A Fibonacci Heap Based Ensemble Model for Stock Price Prediction

3 Pages Posted: 11 Apr 2019

See all articles by Vijay Kumar Dwivedi

Vijay Kumar Dwivedi

Motilal Nehru National Institute of Technology (MNNIT)

M.M. Gore

Motilal Nehru National Institute of Technology (MNNIT)

Date Written: April 9, 2019

Abstract

The prediction of stock price with high accuracy and consistency is a major challenge. A lot of research has been done to predict the stock price. However, there is a scope of improvement in accuracy and consistency of the prediction. This article proposes a Fibonacci heap based ensemble model that predicts the closing price of a stock for the next trading day. The proposed model is a combination of different (time series and regression) models. The model computes the median of significant prediction models that are organized in a Fibonacci heap data structure. The performance of this model is tested with the datasets of well-known eleven stocks. The results prove the effectiveness of the proposed model over other traditional prediction models with respect to consistency and accuracy

Keywords: Accuracy, Consistency, Ensemble, Fibonacci Heap, Prediction, Stock Price

Suggested Citation

Dwivedi, Vijay Kumar and Gore, M.M., A Fibonacci Heap Based Ensemble Model for Stock Price Prediction (April 9, 2019). Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE) 2019. Available at SSRN: https://ssrn.com/abstract=3368764 or http://dx.doi.org/10.2139/ssrn.3368764

Vijay Kumar Dwivedi (Contact Author)

Motilal Nehru National Institute of Technology (MNNIT) ( email )

Link Road Number 3
Near Kali Mata Mandir
Allahabad, IN Madhya Pradesh 452010
India

M.M. Gore

Motilal Nehru National Institute of Technology (MNNIT) ( email )

Link Road Number 3
Near Kali Mata Mandir
Allahabad, IN Madhya Pradesh 452010
India

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