, "Comparison of Individual Pension System and Bank's Deposit System for Low-Risk Investors," Alphanumeric Journal, Bahadir Fatih Yildirim, volume 4, issue 2, pages 95-114, September, DOI: http://dx.doi.org/10.17093/aj.2016..
• Evgeniya Kozlova & Vladimir Volynsky, 2016, "A fuzzy model for the evaluation of suppliers of material resources to machine-building enterprises," International Economics, University of Lodz, Faculty of Economics and Sociology, issue 15, pages 245-277, September.
• A?da Kammoun & Imen Triki, 2016, "Credit Scoring Models for a Tunisian Microfinance Institution: Comparison between Artificial Neural Network and Logistic Regression," Review of Economics & Finance, Better Advances Press, Canada, volume 6, pages 61-78, February.
• Carlos León & José Fernando Moreno & Jorge Cely, 2016, "Whose Balance Sheet is this? Neural Networks for Banks’ Pattern Recognition," Borradores de Economia, Banco de la Republica de Colombia, number 959, Sep, DOI: 10.32468/be.959.
• Michael Creel, 2016, "Neural Nets for Indirect Inference," Working Papers, Barcelona School of Economics, number 942, Nov.
• Jonnathan R. Cáceres Santos, 2016, "Pronóstico de la actividad económica con base en el volumen transaccional - caso boliviano," Revista de Análisis del BCB, Banco Central de Bolivia, volume 24, issue 1, pages 115-145, June.
• José Alberto Molina & Alberto Alcolea & Alfredo Ferrer & Alberto Alcolea & David Iñiguez & Alejandro Rivero & Gonzalo Ruiz & Alfonso Tarancón, 2016, "Co-authorship and Academic Productivity in Economics: Interaction Maps from the Complex Networks Approach," Boston College Working Papers in Economics, Boston College Department of Economics, number 914, Jun.
• Oscar Claveria & Enric Monte & Salvador Torra, 2016, "A self-organizing map analysis of survey-based agents? expectations before impending shocks for model selection: The case of the 2008 financial crisis," International Economics, CEPII research center, issue 146, pages 40-58.
• Gustavo Peralta, 2016, "The Nature of Volatility Spillovers across the International Capital Markets," CNMV Working Papers, CNMV- Spanish Securities Markets Commission - Research and Statistics Department, number CNMV Working Papers no. 6.
• Andrej Srakar & Petja Grafenauer & Marilena Vecco, 2016, "Being Central and Productive? Evidence from Slovenian Visual Artists in the 19th and 20th Century," ACEI Working Paper Series, Association for Cultural Economics International, number AWP-09-2016, Sep, revised Sep 2016.
• Vasile GEORGESCU, 2016, "Using Nature-Inspired Metaheuristics to Train Predictive Machines," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, volume 50, issue 2, pages 5-24.
• Cătălina-Lucia COCIANU & Hakob GRIGORYAN, 2016, "Machine Learning Techniques For Stock Market Prediction.Acase Study Of Omv Petrom," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, volume 50, issue 3, pages 63-82.
• Vergote, Olivier, 2016, "Credit risk spillover between financials and sovereigns in the euro area during 2007-2015," Working Paper Series, European Central Bank, number 1898, Apr.
• Kok, Christoffer & Montagna, Mattia, 2016, "Multi-layered interbank model for assessing systemic risk," Working Paper Series, European Central Bank, number 1944, Aug.
• Endrész, Marianna & Skudelny, Frauke, 2016, "Crisis severity and the international trade network," Working Paper Series, European Central Bank, number 1971, Oct.
• Baruník, Jozef & Malinská, Barbora, 2016, "Forecasting the term structure of crude oil futures prices with neural networks," Applied Energy, Elsevier, volume 164, issue C, pages 366-379, DOI: 10.1016/j.apenergy.2015.11.051.
• Kiani, Khurshid M., 2016, "On business cycle fluctuations in USA macroeconomic time series," Economic Modelling, Elsevier, volume 53, issue C, pages 179-186, DOI: 10.1016/j.econmod.2015.11.022.
• Ductor, Lorenzo & Leiva-Leon, Danilo, 2016, "Dynamics of global business cycle interdependence," Journal of International Economics, Elsevier, volume 102, issue C, pages 110-127, DOI: 10.1016/j.jinteco.2016.07.003.
• Claveria, Oscar & Monte, Enric & Torra, Salvador, 2016, "A self-organizing map analysis of survey-based agents׳ expectations before impending shocks for model selection: The case of the 2008 financial crisis," International Economics, Elsevier, volume 146, issue C, pages 40-58, DOI: 10.1016/j.inteco.2015.11.003.
• Simone Borghesi & Andrea Flori, 2016, "EU ETS Facets in the Net: How Account Types Influence the Structure of the System," Working Papers, Fondazione Eni Enrico Mattei, number 2016.08, Jan.
• Ben R. Craig & Martin Saldias Zambrana, 2016, "Spatial Dependence and Data-Driven Networks of International Banks," Working Papers (Old Series), Federal Reserve Bank of Cleveland, number 1627, Dec.
• David E. Allen & Michael McAleer & Shelton Peiris & Abhay K. Singh, 2016, "Nonlinear Time Series and Neural-Network Models of Exchange Rates between the US Dollar and Major Currencies," Risks, MDPI, volume 4, issue 1, pages 1-14, March.
