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Genetic Algorithms for Estimation Problems with Multiple Optima, Nondifferentiability, and Other Irregular Features

Citations

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Cited by:

  1. Odeh, Oluwarotimi O. & Featherstone, Allen M. & Sanjoy, Das, 2006. "Predicting Credit Default in an Agricultural Bank: Methods and Issues," 2006 Annual Meeting, February 5-8, 2006, Orlando, Florida 35359, Southern Agricultural Economics Association.
  2. Massimiliano Kaucic, 2009. "Predicting EU Energy Industry Excess Returns on EU Market Index via a Constrained Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 34(2), pages 173-193, September.
  3. Mariano Matilla-Garcia, 2006. "Are trading rules based on genetic algorithms profitable?," Applied Economics Letters, Taylor & Francis Journals, vol. 13(2), pages 123-126.
  4. Das, Tirthatanmoy & Polachek, Solomon, 2017. "Micro Foundations of Earnings Differences," IZA Discussion Papers 10922, Institute of Labor Economics (IZA).
  5. Swait, Joffre, 2023. "Distribution-free estimation of individual parameter logit (IPL) models using combined evolutionary and optimization algorithms," Journal of choice modelling, Elsevier, vol. 47(C).
  6. William A. Barnett & Ikuyasu Usui, 2007. "The Theoretical Regularity Properties of the Normalized Quadratic Consumer Demand Model," International Symposia in Economic Theory and Econometrics, in: Functional Structure Inference, pages 107-127, Emerald Group Publishing Limited.
  7. Andriosopoulos, Kostas & Nomikos, Nikos, 2014. "Performance replication of the Spot Energy Index with optimal equity portfolio selection: Evidence from the UK, US and Brazilian markets," European Journal of Operational Research, Elsevier, vol. 234(2), pages 571-582.
  8. Paul D. McNelis & G.C. Lim, 1998. "Parameterizing Currency Risk in the EMS: The Irish Pound and Spanish Peseta against the German Mark," International Finance 9805001, University Library of Munich, Germany.
  9. Kapetanios, George, 2007. "Variable selection in regression models using nonstandard optimisation of information criteria," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 4-15, September.
  10. A. Sanchez & Diego Martinez, 2011. "Optimization in Non-Standard Problems. An Application to the Provision of Public Inputs," Computational Economics, Springer;Society for Computational Economics, vol. 37(1), pages 13-38, January.
  11. Winker, Peter & Gilli, Manfred, 2004. "Applications of optimization heuristics to estimation and modelling problems," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 211-223, September.
  12. Cristiana Benedetti Fasil, 2009. "Product and Process Innovation in a Growth Model of Firm Selection," Economics Working Papers ECO2009/30, European University Institute.
  13. Juretig, Francisco, 2015. "MLGA: A SAS Macro to Compute Maximum Likelihood Estimators via Genetic Algorithms," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 66(c02).
  14. Mika Meitz & Daniel Preve & Pentti Saikkonen, 2023. "A mixture autoregressive model based on Student’s t–distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(2), pages 499-515, January.
  15. Savin Ivan, 2013. "A Comparative Study of the Lasso-type and Heuristic Model Selection Methods," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 233(4), pages 526-549, August.
  16. Pereira, Robert, 1999. "Forecasting Ability But No Profitability: An Empirical Evaluation of Genetic Algorithm-optimised Technical Trading Rules," MPRA Paper 9055, University Library of Munich, Germany.
  17. Robert Pereira, 2000. "Genetic Algorithm Optimisation for Finance and Investment," Working Papers 2000.02, School of Economics, La Trobe University.
  18. Poschke, Markus, 2009. "Employment protection, firm selection, and growth," Journal of Monetary Economics, Elsevier, vol. 56(8), pages 1074-1085, November.
  19. Alicia Gazely & Jane Binner & Graham Kendall, 2004. "Co-evolution vs. Neural Networks; An Evaluation of UK Risky Money," Computing in Economics and Finance 2004 258, Society for Computational Economics.
  20. J. Coulon & Y. Malevergne, 2011. "Heterogeneous expectations and long-range correlation of the volatility of asset returns," Quantitative Finance, Taylor & Francis Journals, vol. 11(9), pages 1329-1356, November.
  21. Khurshid M. Kiani, 2007. "Asymmetric Business Cycle Fluctuations and Contagion Effects in G7 Countries," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 6(3), pages 237-253, December.
  22. Rä‚Zvan Popa, 2020. "Improving Earnings Predictions With Neural Network Models," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 26, pages 77-96, December.
  23. Peter Winker & Dietmar Maringer, 2009. "The convergence of estimators based on heuristics: theory and application to a GARCH model," Computational Statistics, Springer, vol. 24(3), pages 533-550, August.
  24. Antanas Žilinskas & Julius Žilinskas, 2013. "A hybrid global optimization algorithm for non-linear least squares regression," Journal of Global Optimization, Springer, vol. 56(2), pages 265-277, June.
