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A Fibonacci Heap Based Ensemble Model for Stock Price Prediction

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Document pages: 3 pages

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

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