Hybrid Models Combining Technical and Fractal Analysis with ANN for Short-Term Prediction of Close Values on the Warsaw Stock Exchange

This paper presents new methods and models for forecasting stock prices and computing hybrid models, combining analytical and neural approaches. First, technical and fractal analyses are conducted and selected stock market indices calculated, such as moving averages and oscillators. Next, on the bas...

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Bibliographic Details
Published inApplied sciences Vol. 8; no. 12; p. 2473
Main Authors Paluch, Michał, Jackowska-Strumiłło, Lidia
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.12.2018
Subjects
artificial neural networks
Fractal analysis
fractal dimension
Fractal models
fractal moving average
Fractals
hybrid models
Information systems
Modelling
Neural networks
Prediction models
Profits
stock exchange
Stock exchanges
technical analysis
Testing time
Time series
Poland
United States > US
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Summary:This paper presents new methods and models for forecasting stock prices and computing hybrid models, combining analytical and neural approaches. First, technical and fractal analyses are conducted and selected stock market indices calculated, such as moving averages and oscillators. Next, on the basis of these indices, an artificial neural network (ANN) provides predictions one day ahead of the closing prices of the assets. New technical analysis indicators using fractal modeling are also proposed. Three kinds of hybrid model with different degrees of fractal analysis were considered. The new hybrid modeling approach was compared to previous ANN-based prediction methods. The results showed that the hybrid model with fractal analysis outperforms other models and is more robust over longer periods of time.
ISSN:2076-3417
2076-3417
DOI:10.3390/app8122473