  25. William L. Goffe, "undated". "A Toolkit for Optimizing Functions in Economics," Computing in Economics and Finance 1997 65, Society for Computational Economics.
  26. Rajkumar Venkatesan & Trichy V. Krishnan & V. Kumar, 2004. "Evolutionary Estimation of Macro-Level Diffusion Models Using Genetic Algorithms: An Alternative to Nonlinear Least Squares," Marketing Science, INFORMS, vol. 23(3), pages 451-464, August.
  27. Tonsor, Glynn T. & Kastens, Terry L., 2006. "How Much Do Starting Values Really Matter? An Empirical Comparison of Genetic Algorithm and Traditional Approaches," 2006 Annual meeting, July 23-26, Long Beach, CA 21252, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  28. Solomon W. Polachek, 2017. "Heterogeneity in the Labor Market: Ability and Information Acquisition," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(3), pages 377-390, June.
  29. Ivelina Pavlova & A. M. Parhizgari, 2011. "In search of momentum profits: are they illusory?," Applied Financial Economics, Taylor & Francis Journals, vol. 21(21), pages 1617-1639.
  30. Liu, Yu-Hsin, 2011. "Incorporating scatter search and threshold accepting in finding maximum likelihood estimates for the multinomial probit model," European Journal of Operational Research, Elsevier, vol. 211(1), pages 130-138, May.
  31. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
  32. Zilinskas, Julius & Bogle, Ian David Lockhart, 2006. "Balanced random interval arithmetic in market model estimation," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1367-1378, December.
  33. Randall S. Sexton & Naheel A. Sikander, 2001. "Data mining using a genetic algorithm‐trained neural network," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(4), pages 201-210, December.
  34. Yiannis Kamarianakis & Anastasios Xepapadeas, 2006. "Controlling the risky fraction process with an ergodic criterion," Working Papers 0710, University of Crete, Department of Economics.
  35. Parente, Paulo M.D.C. & Smith, Richard J., 2011. "Gel Methods For Nonsmooth Moment Indicators," Econometric Theory, Cambridge University Press, vol. 27(1), pages 74-113, February.
  36. Beenstock, Michael & Szpiro, George, 2002. "Specification search in nonlinear time-series models using the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 26(5), pages 811-835, May.
  37. Jatinder N. D. Gupta & Randall S. Sexton & Enar A. Tunc, 2000. "Selecting Scheduling Heuristics Using Neural Networks," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 150-162, May.
  38. Stéphanie Portet & Anotida Madzvamuse & Andy Chung & Rudolf E Leube & Reinhard Windoffer, 2015. "Keratin Dynamics: Modeling the Interplay between Turnover and Transport," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-29, March.
  39. Max Jerrell, 2000. "Applications Of Public Global Optimization Software To Difficult Econometric Functions," Computing in Economics and Finance 2000 161, Society for Computational Economics.
  40. Mayer, Walter J. & Dorsey, Robert E., 1998. "Maximum score estimation of disequilibrium models and the role of anticipatory price-setting," Journal of Econometrics, Elsevier, vol. 87(1), pages 1-24, August.
  41. Adrián Fernández-P�rez & Fernando Fernández-Rodr�guez & Simón Sosvilla-Rivero, 2012. "Detecting trends in the foreign exchange markets," Applied Economics Letters, Taylor & Francis Journals, vol. 19(5), pages 493-503, March.
  42. Shu-Heng Chen & Yi-Lin Hsieh, 2011. "Reinforcement Learning in Experimental Asset Markets," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 37(1), pages 109-133.
  43. Makram El-Shagi, 2011. "An evolutionary algorithm for the estimation of threshold vector error correction models," International Economics and Economic Policy, Springer, vol. 8(4), pages 341-362, December.
  44. Savi Virolainen, 2020. "Structural Gaussian mixture vector autoregressive model with application to the asymmetric effects of monetary policy shocks," Papers 2007.04713, arXiv.org, revised Oct 2022.
  45. Montagno, Ray & Sexton, Randall S. & Smith, Brien N., 2002. "Using neural networks for identifying organizational improvement strategies," European Journal of Operational Research, Elsevier, vol. 142(2), pages 382-395, October.
  46. Max E. Jerrell, "undated". "Automatic Differentiation and Interval Arithmetic for Estimation of Disequilibrium Models," Computing in Economics and Finance 1996 _028, Society for Computational Economics.
  47. Duffy, John & McNelis, Paul D., 2001. "Approximating and simulating the stochastic growth model: Parameterized expectations, neural networks, and the genetic algorithm," Journal of Economic Dynamics and Control, Elsevier, vol. 25(9), pages 1273-1303, September.
  48. Hansen, Bruce E. & Seo, Byeongseon, 2002. "Testing for two-regime threshold cointegration in vector error-correction models," Journal of Econometrics, Elsevier, vol. 110(2), pages 293-318, October.