• Leoni Eleni Oikonomikou, 2016, "Forecasting the Market Risk Premium with Artificial Neural Networks," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers, Courant Research Centre PEG, number 202, Apr.
• Leoni Eleni Oikonomikou, 2016, "Comparing the market risk premia forecasts in JSE and NYSE equity markets," Courant Research Centre: Poverty, Equity and Growth - Discussion Papers, Courant Research Centre PEG, number 203, Apr.
• Anne Peguin-Feissolle & Bilel Sanhaji, 2016, "Tests of the Constancy of Conditional Correlations of Unknown Functional Form in Multivariate GARCH Models," Post-Print, HAL, number hal-04218472, DOI: 10.15609/annaeconstat2009.123-124.0.
• Fahima Charef & Fethi Ayachi, 2016, "A Comparison between Neural Networks and GARCH Models in Exchange Rate Forecasting," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, volume 6, issue 1, pages 94-99, January.
• Fahima Charef & Fethi Ayachi, 2016, "A Comparison between Neural Networks and GARCH Models in Exchange Rate Forecasting," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, volume 6, issue 1, pages 244-253, January.
• Stephanie Valdivia & Arturo Morales, 2016, "Determinants Of The Index Of Prices And Quotations On The Mexican Stock Exchange: Sensitivity Analysis Based On Artificial Neural Networks," Global Journal of Business Research, The Institute for Business and Finance Research, volume 10, issue 2, pages 27-32.
• Mr. Alexei P Kireyev & Andrei Leonidov, 2016, "A Network Model of Multilaterally Equilibrium Exchange Rates," IMF Working Papers, International Monetary Fund, number 2016/130, Jul.
• Ben Craig & Martín Saldías, 2016, "Spatial Dependence and Data-Driven Networks of International Banks," IMF Working Papers, International Monetary Fund, number 2016/184, Sep.
• Michel Philipp & Achim Zeileis & Carolin Strobl, 2016, "A Toolkit for Stability Assessment of Tree-Based Learners," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2016-11, May.
• Florian Wickelmaier & Achim Zeileis, 2016, "Using Recursive Partitioning to Account for Parameter Heterogeneity in Multinomial Processing Tree Models," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2016-26, Sep.
• Molina, José Alberto & Alcolea, Alberto & Ferrer, Alfredo & Iñiguez, David & Rivero, Alejandro & Ruiz, Gonzalo & Tarancón, Alfonso, 2016, "Co-authorship and Academic Productivity in Economics: Interaction Maps from the Complex Networks Approach," IZA Discussion Papers, IZA Network @ LISER, number 10008, Jun.
• Julian Hagenauer, 2016, "Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks," Journal of Geographical Systems, Springer, volume 18, issue 1, pages 1-15, January, DOI: 10.1007/s10109-015-0220-8.
• Julian Hagenauer, 2016, "Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks," Journal of Geographical Systems, Springer, volume 18, issue 1, pages 1-15, January, DOI: 10.1007/s10109-015-0220-8.
• Salehi, Mehdi & Hamidehpour, Kiana & Khadem, Hamid, 2016, "Comparison of Forecasting the Index Price Movement in Financial Institutions using Artificial Intelligence," Journal of Monetary and Banking Research (فصلنامه پژوهش‌های پولی-بانکی), Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, volume 9, issue 27, pages 131-170, April.
• Áron Horváth & Blanka Imre & Zoltán Sápi, 2016, "The International Practice of Statistical Property Valuation Methods and the Possibilities of Introducing Automated Valuation Models in Hungary," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), volume 15, issue 4, pages 45-64.
• Ricardo Artemio Chávez Meza & Arturo Ángel Lara Rivero, 2016, "The diversity of agents and evolution of overlapping patents on electric vehicles," Contaduría y Administración, Accounting and Management, volume 61, issue 4, pages 603-628, Octubre-D.
• Daniel Goetz, 2016, "Broadband Mergers and Dynamic Bargaining: An Application to Netflix," Working Papers, NET Institute, number 16-07, Sep.
• Xiao Liu & Dokyun Lee & Kannan Srinivasan, 2016, "The Effect of Word of Mouth on Sales: New Answers from the Comprehensive Consumer Journey Data," Working Papers, NET Institute, number 16-09, Sep.
• Monika Hadas-Dyduch & Adam P. Balcerzak & Michal Bernard Pietrzak, 2016, "Wavelet Analisis of Unemployment Rate in Visegrad Countries," Chapters, Institute of Economic Research, in: Tomas Kliestik, "16th International Scientific Conference Globalization and Its Socio-Economic Consequences. University of Zilina, The Faculty of Operation and Economi".
• Monika Hadas-Dyduch & Michal Bernard Pietrzak & Adam P. Balcerzak, 2016, "Wavelet Analysis of Unemployment Rate in Visegrad Countries," Working Papers, Institute of Economic Research, number 37/2016, Sep, revised Sep 2016.
• Gawlik, Remigiusz, 2016, "Methodological Aspects of Qualitative-Quantitative Analysis of Decision-Making Processes," MPRA Paper, University Library of Munich, Germany, number 72362, Jun.
• Basihos, Seda, 2016, "Nightlights as a Development Indicator: The Estimation of Gross Provincial Product (GPP) in Turkey," MPRA Paper, University Library of Munich, Germany, number 75553, May, revised 09 Sep 2016.
