Levenberg-Marquardt Algorithm for Karachi Stock Exchange Share Rates Forecasting
Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.
[1] S. M. Aqil Burney, Tahseen A. Jilani,. (2002). "Time Series forecasting
using artificial neural network methods for Karachi Stock Exchange". A
Project at Department of Computer Science, University of Karachi.
[2] S. M. Aqil Burney, "Measures of central tendency in News-MCB stock
exchange". Price index pp 12-31. Developed by Vital information
services (pvt) limited, Karachi. c/o Department of Computer Science,
University of Karachi.
[3] Adam Blum, (1992)."Neural Network in C++". John Wiley and Sons,
New York.
[4] C. Brooks, (1997). "Linear and non-linear (non-) forecastability of highfrequency
exchange rates". Journal of Forecasting, pp. 16:125-145.
[5] M. Caudill, and C. Butler. (1994)."Understanding neural network". MIT
Press.
[6] Y. Chauvin, and D. Rumelhart, (1995). "Backpropagation: theory,
architecture, and applications." Lawrence Erlbaum Association.
[7] Chung-Ming Kuan and Liu. Tung, (1995)."Forecasting exchange rates
using feedforward and recurrent neural networks." Journal of Applied
Econometrics, pp. 347-64.
[8] C. Lee Giles, Steve Lawrence and A. C. Tsoi, .(2001)."Time series
prediction using a recurrent neural network and grammatical inference".
Machine Learning, Vol. 44, Number › , July/August, pp. 161-183.
[9] C. Lee Giles, Steve Lawrence, A. C. Tsoi.(1997). "Rule inference for
financial prediction using recurrent neural networks". Proceedings of
IEEE/IAFE Conference on Computational Intelligence for Financial
Engineering (CIFEr), IEEE, Piscataway, NJ, , pp. 253-259.
[10] C. M. Bishop.(1995). "Neural networks for pattern recognition".
Clarendon Press. Oxford
[11] R. Dixon, and F. Bevan. (1994)."Neural network tutor." Advance
Technology Transfer Group.
[12] T. M. Hagan, H. B. Demuth, (1996)."Neural network design",
Brooks/Cole publishing company.
[13] R. Hecht-Nielsen, (1989). "Theory of the backpropagation neural
network". International Joint Conference on Neural Networks, IEEE,
New York, pp. 593-605.
[14] K. Hornik., M. Sunchcombe, and H. White. (1990). "Using multilayer
feedforward networks for universal approximation". Neural Networks 3,
pp. 551-60.
[15] Iebeling Kaastra and Milton S. Boyd. (1995). "Forecasting future trading
volume using neural networks." Journal of Future Markets, pp. 953-70.
[16] C. M. Kuan, and T. Liu. (1995). "Forecasting exchange rates using
feedforward and recurrent neural networks". Journal of Applied
Econometrics, pp.10: 347-364.
[17] Lars Liden, (2000) "Neural network simulation package". Department of
Cognitive and Natural Systems at Boston University
[18] Mir F. Atiya, Suzan M. El-Shoura, Samir I. Shaheen. "A comparison
between neural network forecasting techniques- case study: river flow
forecasting". IEEE Transactions on Neural Networks. Vol. 10, No. 2
March 1999
[19] Moody, J.(1994). "Prediction risk and architecture selection for neural networks". appears in, From Statistics to Neural Networks: Theory and
Pattern Recognition Application, NATO ASI Series, Springer-Verlag.
[20] Rich caruana, Steven Lawrence, C. Lee Giles. (2000)."Overfitting in
neural nets: backpropagation, conjugate gradient, and early stopping".
Neural Information Processing Systems, Denver, Colorado, November
pp. 28-30.
[21] B. D. Ripley, (1994)"Neural networks and related methods for
classification", Journal of the Royal Statistician Society, B 56(3),409-456.
[22] R. J. Schalkoff, (1997)."Artificial neural networks". McGraw-Hill
International Edition, computer science series,
[23] N. Schraudolph, Nicol, and T. J. Sejnowski, (1996)."Tempering
backpropagation networks: not all weights are created equal". Appear in
Advances in Neural Information Processing Systems 8, MIT Press,
Cambridge.
[24] W. Chu Chao-Hsien and Djohan Widjaja, (1994)."Neural network
system for forecasting method selection". Decision support systems
(August), pp. 13-24.
[25] T. Stephen Welstead, (1994). "Neural network and fuzzy logic
applications in C/C++". John Wiley and Sons, Inc. N.Y.
[1] S. M. Aqil Burney, Tahseen A. Jilani,. (2002). "Time Series forecasting
using artificial neural network methods for Karachi Stock Exchange". A
Project at Department of Computer Science, University of Karachi.
