Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting

59 Pages Posted: 4 Sep 2020

See all articles by Heni Boubaker

Heni Boubaker

IPAG Business School

Giorgio Canarella

University of Nevada, Las Vegas

Rangan Gupta

University of Pretoria - Department of Economics

Stephen M. Miller

University of Nevada, Las Vegas - Department of Economics; University of Connecticut - Department of Economics

Date Written: July 26, 2020

Abstract

This paper proposes a hybrid modelling approach for forecasting returns and volatilities of the stock market. The model, called ARFIMA-WLLWNN model, integrates the advantages of the ARFIMA model, the wavelet decomposition technique (namely, the discrete MODWT with Daubechies least asymmetric wavelet filter) and artificial neural network (namely, the LLWNN neural network). The model develops through a two-phase approach. In phase one, a wavelet decomposition improves the forecasting accuracy of the LLWNN neural network, resulting in the Wavelet Local Linear Wavelet Neural Network (WLLWNN) model. The Back Propagation (BP) and Particle Swarm Optimization (PSO) learning algorithms optimize the WLLWNN structure. In phase two, the residuals of an ARFIMA model of the conditional mean become the input to the WLLWNN model. The hybrid ARFIMA-WLLWNN model is evaluated using daily closing prices for the Dow Jones Industrial Average (DJIA) index over 01/01/2010 to 02/11/2020. The experimental results indicate that the PSO-optimized version of the hybrid ARFIMA-WLLWNN outperforms the LLWNN, WLLWNN, ARFIMA-LLWNN, and the ARFIMA-HYAPARCH models and provides more accurate out-of-sample forecasts over validation horizons of one, five and twenty-two days.

Keywords: Wavelet decomposition, WLLWNN, Neural network, ARFIMA, HYGARCH

JEL Classification: C45, C58, G17

Suggested Citation

Boubaker, Heni and Canarella, Giorgio and Gupta, Rangan and Miller, Stephen M., Hybrid ARFIMA Wavelet Artificial Neural Network Model for DJIA Index Forecasting (July 26, 2020). Available at SSRN: https://ssrn.com/abstract=3660943 or http://dx.doi.org/10.2139/ssrn.3660943

Heni Boubaker

IPAG Business School ( email )

184 BD Saint Germain
Paris, 75006
France

Giorgio Canarella

University of Nevada, Las Vegas ( email )

4505 S. Maryland Parkway
Box 456005
Las Vegas, NV 89154-6005
United States

Rangan Gupta

University of Pretoria - Department of Economics ( email )

South Africa

Stephen M. Miller (Contact Author)

University of Nevada, Las Vegas - Department of Economics ( email )

4505 S. Maryland Parkway
Box 456005
Las Vegas, NV 89154
United States
702-895-3776 (Phone)
702-895-1354 (Fax)

HOME PAGE: http://faculty.unlv.edu/smiller/

University of Connecticut - Department of Economics

365 Fairfield Way, U-1063
Storrs, CT 06269-1063
United States

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