A COMPARATIVE STUDY OF NEURAL NETWORKS' CAPABILITIES USING INDICATORS OF TECHNICAL ANALYSIS FOR FORECASTING OF STOCK'S PRICE

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

MOTEVASELI MAHMOUD; TALEB KASHEFI B.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: NAMEH-YE-MOFID Year:2006 | Volume:12 | Issue:1 (54 ECONOMICS) Page(s): 57-82

Download Full-Text

Persian Verion

View:

1,702

Download:

Cites:

Information Journal Paper

Title

A COMPARATIVE STUDY OF NEURAL NETWORKS' CAPABILITIES USING INDICATORS OF TECHNICAL ANALYSIS FOR FORECASTING OF STOCK'S PRICE

Author(s)

MOTEVASELI MAHMOUD | TALEB KASHEFI B. | Issue Writer Certificate

Keywords

STOCK'S PRICE FORECASTINGQ2

TECHNICAL ANALYSISQ2

NEURAL NETWORKSQ3

TIME-SERIES MODELSQ3

APPLICATIONSQ3

Abstract

The most important issue for active investors in capital market is forecasting the stock's price. The main goal of this research is to study the application of stock's price anticipation by using indicators of TECHNICAL ANALYSIS based on NEURAL NETWORKS and the comparison of this method and NEURAL NETWORKS which uses stock's price and ARIMA models. In this research stock's price of the next 10 days of 40 active companies will be anticipated in Tehran stock exchange by using three different methods. In the first method, the stock's price will be forecasted by applying SINGLE LAYER FEED FORWARD NEURAL NETWORKS. Using Levenberg-Marquardt learning algorithm and the performance criteria of MSE with admission of market value.In the next step, beside the entry of market value, 5, 10 and 20 days of moving average and 12 days of RSI and also ROC were introduced as new entries to the network and forecasting was accomplished. The Stock's prices were also anticipated for all companies using ARIMA models. By applying analysis of variance, three different anticipating models were compared. Since price anticipation for thirty companies by ARIMA models have presented better and more meaningful results rather than NEURAL NETWORKS model. Therefore, we can claim that the linear models of ARIMA are more capable of explaining and analyzing the complexities of time series of stock's price than the nonlinear models of NEURAL NETWORKS. Therefore, they are recommended to be used for anticipation of stock's price.

Cites

References

Cite

APA: Copy

MOTEVASELI, MAHMOUD, & TALEB KASHEFI, B.. (2006). A COMPARATIVE STUDY OF NEURAL NETWORKS' CAPABILITIES USING INDICATORS OF TECHNICAL ANALYSIS FOR FORECASTING OF STOCK'S PRICE. NAMEH-YE-MOFID, 12(1 (54 ECONOMICS)), 57-82. SID. https://sid.ir/paper/3729/en

Vancouver: Copy

MOTEVASELI MAHMOUD, TALEB KASHEFI B.. A COMPARATIVE STUDY OF NEURAL NETWORKS' CAPABILITIES USING INDICATORS OF TECHNICAL ANALYSIS FOR FORECASTING OF STOCK'S PRICE. NAMEH-YE-MOFID[Internet]. 2006;12(1 (54 ECONOMICS)):57-82. Available from: https://sid.ir/paper/3729/en

IEEE: Copy

MAHMOUD MOTEVASELI, and B. TALEB KASHEFI, “A COMPARATIVE STUDY OF NEURAL NETWORKS' CAPABILITIES USING INDICATORS OF TECHNICAL ANALYSIS FOR FORECASTING OF STOCK'S PRICE,” NAMEH-YE-MOFID, vol. 12, no. 1 (54 ECONOMICS), pp. 57–82, 2006, [Online]. Available: https://sid.ir/paper/3729/en

Related Journal Papers