Deep Learning and Autoregressive Approach for Prediction of Time Series Data

Journal: Journal of Autonomous Intelligence DOI: 10.32629/jai.v3i2.207

Akhter Mohiuddin Rather

Great Lakes Institute of Management, Gurgaon


A deep neural network based approach for prediction of non-stationary data has been proposed in this work. A new
regression scheme has been used in the proposed model. Any non-stationary data can be used to test the efficiency of
the proposed model, however in this work stock data has been used due to the fact that stock data has a property
of being nonlinear or non-stationary in nature. Beside using proposed model, predictions were also obtained using some
statistical models and artificial neural networks. Traditional statistical models did not yield any expected results;
artificial neural networks resulted into high time complexity. Therefore, deep learning approach seemed to be the best
method as of today in dealing with such problems wherein time complexity and excellent predictions are of concern.


Artificial Neural Networks; Autoregressive Model; Deep Learning; Time series; Keras


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