• Aviral Kumar Tiwari & Rangan Gupta & Stelios Bekiros, 2016, "Chaos in G7 Stock Markets using Over One Century of Data: A Note," Working Papers, University of Pretoria, Department of Economics, number 201678, Oct.
• Peter F. Kaznacheev (Казначеев, Петр) & Regina V. Samoilova (Самойлова, Регина) & Nikola V. Kjurchiski (Курчиски, Никола), 2016, "Improving Efficiency of the Oil and Gas Sector and Other Extractive Industries by Applying Methods of Artificial Intelligence
  [Применение Методов Искусственного Интеллекта Для Повышения Эффективности В Нефтегазовой И Других Сырьевых Отраслях]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, volume 5, pages 188-197, October.
• Loretta Mastroeni & Pierluigi Vellucci, 2016, "“Butterfly Effect" vs Chaos in Energy Futures Markets," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0209, Oct.
• Chun Wei R. Lin & Yun-Jiuan Melody Parng & Hong-Yi Chen, 2016, "A Fuzzy-Neural Performance Evaluation Approach of Selecting Outsource International Logistic Company," Proceedings of Economics and Finance Conferences, International Institute of Social and Economic Sciences, number 3205849, Mar.
• Şerafettin SEVİM & Birol YILDIZ & Nilüfer DALKILIÇ, 2016, "Risk Assessment for Accounting Professional Liability Insurance," Sosyoekonomi Journal, Sosyoekonomi Society, issue 24(29).
• Ali Babikir & Henry Mwambi, 2016, "Evaluating the combined forecasts of the dynamic factor model and the artificial neural network model using linear and nonlinear combining methods," Empirical Economics, Springer, volume 51, issue 4, pages 1541-1556, December, DOI: 10.1007/s00181-015-1049-1.
• Oscar Claveria & Enric Monte & Salvador Torra, 2016, "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, volume 7, issue 3, pages 341-357, August, DOI: 10.1007/s13209-016-0144-7.
• Anders Bredahl Kock & Timo Teräsvirta, 2016, "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, volume 35, issue 8-10, pages 1753-1779, December, DOI: 10.1080/07474938.2015.1035163.
• Vladyslav Rashkovan & Dmytro Pokidin, 2016, "Ukrainian Banks' Business Models Clustering: Application of Kohonen Neural Networks," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 238, pages 13-38, DOI: 10.26531/vnbu2016.238.013.
• Alberto José Hurtado Briceño, 2016, "Measuring the impact of Mision Alimentacion in Merida by means of fuzzy logic," Economía, Instituto de Investigaciones Económicas y Sociales (IIES). Facultad de Ciencias Económicas y Sociales. Universidad de Los Andes. Mérida, Venezuela, volume 41, issue 42, pages 105-132, july-dece.
• Francis Bismans & Igor N. Litvine, 2016, "Forecasting with Neural Networks Models," Working Papers of BETA, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg, number 2016-28.
• EMAMVERDI, Ghodratollah & KARIMI, Mohammad Sharif & KHAKIE, Sima & KARIMI, Mojtaba, 2016, "Forecasting The Total Index Of Tehran Stock Exchange," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 20, issue 1, pages 54-68.
• Muczyński Andrzej & Walacik Marek, 2016, "Neural Networks Modelling of Municipal Real Estate Market Rent Rates," Folia Oeconomica Stetinensia, Sciendo, volume 16, issue 2, pages 17-28, December, DOI: 10.1515/foli-2016-0022.
• Kaczmarczyk Paweł, 2016, "Integrated Model of Demand for Telephone Services in Terms of Microeconometrics," Folia Oeconomica Stetinensia, Sciendo, volume 16, issue 2, pages 72-83, December, DOI: 10.1515/foli-2016-0026.
• Ćorić, Ivica, 2016, "Comparison of Multivariate Statistical Analysis and Machine Learning Methods in Retailing: Research Framework Proposition," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2016), Rovinj, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 8-9 September 2016".
• Bilal Zorić, Alisa, 2016, "Determinants of Efficacy of Studying in the Republic Croatia - Comparing Neural Networks and Decision Trees: Research Framework Proposition," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2016), Rovinj, Croatia, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 8-9 September 2016".
• Alisa Bilal Zoric, 2016, "Predicting customer churn in banking industry using neural networks," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, volume 14, issue 2, pages 116-124.

2015

• Anne Péguin-Feissolle & Bilel Sanhaji, 2015, "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers, Aix-Marseille School of Economics, France, number 1516, Mar.
• Sihem Khemakhem & Younes Boujelbene, 2015, "Credit Risk Prediction: A Comparative Study between Discriminant Analysis and the Neural Network Approach," Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, volume 14, issue 1, pages 60-78, March.
• Aida Krichene Abdelmoula, 2015, "Bank Credit Risk Analysis with K-Nearest-Neighbor Classifier: Case of Tunisian Banks," Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, volume 14, issue 1, pages 79-106, March.
• Vesile Sinem Arıkan Kargı, 2015, "A Comparison of Artificial Neural Networks and Multiple Linear Regression Models As Predictors of Discard Rates In Plastic Injection Molding," Alphanumeric Journal, Bahadir Fatih Yildirim, volume 3, issue 2, pages 65-72, December, DOI: http://dx.doi.org/10.17093/aj.2015..
