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A neural network approach to mutual fund net asset value forecasting

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Cited by:

  1. Sen Cheong Kon & Lindsay W. Turner, 2005. "Neural Network Forecasting of Tourism Demand," Tourism Economics, , vol. 11(3), pages 301-328, September.
  2. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
  3. Victor DeMiguel & Javier Gil-Bazo & Francisco J. Nogales & André A. P. Santos, 2021. "Can Machine Learning Help to Select Portfolios of Mutual Funds?," Working Papers 1245, Barcelona School of Economics.
  4. Indro, D. C. & Jiang, C. X. & Patuwo, B. E. & Zhang, G. P., 1999. "Predicting mutual fund performance using artificial neural networks," Omega, Elsevier, vol. 27(3), pages 373-380, June.
  5. Mishra, Sasmita & Padhy, Sudarsan, 2019. "An efficient portfolio construction model using stock price predicted by support vector regression," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  6. Hwarng, H. Brian, 2001. "Insights into neural-network forecasting of time series corresponding to ARMA(p,q) structures," Omega, Elsevier, vol. 29(3), pages 273-289, June.
  7. Adam Fadlalla & Chien-Hua Lin, 2001. "An Analysis of the Applications of Neural Networks in Finance," Interfaces, INFORMS, vol. 31(4), pages 112-122, August.
  8. Azadeh, A. & Saberi, M. & Seraj, O., 2010. "An integrated fuzzy regression algorithm for energy consumption estimation with non-stationary data: A case study of Iran," Energy, Elsevier, vol. 35(6), pages 2351-2366.
  9. Curry, B. & Morgan, P., 1997. "Neural networks: a need for caution," Omega, Elsevier, vol. 25(1), pages 123-133, February.
  10. Gruca, TS & Klemz, BR, 1998. "Using Neural Networks to Identify Competitive Market Structures from Aggregate Market Response Data," Omega, Elsevier, vol. 26(1), pages 49-62, February.
  11. Michael Dietrich, 2006. "Neural networks and the evolution of firms and industries: An application to UK SIC34 and SIC72," Working Papers 2006007, The University of Sheffield, Department of Economics, revised May 2006.
  12. Chen Jo-Hui & Diaz John Francis T., 2021. "Application of grey relational analysis and artificial neural networks on currency exchange-traded notes (ETNs)," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(2), pages 1-17, April.
  13. Gupta, V. K. & Chen, J. G. & Murtaza, M. B., 1997. "A learning vector quantization neural network model for the classification of industrial construction projects," Omega, Elsevier, vol. 25(6), pages 715-727, December.
  14. 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.
  15. Nghia Chu & Binh Dao & Nga Pham & Huy Nguyen & Hien Tran, 2022. "Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques," Papers 2209.09649, arXiv.org, revised Jul 2023.
  16. DeMiguel, Victor & Gil-Bazo, Javier & Nogales, Francisco J. & Santos, André A.P., 2023. "Machine learning and fund characteristics help to select mutual funds with positive alpha," Journal of Financial Economics, Elsevier, vol. 150(3).
  17. Yasemin Deniz Akarım, 2013. "A Comparison of Linear and Nonlinear Models in Forecasting Market Risk: The Evidence from Turkish Derivative Exchange," Journal of Economics and Behavioral Studies, AMH International, vol. 5(3), pages 164-172.
  18. Onsel Sahin, Sule & Ulengin, Fusun & Ulengin, Burc, 2004. "Using neural networks and cognitive mapping in scenario analysis: The case of Turkey's inflation dynamics," European Journal of Operational Research, Elsevier, vol. 158(1), pages 124-145, October.
  19. Zhao, Ze & Wang, Jianzhou & Zhao, Jing & Su, Zhongyue, 2012. "Using a Grey model optimized by Differential Evolution algorithm to forecast the per capita annual net income of rural households in China," Omega, Elsevier, vol. 40(5), pages 525-532.
  20. Laura Fabregat-Aibar & Maria-Teresa Sorrosal-Forradellas & Glòria Barberà-Mariné & Antonio Terceño, 2021. "Can Artificial Neural Networks Predict the Survival Capacity of Mutual Funds? Evidence from Spain," Mathematics, MDPI, vol. 9(6), pages 1-10, March.
  21. Shaogao Lv & Yongchao Hou & Hongwei Zhou, 2019. "Financial Market Directional Forecasting With Stacked Denoising Autoencoder," Papers 1912.00712, arXiv.org.
  22. Klein, B. D. & Rossin, D. F., 1999. "Data quality in neural network models: effect of error rate and magnitude of error on predictive accuracy," Omega, Elsevier, vol. 27(5), pages 569-582, October.
  23. Chiang, Wen-Chyuan & Russell, Robert A. & Urban, Timothy L., 2011. "Forecasting ridership for a metropolitan transit authority," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 696-705, August.
  24. Mishra, Sasmita & Padhy, Sudarsan & Mishra, Satya Narayan & Misra, Satya Narayan, 2021. "A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
  25. E. Hurwitz & T. Marwala, 2012. "Common Mistakes when Applying Computational Intelligence and Machine Learning to Stock Market modelling," Papers 1208.4429, arXiv.org.
  26. Shouhong, Wang, 1998. "An Insight Into the Standard Back-propagation Neural Network Model for Regression Analysis," Omega, Elsevier, vol. 26(1), pages 133-140, February.
  27. Azadeh, A. & Ghaderi, S.F. & Anvari, M. & Saberi, M., 2007. "Performance assessment of electric power generations using an adaptive neural network algorithm," Energy Policy, Elsevier, vol. 35(6), pages 3155-3166, June.
  28. Zhang, Guoqiang & Eddy Patuwo, B. & Y. Hu, Michael, 1998. "Forecasting with artificial neural networks:: The state of the art," International Journal of Forecasting, Elsevier, vol. 14(1), pages 35-62, March.
  29. Tay, Francis E. H. & Cao, Lijuan, 2001. "Application of support vector machines in financial time series forecasting," Omega, Elsevier, vol. 29(4), pages 309-317, August.
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