The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm: a case study in romantic decision support
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Cites
Learning representations by back-propagating errors
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986) · Nature · doi:10.1038/323533a0 · Cited by 31,892
Multilayer feedforward networks are universal approximators
Hornik, K., Stinchcombe, M., & White, H. (1989) · Neural Networks · doi:10.1016/0893-6080(89)90020-8 · Cited by 21,728
(1973) · CERN Document Server (European Organization for Nuclear Research) · Cited by 12,895
Elman, J. L. (1990) · Cognitive Science · doi:10.1207/s15516709cog1402_1 · Cited by 11,212
Multilayer feedforward networks are universal approximators
HornikK., StinchcombeM., & WhiteH. (1989) · Neural Networks · doi:10.5555/70405.70408 · Cited by 9,081
Ensemble methods in machine learning
Dietterich, T. G. (2000) · Lecture Notes in Computer Science · doi:10.1007/3-540-45014-9_1 · Cited by 8,408
FAMA, E. F. (1991) · The Journal of Finance · doi:10.1111/j.1540-6261.1991.tb04636.x · Cited by 5,350
Forecasting with artificial neural networks:
Zhang, G., Eddy Patuwo, B., & Y. Hu, M. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(97)00044-7 · Cited by 4,229
A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets
Hong, H., & Stein, J. C. (1999) · The Journal of Finance · doi:10.1111/0022-1082.00184 · Cited by 4,001
Pattern classification and scene analysis
Chien, Y. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100577 · Cited by 3,398
Cited by
A data-driven approach to predict the success of bank telemarketing
Moro, S., Cortez, P., & Rita, P. (2014) · Decision Support Systems · doi:10.1016/j.dss.2014.03.001 · Cited by 868
Financial time series forecasting using independent component analysis and support vector regression
Lu, C.-J., Lee, T.-S., & Chiu, C.-C. (2009) · Decision Support Systems · doi:10.1016/j.dss.2009.02.001 · Cited by 537
A Bayesian regularized artificial neural network for stock market forecasting
Ticknor, J. L. (2013) · Expert Systems with Applications · doi:10.1016/j.eswa.2013.04.013 · Cited by 517
Series in Machine Perception and Artificial Intelligence
(2012) · Series in machine perception and artificial intelligence · doi:10.1142/smpai · Cited by 365
Artificial neural networks in business: Two decades of research
Tkáč, M., & Verner, R. (2016) · Applied Soft Computing · doi:10.1016/j.asoc.2015.09.040 · Cited by 340
Metadata
- Authors
- Leigh, W., Purvis, R., & Ragusa, J. M.
- Venue
- Decision Support Systems
- Publisher
- Elsevier BV
- Published
- 2002-03
- Volume
- 32
- Issue
- 4
- Pages
- 361-377
- ISSN
- 0167-9236 (ISSN-L)
- OpenAlex
- W2001751530
- Cited by
- 277
- References
- 53
- FWCI
- 8.66
- Type
- journal article
- Language
- en
- Open access
- green
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- Leigh, W., Purvis, R., & Ragusa, J. M. (2002). Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm: a case study in romantic decision support. Decision Support Systems. https://doi.org/10.1016/s0167-9236(01)00121-x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.