Analysis of ARIMA-Artificial Neural Network Hybrid Model in Forecasting of Stock Market Returns

Author:

Musa Yakubu,Joshua Stephen

Abstract

This study focuses on the modelling of Nigerian stock market all–shares index and evaluations of predictions ability using ARIMA, Artificial Neural Network and a hybrid ARIMA-Artificial Neural Network model. The ARIMA (1,1,1) model and neural network with architecture (6:1:3) turns out to be the most fitted among the considered models, these models were used for forecasting the returns, and their performances have been compared according to some statistical measure of accuracy. A hybrid model has been constructed using ARIMA-Artificial Neural Networks model, the computational results on the data reveal that the hybrid model using Artificial Neural Network, provides better forecasts, and will enhance forecasting over the single ARIMA and Artificial Neural Networks models. The study recommends the use of ARIMA-Artificial neural network for modelling and forecasting stock market returns.

Publisher

Sciencedomain International

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Progress and prospects of data-driven stock price forecasting research;International Journal of Cognitive Computing in Engineering;2023-06

2. Estimating Construction Material Indices with ARIMA and Optimized NARNETs;Computers, Materials & Continua;2023

3. A comparative analysis of market forecasting using ANNs;INTERNATIONAL CONFERENCE ON SCIENCE, ENGINEERING, AND TECHNOLOGY 2022: Conference Proceedings;2023

4. Stock Market Forecasting Using the Random Forest and Deep Neural Network Models Before and During the COVID-19 Period;Frontiers in Environmental Science;2022-07-25

5. Forecasting Selected Colombian Shares Using a Hybrid ARIMA-SVR Model;Mathematics;2022-06-23

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