Forecasting the Istanbul Stock Exchange National 100 Index Using an Artificial Neural Network
Many studies have shown that Artificial Neural
Networks (ANN) have been widely used for forecasting financial
markets, because of many financial and economic variables are nonlinear,
and an ANN can model flexible linear or non-linear
relationship among variables.
The purpose of the study was to employ an ANN models to
predict the direction of the Istanbul Stock Exchange National 100
Indices (ISE National-100).
As a result of this study, the model forecast the direction of the
ISE National-100 to an accuracy of 74, 51%.
[1] E. Y. Li,"Artificial Neural Networks and Their Business Applications,"
Information and Management, vol. 27, no. 5, pp. 303-313, 1994.
[2] F. Zadehi, "A Meta-analysis of Financial Applications of Neural
Networks," International Journal of Computational Intelligence and
Organization, vol. 1, no. 3, pp. 164-178, 1996.
[3] D. West, "Neural Network Credit Scoring Models," Computers and
Operational Research, vol. 27, no. 11/12, pp. 1131-1152, 2000.
[4] Y. Yoon, G. Swales Jr., and T.M. Margavio "A Comparison of
Discriminant Analysis versus Artificial Neural Networks," Journal of the
Operational Research Society, vol. 44, no. 1, pp. 51-60, January 1993.
[5] A. Kanas, "Non-linear forecasts of stock returns ," Journal of
Forecasting, vol. 22, no.4, pp. 299-315, July 2003.
[6] R.L.Wilson, and R. Sharda, "Bankruptcy Prediction Using Neural
Networks," Decision Support System, vol. 11, no.5, pp. 545-557, June
1994.
[7] R.S. Ludwig and M.J. Piovoso, "A Comparison of Machine-Learning
Classifiers For Selecting Money Managers," Intelligent Systems in
Accounting, Finance and Management, Chichester, vol. 13, no. 3, p.
151-164, July 2005.
[8] K. Kumar and S. Bhattacharya, "Artificial Neural Network vs Linear
Discriminant Analysis in Credit Ratings Forecast: A Comparative Study
of Prediction Performances," Review of Accounting and Finance, vol. 5,
no. 3, 217-227, 2006.
[9] P.R. Burell and B.O. Florin, "The Impact of Neural Networks in
Finance," Neural Computing and Applications, vol. 6, no. 4, pp. 193-
200, December 1997.
[10] S.V. Kartalopoulos, Understanding Neural Networks and Fuzzy Logic:
Basic Concepts and Applications, Wiley IEEE Press, New York, August
1995.
[11] R.Stein and V. Dhar, Intelligent Decision Support Methods: The Science
of Knowledge Work, Prentice Hall Business Publishing, N.J., 1996
[12] S. Ward and M. Sherald, The Neural Network Financial Wizards,
Technical Analysis of Stocks and Commodities, Reprinted, Technical
Analyses Inc., Seattle, Washington 1995.
[13] P.K.H. Pahua, D. Ming and W. Lin, "Neural Network with Genetically
Evolved Algorithms for Stocks Prediction," Asia-Pacific Journal of
Operational Research, vol. 18, pp. 103-107, 2001.
[14] A.I. Diler, "IMKB-100 Endeksinin Yön├╝n├╝n Yapay Sinira─ƒlar─▒ Hata
Geriye Yayma Yöntemiyle Tahmin Edilmesi," IMKB Dergisi, vol.7, pp.
25-26, 2003.
[15] A. Erdinç and M.H. Satman, "Stock Market Forecasting: Artificial
Neural Network and Linear Regression Comparison in An Emerging
Market," Journal of Financial Management and Analysis, vol.18, no. 2,
pp. 18-34, 2005.
[1] E. Y. Li,"Artificial Neural Networks and Their Business Applications,"
Information and Management, vol. 27, no. 5, pp. 303-313, 1994.
[2] F. Zadehi, "A Meta-analysis of Financial Applications of Neural
Networks," International Journal of Computational Intelligence and
Organization, vol. 1, no. 3, pp. 164-178, 1996.
[3] D. West, "Neural Network Credit Scoring Models," Computers and
Operational Research, vol. 27, no. 11/12, pp. 1131-1152, 2000.
[4] Y. Yoon, G. Swales Jr., and T.M. Margavio "A Comparison of
Discriminant Analysis versus Artificial Neural Networks," Journal of the
Operational Research Society, vol. 44, no. 1, pp. 51-60, January 1993.
[5] A. Kanas, "Non-linear forecasts of stock returns ," Journal of
Forecasting, vol. 22, no.4, pp. 299-315, July 2003.
[6] R.L.Wilson, and R. Sharda, "Bankruptcy Prediction Using Neural
Networks," Decision Support System, vol. 11, no.5, pp. 545-557, June
1994.
[7] R.S. Ludwig and M.J. Piovoso, "A Comparison of Machine-Learning
Classifiers For Selecting Money Managers," Intelligent Systems in
Accounting, Finance and Management, Chichester, vol. 13, no. 3, p.
151-164, July 2005.
[8] K. Kumar and S. Bhattacharya, "Artificial Neural Network vs Linear
Discriminant Analysis in Credit Ratings Forecast: A Comparative Study
of Prediction Performances," Review of Accounting and Finance, vol. 5,
no. 3, 217-227, 2006.
[9] P.R. Burell and B.O. Florin, "The Impact of Neural Networks in
Finance," Neural Computing and Applications, vol. 6, no. 4, pp. 193-
200, December 1997.
[10] S.V. Kartalopoulos, Understanding Neural Networks and Fuzzy Logic:
Basic Concepts and Applications, Wiley IEEE Press, New York, August
1995.
[11] R.Stein and V. Dhar, Intelligent Decision Support Methods: The Science
of Knowledge Work, Prentice Hall Business Publishing, N.J., 1996
[12] S. Ward and M. Sherald, The Neural Network Financial Wizards,
Technical Analysis of Stocks and Commodities, Reprinted, Technical
Analyses Inc., Seattle, Washington 1995.
[13] P.K.H. Pahua, D. Ming and W. Lin, "Neural Network with Genetically
Evolved Algorithms for Stocks Prediction," Asia-Pacific Journal of
Operational Research, vol. 18, pp. 103-107, 2001.
[14] A.I. Diler, "IMKB-100 Endeksinin Yön├╝n├╝n Yapay Sinira─ƒlar─▒ Hata
Geriye Yayma Yöntemiyle Tahmin Edilmesi," IMKB Dergisi, vol.7, pp.
25-26, 2003.
[15] A. Erdinç and M.H. Satman, "Stock Market Forecasting: Artificial
Neural Network and Linear Regression Comparison in An Emerging
Market," Journal of Financial Management and Analysis, vol.18, no. 2,
pp. 18-34, 2005.
@article{"International Journal of Business, Human and Social Sciences:60425", author = "Birol Yildiz and Abdullah Yalama and Metin Coskun", title = "Forecasting the Istanbul Stock Exchange National 100 Index Using an Artificial Neural Network", abstract = "Many studies have shown that Artificial Neural
Networks (ANN) have been widely used for forecasting financial
markets, because of many financial and economic variables are nonlinear,
and an ANN can model flexible linear or non-linear
relationship among variables.
The purpose of the study was to employ an ANN models to
predict the direction of the Istanbul Stock Exchange National 100
Indices (ISE National-100).
As a result of this study, the model forecast the direction of the
ISE National-100 to an accuracy of 74, 51%.", keywords = "Artificial Neural Networks, Istanbul StockExchange, Non-linear Modeling.", volume = "2", number = "10", pages = "1137-4", }
