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Deep Learning and Autoregressive Approach for Prediction of Time Series Data

Akhter Mohiuddin Rather

Abstract


A deep neural network based approach for prediction of non-stationary data has been proposed in this work. A newregression scheme has been used in the proposed model. Any non-stationary data can be used to test the efficiency ofthe proposed model, however in this work stock data has been used due to the fact that stock data has a propertyof being nonlinear or non-stationary in nature. Beside using proposed model, predictions were also obtained using somestatistical 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 bestmethod as of today in dealing with such problems wherein time complexity and excellent predictions are of concern.

Keywords


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

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References


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DOI: https://doi.org/10.32629/jai.v3i2.207

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