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Multiple-input multiple-output vs. single-input single-output neural network forecasting”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201502, Jan, revised Jan 2015.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Effects of removing the trend and the seasonal component on the forecasting performance of artificial neural network techniques”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201503, Jan, revised Jan 2015.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Regional Forecasting with Support Vector Regressions: The Case of Spain”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201506, Jan, revised Jan 2015.
• 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, University of Barcelona, Regional Quantitative Analysis Group, number 201508, Mar, revised Mar 2015.
• Jozef Barunik & Barbora Malinska, 2015, "Forecasting the term structure of crude oil futures prices with neural networks," Papers, arXiv.org, number 1504.04819, Apr.
• Ferdi SONMEZ & Metin ZONTUL & Sahamet BULBUL, 2015, "Estimating Deposit Banks Profitability with Artificial Neural Networks: A Software Model Design," Journal of BRSA Banking and Financial Markets, Banking Regulation and Supervision Agency, volume 9, issue 1, pages 9-46.
• Jasna Soldić-Aleksić & Rade Stankić, 2015, "A Comparative Analysis Of Serbia And The Eu Member States In The Context Of The Networked Readiness Index Values," Economic Annals, Faculty of Economics and Business, University of Belgrade, volume 60, issue 206, pages 45-86, July - Se.
• S Battiston & G di Iasio & L Infante & F Pierobon, 2015, "Capital and contagion in financial networks," IFC Bulletins chapters, Bank for International Settlements, in: Bank for International Settlements, "Indicators to support monetary and financial stability analysis: data sources and statistical methodologies".
• Zekić-Sušac Marijana & Has Adela, 2015, "Data Mining as Support to Knowledge Management in Marketing," Business Systems Research, Sciendo, volume 6, issue 2, pages 18-30, September, DOI: 10.1515/bsrj-2015-0008.
• Margherita Comola & Mariapia Mendola, 2015, "Formation of Migrant Networks," Scandinavian Journal of Economics, Wiley Blackwell, volume 117, issue 2, pages 592-618, April.
• Jonnathan Cáceres Santos, 2015, "Identificación de instituciones financieras sistémicamente importantes en Bolivia a través de la construcción de mapas auto-organizados. Aproximaciones macro y microprudencial," Serie de Documentos de Trabajo, Banco Central de Bolivia, number 2015/01, Oct.
• David Bholat & Stephen Hans & Pedro Santos & Cheryl Schonhardt-Bailey, 2015, "Text mining for central banks," Handbooks, Centre for Central Banking Studies, Bank of England, number 33, April.
• Lorenzo Ductor & Danilo Leiva-Leon, 2015, "Dynamics of Global Business Cycles Interdependence," Working Papers Central Bank of Chile, Central Bank of Chile, number 763, Jul.
• Mihaela GHEORGHE, 2015, "A Support Vector Machine Approach For Developing Telemedicine Solutions: Medical Diagnosis," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 5, pages 43-48, June.
• Gustavo Peralta, 2015, "Network-based Measures as Leading Indicators of Market Instability: The case of the Spanish Stock," CNMV Working Papers, CNMV- Spanish Securities Markets Commission - Research and Statistics Department, number CNMV Working Papers no 59.
• Åžebnem KOLTAN YILMAZ & M. Mustafa YÃœCEL, 2015, "Concrete strength control charts pattern recognition based on Linear Vector Quantization neural networks," Eurasian Eononometrics, Statistics and Emprical Economics Journal, Eurasian Academy Of Sciences, volume 2, issue 2, pages 1-15, February, DOI: 10.17740/eas.stat.2015-V2-01.
• Astebro , Thomas & Akdemir , Canan & Elhedhli , Samir, 2015, "Classification Models Via Tabu Search: An Application to Early Stage Venture Classification," HEC Research Papers Series, HEC Paris, number 1097, Oct.
• Bekiros, Stelios D., 2015, "Heuristic learning in intraday trading under uncertainty," Journal of Empirical Finance, Elsevier, volume 30, issue C, pages 34-49, DOI: 10.1016/j.jempfin.2014.11.002.
• Castelli, Mauro & Vanneschi, Leonardo & De Felice, Matteo, 2015, "Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case," Energy Economics, Elsevier, volume 47, issue C, pages 37-41, DOI: 10.1016/j.eneco.2014.10.009.
• Sánchez Lasheras, Fernando & de Cos Juez, Francisco Javier & Suárez Sánchez, Ana & Krzemień, Alicja & Riesgo Fernández, Pedro, 2015, "Forecasting the COMEX copper spot price by means of neural networks and ARIMA models," Resources Policy, Elsevier, volume 45, issue C, pages 37-43, DOI: 10.1016/j.resourpol.2015.03.004.
• Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015, "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, volume 34, issue C, pages 273-292, DOI: 10.1016/j.pacfin.2015.03.002.
• Khediri, Karim Ben & Charfeddine, Lanouar & Youssef, Slah Ben, 2015, "Islamic versus conventional banks in the GCC countries: A comparative study using classification techniques," Research in International Business and Finance, Elsevier, volume 33, issue C, pages 75-98, DOI: 10.1016/j.ribaf.2014.07.002.