  49. Adrián Fernández-P�rez & Fernando Fernández-Rodr�guez & Simón Sosvilla-Rivero, 2012. "Exploiting trends in the foreign exchange markets," Applied Economics Letters, Taylor & Francis Journals, vol. 19(6), pages 591-597, April.
  50. Markus Poschke, 2010. "The Regulation of Entry and Aggregate Productivity," Economic Journal, Royal Economic Society, vol. 120(549), pages 1175-1200, December.
  51. Sexton, Randall S. & McMurtrey, Shannon & Cleavenger, Dean, 2006. "Knowledge discovery using a neural network simultaneous optimization algorithm on a real world classification problem," European Journal of Operational Research, Elsevier, vol. 168(3), pages 1009-1018, February.
  52. Eklund, Jana & Kapetanios, George, 2008. "A review of forecasting techniques for large datasets," National Institute Economic Review, National Institute of Economic and Social Research, vol. 203, pages 109-115, January.
  53. Khurshid M. Kiani, 2009. "Asymmetries in Macroeconomic Time Series in Eleven Asian Economies," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(1), pages 37-54, April.
  54. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, vol. 51(2), pages 245-271, February.
  55. Arne Risa Hole & Hong Il Yoo, 2017. "The use of heuristic optimization algorithms to facilitate maximum simulated likelihood estimation of random parameter logit models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(5), pages 997-1013, November.
  56. Mariano Matilla-Garcia, 2005. "A note on cointegrated relationships estimated with genetic algorithms," Applied Economics Letters, Taylor & Francis Journals, vol. 12(4), pages 235-238.
  57. Yasuhiko Nakamura, 2008. "On Forecasting Recessions via Neural Nets," Economics Bulletin, AccessEcon, vol. 3(13), pages 1-15.
  58. Christopher R. Knittel & Konstantinos Metaxoglou, 2008. "Estimation of Random Coefficient Demand Models: Challenges, Difficulties and Warnings," NBER Working Papers 14080, National Bureau of Economic Research, Inc.
  59. Petrella, Ivan & Santoro, Emiliano & Simonsen, Lasse de la Porte, 2018. "Time-varying Price Flexibility and Inflation Dynamics," CEPR Discussion Papers 13027, C.E.P.R. Discussion Papers.
  60. Chi, Li-Chiu & Tang, Tseng-Chung, 2007. "Impact of reorganization announcements on distressed-stock returns," Economic Modelling, Elsevier, vol. 24(5), pages 749-767, September.
  61. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37603, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
  62. Sexton, Randall S. & Dorsey, Robert E. & Johnson, John D., 1999. "Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing," European Journal of Operational Research, Elsevier, vol. 114(3), pages 589-601, May.
  63. Kelvin Balcombe, 2005. "Model Selection Using Information Criteria and Genetic Algorithms," Computational Economics, Springer;Society for Computational Economics, vol. 25(3), pages 207-228, June.
  64. repec:wrk:wrkemf:28 is not listed on IDEAS
  65. Gupta, Jatinder N. D. & Sexton, Randall S., 1999. "Comparing backpropagation with a genetic algorithm for neural network training," Omega, Elsevier, vol. 27(6), pages 679-684, December.
  66. Ostermark, Ralf, 2004. "A multipurpose parallel genetic hybrid algorithm for non-linear non-convex programming problems," European Journal of Operational Research, Elsevier, vol. 152(1), pages 195-214, January.
  67. Tucci, Marco P., 2002. "A note on global optimization in adaptive control, econometrics and macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 26(9-10), pages 1739-1764, August.
  68. Manfred Gilli & Peter Winker, 2008. "Review of Heuristic Optimization Methods in Econometrics," Working Papers 001, COMISEF.
  69. Solomon W. Polachek & Tirthatanmoy Das & Rewat Thamma-Apiroam, 2015. "Micro- and Macroeconomic Implications of Heterogeneity in the Production of Human Capital," Journal of Political Economy, University of Chicago Press, vol. 123(6), pages 1410-1455.
  70. Eklund, Jana & Kapetanios, George, 2008. "A review of forecasting techniques for large datasets," National Institute Economic Review, Cambridge University Press, vol. 203, pages 109-115, January.
  71. Adrian Costea & Iulian Nastac, 2005. "Assessing the predictive performance of artifIcial neural network‐based classifiers based on different data preprocessing methods, distributions and training mechanisms," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(4), pages 217-250, December.
  72. Sarah Stolting, 2009. "International Trade and Growth: The Impact of Seletion and Imitation," Economics Working Papers ECO2009/21, European University Institute.
  73. Skouras, Spyros, 2003. "An algorithm for computing estimators that optimize step functions," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 349-361, March.
  74. M. Bierlaire & M. Thémans & N. Zufferey, 2010. "A Heuristic for Nonlinear Global Optimization," INFORMS Journal on Computing, INFORMS, vol. 22(1), pages 59-70, February.
  75. Henri Karttunen, 2020. "An autoregressive model based on the generalized hyperbolic distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 787-816, September.
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