A heuristic forecasting model for stock decision making.

D. Zhang; Q. Jiang; X. Li

Mathware and Soft Computing (2005)

  • Volume: 12, Issue: 1, page 33-39
  • ISSN: 1134-5632

Abstract

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This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting model was found capable of consistently outperforming this benchmark strategy.

How to cite

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Zhang, D., Jiang, Q., and Li, X.. "A heuristic forecasting model for stock decision making.." Mathware and Soft Computing 12.1 (2005): 33-39. <http://eudml.org/doc/40855>.

@article{Zhang2005,
abstract = {This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting model was found capable of consistently outperforming this benchmark strategy.},
author = {Zhang, D., Jiang, Q., Li, X.},
journal = {Mathware and Soft Computing},
keywords = {Redes neuronales; Predicción; Heurística; Procesos de decisión; Bolsa de valores; learning capability; benchmark strategy},
language = {eng},
number = {1},
pages = {33-39},
title = {A heuristic forecasting model for stock decision making.},
url = {http://eudml.org/doc/40855},
volume = {12},
year = {2005},
}

TY - JOUR
AU - Zhang, D.
AU - Jiang, Q.
AU - Li, X.
TI - A heuristic forecasting model for stock decision making.
JO - Mathware and Soft Computing
PY - 2005
VL - 12
IS - 1
SP - 33
EP - 39
AB - This paper describes a heuristic forecasting model based on neural networks for stock decision-making. Some heuristic strategies are presented for enhancing the learning capability of neural networks and obtaining better trading performance. The China Shanghai Composite Index is used as case study. The forecasting model can forecast the buying and selling signs according to the result of neural network prediction. Results are compared with a benchmark buy-and-hold strategy. The forecasting model was found capable of consistently outperforming this benchmark strategy.
LA - eng
KW - Redes neuronales; Predicción; Heurística; Procesos de decisión; Bolsa de valores; learning capability; benchmark strategy
UR - http://eudml.org/doc/40855
ER -

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