• Allen, D.E. & McAleer, M.J. & Peiris, S. & Singh, A.K., 2015, "Nonlinear time series and neural-network models of exchange rates between the US dollar and major currencies," Econometric Institute Research Papers, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute, number EI2015-33, Nov.
• Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015, "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 65, issue 2, pages 144-166, April.
• Jozef Barunik & Barbora Malinska, 2015, "Forecasting the Term Structure of Crude Oil Futures Prices with Neural Networks," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2015/25, Nov, revised Nov 2015.
• Càmara-Turull, X. & Fernández Izquierdo, M.A. & Sorrosal Forradellas, M.T., 2015, "How Do Different Time Spans Affect The Prediction Accuracy Of Business Failure?," Fuzzy Economic Review, International Association for Fuzzy-set Management and Economy (SIGEF), volume 0, issue 1, pages 71-89, May.
• Margherita Comola & M. Mendola, 2015, "The Formation of Migrant Networks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers), HAL, number hal-00977544, Apr, DOI: 10.1111/sjoe.12093.
• Margherita Comola & M. Mendola, 2015, "The Formation of Migrant Networks," Post-Print, HAL, number hal-00977544, Apr, DOI: 10.1111/sjoe.12093.
• Margherita Comola & M. Mendola, 2015, "The Formation of Migrant Networks," PSE-Ecole d'économie de Paris (Postprint), HAL, number hal-00977544, Apr, DOI: 10.1111/sjoe.12093.
• Samir Elhedhli & Canan Akdemir & Thomas Astebro, 2015, "Classification Models Via Tabu Search: An Application to Early Stage Venture Classification," Working Papers, HAL, number hal-02002758, Jul.
• Anne Péguin-Feissolle & Bilel Sanhaji, 2015, "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," Working Papers, HAL, number halshs-01133751, Mar.
• Green, Rikard, 2015, "A Power Market Forward Curve with Hydrology Dependence An Approach based on Artificial Neural Networks," Knut Wicksell Working Paper Series, Lund University, Knut Wicksell Centre for Financial Studies, number 2015/1, Jan.
• Kasa, Richard, 2015, "Approximating Innovation Potential With Neurofuzzy Robust Model / Aproximación Al Potencial Innovador Con Un Modelo Robusto De Neuro-Fuzzy," Investigaciones Europeas de Dirección y Economía de la Empresa (IEDEE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), volume 21, issue 1, pages 35-46.
• Jitendra Aswani, 2015, "Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science," Indira Gandhi Institute of Development Research, Mumbai Working Papers, Indira Gandhi Institute of Development Research, Mumbai, India, number 2015-020, Jul.
• Marjolein Fokkema & Niels Smits & Achim Zeileis & Torsten Hothorn & Henk Kelderman, 2015, "Detecting Treatment-Subgroup Interactions in Clustered Data with Generalized Linear Mixed-Effects Model Trees," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2015-10, Sep.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Multiple-input multiple-output vs. single-input single-output neural network forecasting”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201502, Jan, revised Jan 2015.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Effects of removing the trend and the seasonal component on the forecasting performance of artificial neural network techniques”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201503, Jan, revised Jan 2015.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Regional Forecasting with Support Vector Regressions: The Case of Spain”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201507, Jan, revised Jan 2015.
• Oscar Claveria & Enric Monte & Salvador Torra, 2015, "“Self-organizing map analysis of agents' expectations. Different patterns of anticipation of the 2008 financial crisis”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201511, Mar, revised Mar 2015.
• Meysam Effati & Jean-Claude Thill & Shahin Shabani, 2015, "Geospatial and machine learning techniques for wicked social science problems: analysis of crash severity on a regional highway corridor," Journal of Geographical Systems, Springer, volume 17, issue 2, pages 107-135, April, DOI: 10.1007/s10109-015-0210-x.
• Ádám Banai & András Kollarik & András Szabó-Solticzky, 2015, "Topology of the foreign currency/forint swap market," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), volume 14, issue 2, pages 28-157.
• Wenyun Tang & Lin Cheng, 2015, "Analyzing Multiday Route Choice Behavior using GPS Data," Working Papers, University of Minnesota: Nexus Research Group, number 000135.
• Goldstone, Robert L., 2015, "Homo Economicus and Homo Sapiens," Review of Behavioral Economics, now publishers, volume 2, issue 1-2, pages 77-87, July, DOI: 10.1561/105.00000019.
• Tomasz Jasinski & Agnieszka Scianowska, 2015, "Security Assessment And Optimization Of Energy Supply (Neural Networks Approach)," Oeconomia Copernicana, Institute of Economic Research, volume 6, issue 2, pages 129-141, June, DOI: 10.12775/OeC.2015.016.
• Kulaksizoglu, Tamer, 2015, "Measuring the Core Inflation in Turkey with the SM-AR Model," MPRA Paper, University Library of Munich, Germany, number 62653, Mar.
• Matkovskyy, Roman & Bouraoui, Taoufik & Hammami, Helmi, 2015, "Estimation and prediction of an Index of Financial Safety of Tunisia," MPRA Paper, University Library of Munich, Germany, number 74573, revised 2016.
• Marcos Álvarez-Díaz & Rangan Gupta, 2015, "Forecasting the US CPI: Does Nonlinearity Matter?," Working Papers, University of Pretoria, Department of Economics, number 201512, Mar.
