An Artificial Neural Network for Data Forecasting Purposes

Considering the fact that markets are generally influenced by different external factors, the stock market prediction is one of the most difficult tasks of time series analysis. The research reported in this paper aims to investigate the potential of artificial neural networks (ANN) in solving the f...

Full description

Bibliographic Details
Main Authors: Catalina Lucia COCIANU, Hakob GRIGORYAN
Format: Article
Language:English
Published: Inforec Association 2015-01-01
Series:Informatică economică
Subjects:
Online Access:http://revistaie.ase.ro/content/74/04%20-%20cocianu,%20grigoryan.pdf
_version_ 1819263164511944704
author Catalina Lucia COCIANU
Hakob GRIGORYAN
author_facet Catalina Lucia COCIANU
Hakob GRIGORYAN
author_sort Catalina Lucia COCIANU
collection DOAJ
description Considering the fact that markets are generally influenced by different external factors, the stock market prediction is one of the most difficult tasks of time series analysis. The research reported in this paper aims to investigate the potential of artificial neural networks (ANN) in solving the forecast task in the most general case, when the time series are non-stationary. We used a feed-forward neural architecture: the nonlinear autoregressive network with exogenous inputs. The network training function used to update the weight and bias parameters corresponds to gradient descent with adaptive learning rate variant of the backpropagation algorithm. The results obtained using this technique are compared with the ones resulted from some ARIMA models. We used the mean square error (MSE) measure to evaluate the performances of these two models. The comparative analysis leads to the conclusion that the proposed model can be successfully applied to forecast the financial data.
first_indexed 2024-12-23T20:09:14Z
format Article
id doaj.art-04037efad9484146beeffada2a41e183
institution Directory Open Access Journal
issn 1453-1305
1842-8088
language English
last_indexed 2024-12-23T20:09:14Z
publishDate 2015-01-01
publisher Inforec Association
record_format Article
series Informatică economică
spelling doaj.art-04037efad9484146beeffada2a41e1832022-12-21T17:32:51ZengInforec AssociationInformatică economică1453-13051842-80882015-01-01192344510.12948/issn14531305/19.2.2015.04An Artificial Neural Network for Data Forecasting PurposesCatalina Lucia COCIANUHakob GRIGORYANConsidering the fact that markets are generally influenced by different external factors, the stock market prediction is one of the most difficult tasks of time series analysis. The research reported in this paper aims to investigate the potential of artificial neural networks (ANN) in solving the forecast task in the most general case, when the time series are non-stationary. We used a feed-forward neural architecture: the nonlinear autoregressive network with exogenous inputs. The network training function used to update the weight and bias parameters corresponds to gradient descent with adaptive learning rate variant of the backpropagation algorithm. The results obtained using this technique are compared with the ones resulted from some ARIMA models. We used the mean square error (MSE) measure to evaluate the performances of these two models. The comparative analysis leads to the conclusion that the proposed model can be successfully applied to forecast the financial data.http://revistaie.ase.ro/content/74/04%20-%20cocianu,%20grigoryan.pdfNeural NetworkNonlinear Autoregressive NetworkExogenous InputsTime SeriesARIMA Model
spellingShingle Catalina Lucia COCIANU
Hakob GRIGORYAN
An Artificial Neural Network for Data Forecasting Purposes
Informatică economică
Neural Network
Nonlinear Autoregressive Network
Exogenous Inputs
Time Series
ARIMA Model
title An Artificial Neural Network for Data Forecasting Purposes
title_full An Artificial Neural Network for Data Forecasting Purposes
title_fullStr An Artificial Neural Network for Data Forecasting Purposes
title_full_unstemmed An Artificial Neural Network for Data Forecasting Purposes
title_short An Artificial Neural Network for Data Forecasting Purposes
title_sort artificial neural network for data forecasting purposes
topic Neural Network
Nonlinear Autoregressive Network
Exogenous Inputs
Time Series
ARIMA Model
url http://revistaie.ase.ro/content/74/04%20-%20cocianu,%20grigoryan.pdf
work_keys_str_mv AT catalinaluciacocianu anartificialneuralnetworkfordataforecastingpurposes
AT hakobgrigoryan anartificialneuralnetworkfordataforecastingpurposes
AT catalinaluciacocianu artificialneuralnetworkfordataforecastingpurposes
AT hakobgrigoryan artificialneuralnetworkfordataforecastingpurposes