The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Using artificial neural network models in stock market index prediction
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Citations
Cites
Neural Networks: A Comprehensive Foundation
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Bollerslev, T. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90063-1 · Cited by 22,254
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Conditional Heteroskedasticity in Asset Returns: A New Approach
Nelson, D. B. (1991) · Econometrica · doi:10.2307/2938260 · Cited by 10,236
Introduction to Machine Learning
(2019) · Series in Machine Perception and Artificial Intelligence · doi:10.1142/9789811201967_0001 · Cited by 1,639
25 years of time series forecasting
De Gooijer, J. G., & Hyndman, R. J. (2006) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2006.01.001 · Cited by 1,587
Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review
Ravi Kumar, P., & Ravi, V. (2007) · European Journal of Operational Research · doi:10.1016/j.ejor.2006.08.043 · Cited by 1,074
Surveying stock market forecasting techniques – Part II: Soft computing methods
Atsalakis, G. S., & Valavanis, K. P. (2009) · Expert Systems with Applications · doi:10.1016/j.eswa.2008.07.006 · Cited by 839
Neural and adaptive systems : fundamentals through simulations
Príncipe, J. C., Euliano, N. R., & Lefebvre, W. (2000) · CERN Document Server (European Organization for Nuclear Research) · Cited by 818
An artificial neural network (p,d,q) model for timeseries forecasting
Khashei, M., & Bijari, M. (2010) · Expert Systems with Applications · doi:10.1016/j.eswa.2009.05.044 · Cited by 785
Cited by
Chong, E., Han, C., & Park, F. C. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.04.030 · Cited by 834
Financial time series forecasting model based on CEEMDAN and LSTM
Cao, J., Li, Z., & Li, J. (2019) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2018.11.061 · Cited by 710
A systematic review of fundamental and technical analysis of stock market predictions
Nti, I. K., Adekoya, A. F., & Weyori, B. A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09754-z · Cited by 547
Sezer, O. B., & Ozbayoglu, A. M. (2018) · Applied Soft Computing · doi:10.1016/j.asoc.2018.04.024 · Cited by 432
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
- Guresen, E., Kayakutlu, G., & Daim, T. U.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2011-08
- Volume
- 38
- Issue
- 8
- Pages
- 10389-10397
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W2059852492
- Cited by
- 786
- References
- 38
- FWCI
- 29.91
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Guresen, E., Kayakutlu, G., & Daim, T. U. (2011). Using artificial neural network models in stock market index prediction. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2011.02.068
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.