• Periklis Gogas & Theophilos Papadimitriou & Vasilios Plakandaras & Rangan Gupta, 2015, "The Informational Content of the Term-Spread in Forecasting the U.S. Inflation Rate: A Nonlinear Approach," Working Papers, University of Pretoria, Department of Economics, number 201548, Jun.
• Ramaprasad Bhar & A.G. Malliaris & Mary Malliaris, 2015, "Quantitative Easing and the U.S. Stock Market: A Decision Tree Analysis," Review of Economic Analysis, Digital Initiatives at the University of Waterloo Library, volume 7, issue 2, pages 135-156, December.
• Corina SAMAN, 2015, "Out-Of-Sample Forecasting Performance Of A Robust Neural Exchange Rate Model Of Ron/Usd," Journal for Economic Forecasting, Institute for Economic Forecasting, volume 0, issue 1, pages 93-106, March.
• Muhamed Kudic & Wilfried Ehrenfeld & Toralf Pusch, 2015, "On the trail of core–periphery patterns in innovation networks: measurements and new empirical findings from the German laser industry," The Annals of Regional Science, Springer;Western Regional Science Association, volume 55, issue 1, pages 187-220, October, DOI: 10.1007/s00168-015-0679-8.
• Shiyi Chen & Kiho Jeong & Wolfgang Härdle, 2015, "Recurrent support vector regression for a non-linear ARMA model with applications to forecasting financial returns," Computational Statistics, Springer, volume 30, issue 3, pages 821-843, September, DOI: 10.1007/s00180-014-0543-9.
• Harun Özkan & M. Yazgan, 2015, "Is forecasting inflation easier under inflation targeting?," Empirical Economics, Springer, volume 48, issue 2, pages 609-626, March, DOI: 10.1007/s00181-013-0793-3.
• David E. Allen & Michael McAleer & Shelton Peiris & Abhay K. Singh, 2015, "Nonlinear Time Series and Neural-Network Models of Exchange Rates between the US Dollar and Major Currencies," Tinbergen Institute Discussion Papers, Tinbergen Institute, number 15-125/III, Nov.
• Kim Ristolainen, 2015, "Were the Scandinavian Banking Crises Predictable? A Neural Network Approach," Discussion Papers, Aboa Centre for Economics, number 99, Jan.
• Dmytro Pokidin, 2015, "National Bank of Ukraine Econometric Model for the Assessment of Banks' Credit Risk and Support Vector Machine Alternative," Visnyk of the National Bank of Ukraine, National Bank of Ukraine, issue 234, pages 52-72, DOI: 10.26531/vnbu2015.234.052.
• Bilal Zorić, Alisa, 2015, "Case Study in Banking Using Neural Networks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2015), Kotor, Montengero, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb, "Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015".
• Kudic, Muhamed & Ehrenfeld, Wilfried & Pusch, Toralf, 2015, "Isolation and Innovation – Two Contradictory Concepts? Explorative Findings from the German Laser Industry," IWH Discussion Papers, Halle Institute for Economic Research (IWH), number 1/2015.
• Kreuchauff, Florian & Korzinov, Vladimir, 2015, "A patent search strategy based on machine learning for the emerging field of service robotics," Working Paper Series in Economics, Karlsruhe Institute of Technology (KIT), Department of Economics and Management, number 71, DOI: 10.5445/IR/1000049790.
• Kephart, Curtis & Friedman, Daniel & Baumer, Matt, 2015, "Emergence of networks and market institutions in a large virtual economy," Discussion Papers, Research Professorship Market Design: Theory and Pragmatics, WZB Berlin Social Science Center, number SP II 2015-502.

2014

• Mary Violeta Bar, 2014, "The Computational Intelligence Techniques For Predictions - Artificial Neural Networks," Annals of University of Craiova - Economic Sciences Series, University of Craiova, Faculty of Economics and Business Administration, volume 2, issue 42, pages 184-190.
• Miklós Virág & Tamás Nyitrai, 2014, "Is there a trade-off between the predictive power and the interpretability of bankruptcy models? The case of the first Hungarian bankruptcy prediction model," Acta Oeconomica, Akadémiai Kiadó, Hungary, volume 64, issue 4, pages 419-440, December.
• Oscar Claveria & Enric Monte & Salvador Torra, 2014, "“A multivariate neural network approach to tourism demand forecasting”," AQR Working Papers, University of Barcelona, Regional Quantitative Analysis Group, number 201410, May, revised May 2014.
• Danilo Leiva-Leon, 2014, "A New Approach to Infer Changes in the Synchronization of Business Cycle Phases," Staff Working Papers, Bank of Canada, number 14-38, DOI: 10.34989/swp-2014-38.
• Zekić-Sušac Marijana & Pfeifer Sanja & Šarlija Nataša, 2014, "A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem," Business Systems Research, Sciendo, volume 5, issue 3, pages 82-96, September, DOI: 10.2478/bsrj-2014-0021.
• David Matesanz & Benno Torgler & Germán Dabat & Guillermo J. Ortega, 2014, "Co-movements in commodity prices: a note based on network analysis," Agricultural Economics, International Association of Agricultural Economists, volume 45, issue S1, pages 13-21, November.