[2] S. M. Aqil Burney, "Measures of central tendency in News-MCB stock
exchange". Price index pp 12-31. Developed by Vital information
services (pvt) limited, Karachi. c/o Department of Computer Science,
University of Karachi.
[3] Adam Blum, (1992)."Neural Network in C++". John Wiley and Sons,
New York.
[4] C. Brooks, (1997). "Linear and non-linear (non-) forecastability of highfrequency
exchange rates". Journal of Forecasting, pp. 16:125-145.
[5] M. Caudill, and C. Butler. (1994)."Understanding neural network". MIT
Press.
[6] Y. Chauvin, and D. Rumelhart, (1995). "Backpropagation: theory,
architecture, and applications." Lawrence Erlbaum Association.
[7] Chung-Ming Kuan and Liu. Tung, (1995)."Forecasting exchange rates
using feedforward and recurrent neural networks." Journal of Applied
Econometrics, pp. 347-64.
[8] C. Lee Giles, Steve Lawrence and A. C. Tsoi, .(2001)."Time series
prediction using a recurrent neural network and grammatical inference".
Machine Learning, Vol. 44, Number › , July/August, pp. 161-183.
[9] C. Lee Giles, Steve Lawrence, A. C. Tsoi.(1997). "Rule inference for
financial prediction using recurrent neural networks". Proceedings of
IEEE/IAFE Conference on Computational Intelligence for Financial
Engineering (CIFEr), IEEE, Piscataway, NJ, , pp. 253-259.
[10] C. M. Bishop.(1995). "Neural networks for pattern recognition".
Clarendon Press. Oxford
[11] R. Dixon, and F. Bevan. (1994)."Neural network tutor." Advance
Technology Transfer Group.
[12] T. M. Hagan, H. B. Demuth, (1996)."Neural network design",
Brooks/Cole publishing company.
[13] R. Hecht-Nielsen, (1989). "Theory of the backpropagation neural
network". International Joint Conference on Neural Networks, IEEE,
New York, pp. 593-605.
[14] K. Hornik., M. Sunchcombe, and H. White. (1990). "Using multilayer
feedforward networks for universal approximation". Neural Networks 3,
pp. 551-60.
[15] Iebeling Kaastra and Milton S. Boyd. (1995). "Forecasting future trading
volume using neural networks." Journal of Future Markets, pp. 953-70.
[16] C. M. Kuan, and T. Liu. (1995). "Forecasting exchange rates using
feedforward and recurrent neural networks". Journal of Applied
Econometrics, pp.10: 347-364.
[17] Lars Liden, (2000) "Neural network simulation package". Department of
Cognitive and Natural Systems at Boston University
[18] Mir F. Atiya, Suzan M. El-Shoura, Samir I. Shaheen. "A comparison
between neural network forecasting techniques- case study: river flow
forecasting". IEEE Transactions on Neural Networks. Vol. 10, No. 2
March 1999
[19] Moody, J.(1994). "Prediction risk and architecture selection for neural networks". appears in, From Statistics to Neural Networks: Theory and
Pattern Recognition Application, NATO ASI Series, Springer-Verlag.
[20] Rich caruana, Steven Lawrence, C. Lee Giles. (2000)."Overfitting in
neural nets: backpropagation, conjugate gradient, and early stopping".
Neural Information Processing Systems, Denver, Colorado, November
pp. 28-30.
[21] B. D. Ripley, (1994)"Neural networks and related methods for
classification", Journal of the Royal Statistician Society, B 56(3),409-456.
[22] R. J. Schalkoff, (1997)."Artificial neural networks". McGraw-Hill
International Edition, computer science series,
[23] N. Schraudolph, Nicol, and T. J. Sejnowski, (1996)."Tempering
backpropagation networks: not all weights are created equal". Appear in
Advances in Neural Information Processing Systems 8, MIT Press,
Cambridge.
[24] W. Chu Chao-Hsien and Djohan Widjaja, (1994)."Neural network
system for forecasting method selection". Decision support systems
(August), pp. 13-24.
[25] T. Stephen Welstead, (1994). "Neural network and fuzzy logic
applications in C/C++". John Wiley and Sons, Inc. N.Y.
@article{"International Journal of Information, Control and Computer Sciences:57722", author = "Syed Muhammad Aqil Burney and Tahseen Ahmed Jilani and C. Ardil", title = "Levenberg-Marquardt Algorithm for Karachi Stock Exchange Share Rates Forecasting ", abstract = "Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.
", keywords = "Gradient descent method, jacobian matrix.Levenberg-Marquardt algorithm, quadratic error surfaces,", volume = "2", number = "4", pages = "1195-6", }