• Julien Boelaert, 2014, "Une seule fonction de demande ?. Une enquête sur la stabilité des préférences par mélanges discrets de réseaux de neurones," Revue économique, Presses de Sciences-Po, volume 65, issue 4, pages 515-535.
• Charle Augusto Londono & Juan Carlos Correa & Mauricio Lopera, 2014, "Estimación bayesiana del valor en riesgo: una aplicación para el mercado de valores colombiano," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID.
• Mauricio Lopera & Ram�n Javier Mesa & Charle Londo�o, 2014, "Evaluando las intervenciones cambiarias en Colombia: 2004-2012," Estudios Gerenciales, Universidad Icesi.
• KRINGS, Gautier M & CARPANTIER, Jean-François & DELVENNE, Jean-Charles, 2014, "Trade integration and trade imbalances in the European Union: a network perspective," LIDAM Reprints CORE, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE), number 2619, Jan.
• Claveria, Oscar & Torra, Salvador, 2014, "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, volume 36, issue C, pages 220-228, DOI: 10.1016/j.econmod.2013.09.024.
• Papadimitriou, Theophilos & Gogas, Periklis & Stathakis, Efthimios, 2014, "Forecasting energy markets using support vector machines," Energy Economics, Elsevier, volume 44, issue C, pages 135-142, DOI: 10.1016/j.eneco.2014.03.017.
• Yu, Lean & Zhao, Yang & Tang, Ling, 2014, "A compressed sensing based AI learning paradigm for crude oil price forecasting," Energy Economics, Elsevier, volume 46, issue C, pages 236-245, DOI: 10.1016/j.eneco.2014.09.019.
• 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, volume 30, issue C, pages 21-54, DOI: 10.1016/j.intfin.2014.01.006.
• Kock, Anders Bredahl & Teräsvirta, Timo, 2014, "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, volume 30, issue 3, pages 616-631, DOI: 10.1016/j.ijforecast.2013.01.003.
• Abbruzzo, Antonino & Brida, Juan Gabriel & Scuderi, Raffaele, 2014, "Determinants of individual tourist expenditure as a network: Empirical findings from Uruguay," Tourism Management, Elsevier, volume 43, issue C, pages 36-45, DOI: 10.1016/j.tourman.2014.01.014.
• Mahmut ZORTUK & Berna BESER, 2014, "Disa Aciklik ve Demokratik Yapinin Kamu Kesimi Buyuklugu Uzerindeki Etkisi: Rodrik Hipotezine Gecis Ekonomilerinden Kanit," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, volume 14, issue 3, pages 345-359.
• Selahattin YAVUZ & Muhammet DEVECI, 2014, "Bulanik TOPSIS ve Bulanik VIKOR Yontemleriyle Alisveris Merkezi Kurulus Yeri Secimi ve Bir Uygulama," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, volume 14, issue 3, pages 463-479.
• Meltem KARAATLI & Serpil SENAL & Mahmut Sami OZTURK, 2014, "Suleyman Demirel Universitesi, Iktisadi ve Idari Bilimler Fakultesi, Isletme Bolumu," Ege Academic Review, Ege University Faculty of Economics and Administrative Sciences, volume 14, issue 4, pages 637-648.
• Bozena Bobkova, 2014, "On Estimation of Gravity Equation: A Cluster Analysis," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2014/37, Dec, revised Dec 2014.
• Jasmina ARIFOVIC & Murat YILDIZOGLU, 2014, "Learning the Ramsey outcome in a Kydland & Prescott economy," Cahiers du GREThA (2007-2019), Groupe de Recherche en Economie Théorique et Appliquée (GREThA), number 2014-06.
• Samir Elhedhli & Canan Akdemir & Thomas Astebro, 2014, "Classification models via Tabu search: An application to early stage venture classification," Post-Print, HAL, number hal-01066492, Dec, DOI: 10.1016/j.eswa.2014.07.010.
• Selin Devrim ÖZDEMİR & Işıl AKGÜL, 2014, "Hisse Senedi Piyasalarının Kaotik Yapısı ve Yapay Sinir Ağları ile öngörüsü: IMKB-100 örneği," Iktisat Isletme ve Finans, Bilgesel Yayincilik, volume 29, issue 336, pages 31-58.
• Torsten Hothorn & Achim Zeileis, 2014, "partykit: A Modular Toolkit for Recursive Partytioning in R," Working Papers, Faculty of Economics and Statistics, Universität Innsbruck, number 2014-10, Mar.
• Oscar Claveria & Enric Monte & Salvador Torra, 2014, "“A multivariate neural network approach to tourism demand forecasting”," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 201417, May, revised May 2014.
• Comola, Margherita & Mendola, Mariapia, 2014, "The Formation of Migrant Networks," IZA Discussion Papers, IZA Network @ LISER, number 7981, Feb.
• Grubinger, Thomas & Zeileis, Achim & Pfeiffer, Karl-Peter, 2014, "evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R," Journal of Statistical Software, Foundation for Open Access Statistics, volume 61, issue i01, DOI: http://hdl.handle.net/10.18637/jss..
• Elena Olmedo, 2014, "Forecasting Spanish Unemployment Using Near Neighbour and Neural Net Techniques," Computational Economics, Springer;Society for Computational Economics, volume 43, issue 2, pages 183-197, February, DOI: 10.1007/s10614-013-9371-1.
• Gheorghe H. Popescu & Elvira Nica, 2014, "Neuroeconomic Models of Decision-Making," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, volume 6, issue 1, pages 63-66, March.
• Ömer Akgöbek & Emre Yakut, 2014, "Efficiency measurement in Turkish manufacturing sector using Data Envelopment Analysis (DEA) and Artificial Neural Networks (ANN)," Journal of Economic and Financial Studies (JEFS), LAR Center Press, volume 2, issue 3, pages 35-45, June.
• Reinhold Decker, 2014, "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, LAR Center Press, volume 4, issue 11, pages 60-70, November.
• Reinhold Decker, 2014, "Real-Time Analysis of Online Product Reviews by Means of Multi-Layer Feed-Forward Neural Networks," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, volume 4, issue 11, pages 60-70, November.
• Ricardo Figueiredo Summa & Leonardo Macrini, 2014, "Os determinantes da inflação brasileira recente: estimações utilizando redes neurais [Determinants of recent Brazilian inflation: Estimates using neural networks]," Nova Economia, Economics Department, Universidade Federal de Minas Gerais (Brazil), volume 24, issue 2, pages 279-296, May-Augus.
• Dan Farhat, 2014, "Artificial Neural Networks and Aggregate Consumption Patterns in New Zealand:," Working Papers, University of Otago, Department of Economics, number 1404, Mar, revised Mar 2014.
• Dan Farhat, 2014, "Information Processing, Pattern Transmission and Aggregate Consumption Patterns in New Zealand:," Working Papers, University of Otago, Department of Economics, number 1405, Mar, revised Mar 2014.
• Tomasz Jasinski & Agnieszka Scianowska, 2014, "Security Assessment and Optimization of Energy Supply," Working Papers, Institute of Economic Research, number 30/2014, Dec, revised Dec 2014.
• Gautier M Krings & Jean-François Carpantier & Jean-Charles Delvenne, 2014, "Trade Integration and Trade Imbalances in the European Union: A Network Perspective," PLOS ONE, Public Library of Science, volume 9, issue 1, pages 1-14, January, DOI: 10.1371/journal.pone.0083448.
• Mishra, Sudhanshu K, 2014, "What happens if in the principal component analysis the Pearsonian is replaced by the Brownian coefficient of correlation?," MPRA Paper, University Library of Munich, Germany, number 56861, Jun.
• Mishra, SK, 2014, "A note on Poincaré recurrence in Anosov diffeomorphic transformation of discretized outline of some plant leaves," MPRA Paper, University Library of Munich, Germany, number 57594, Jul.
• Gawlik, Remigiusz & Gołębiowski, Kamil, 2014, "Incorporating Qualitative Indicators of Well - Being into Quantitative Economic Research," MPRA Paper, University Library of Munich, Germany, number 58587.
• Gawlik, Remigiusz, 2014, "Application of Artificial Intelligence Methods for Analysis of Material and Non-material Determinants of Functioning of Young Europeans in Times of Crisis in the Eurozone," MPRA Paper, University Library of Munich, Germany, number 62444, revised 2014.
• Alpaslan YARAR & Mustafa ONÜÇYILDIZ & Nuri PEKÇET?N, 2014, "Forecasting The Runoff Data Using Adaptive Neuro Fuzzy Inference Systems (ANFIS)," Proceedings of International Academic Conferences, International Institute of Social and Economic Sciences, number 0201599, Jun.
• Oswaldo García Salgado & Arturo Morales Castro, 2014, "Empresas exitosas y no exitosas que cotizan en la BMV del Sector Comercial: Una clasificación con Análisis Discriminante Múltiple, Modelos Logit y Redes Neuronales Artificiales," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, volume 4, issue 1, pages 33-62, enero-jun.
• Manuel Rodríguez & Carlos Piñeiro & Pablo De Llano, 2014, "Determinación del riesgo de fracaso financiero mediante la utilización de modelos paramétricos, de inteligencia artificial, y de información de auditoría," Estudios de Economia, University of Chile, Department of Economics, volume 41, issue 2 Year 20, pages 187-217, December.
• DIMITRIU, Mihail, 2014, "A Point Of View On The Logic Modelling Of The Financial Network," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", volume 18, issue 1, pages 8-19.
• DIMITRIU, Mihail, 2014, "Particularities Of Transfer Channel In The Financial Network Modeling," Journal of Financial and Monetary Economics, Centre of Financial and Monetary Research "Victor Slavescu", volume 1, issue 1, pages 239-243.

2013

• Cagdas Hakan ALADAG & Miruna MAZURENCU MARINESCU, 2013, "Tl/Euro And Leu/Euro Exchange Rates Forecasting With Artificial Neural Network," Journal of Social and Economic Statistics, Bucharest University of Economic Studies, volume 2, issue 2, pages 1-6, DECEMBER.
• Romano, Severino & Cozzi, Mario & Giglio, Paolo & Catullo, Giovanna, 2013, "Post-2013 EU Common Agricultural Policy: predictive models of land use change," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), volume 2, issue 2, pages 1-22, August, DOI: 10.22004/ag.econ.156472.
• Hardle, Wolfgang Karl & Prastyo, Dedy Dwi & Hafner, Christian, 2013, "Support Vector Machines with Evolutionary Feature Selection for Default Prediction," LIDAM Discussion Papers ISBA, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA), number 2013040, Jan.