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A Hybrid EMD-ANN Model for Stock Price Prediction

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9873))

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Abstract

Financial time series such as foreign exchange rate and stock index, in general, exhibit non-linear and non-stationary behavior. Statistical models and machine learning models, often, fail to predict time series with such behavior. Former models are prone to large statistical errors. While machine learning models such as Support Vector Machines (SVM) and Artificial Neural Network (ANN) suffer from the limitations of overfitting and getting stuck in local minima, etc. In this paper, a hybrid model integrating the advantages of Empirical Mode Decomposition (EMD) and ANN is used to predict the short-term forecasts of Nifty stock index. In first stage, EMD is used to decompose the time series into a set of subseries, namely, intrinsic mode function (IMF) and residue component. In the next stage, ANN is used to predict each IMF independently along with residue component. The results show that the hybrid EMD-ANN model outperformed both SVR and ANN models without decomposition.

The original version of this chapter was revised: Two references have been added. The erratum to this chapter is available at DOI: 10.1007/978-3-319-48959-9_25

An erratum to this chapter can be found at http://dx.doi.org/10.1007/978-3-319-48959-9_25

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Notes

  1. 1.

    Difference of the first difference of the series. Suppose \(F(t) = y(t), y(t-1)... y(t-n)\), then the first difference is \(d1 = {y(t-1)-y(t)}, {y(t-2)-y(t-1)},...\) and the second difference \(d2 = {y(t-2)-2y(t-1)+y(t)},... \).

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Authors and Affiliations

  1. Department of Management Studies, Indian Institute of Technology Delhi, New Delhi, India

    Dhanya Jothimani, Ravi Shankar & Surendra S. Yadav

Authors
  1. Dhanya Jothimani
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  2. Ravi Shankar
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  3. Surendra S. Yadav
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Corresponding author

Correspondence to Dhanya Jothimani .

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Editors and Affiliations

  1. IIT, New Dehli, India

    Bijaya Ketan Panigrahi

  2. Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Indian Statistical Institute, Kolkata, India

    Swagatam Das

  4. Department of Computer Science Engineering, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, India

    Suresh Chandra Satapathy

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Jothimani, D., Shankar, R., Yadav, S.S. (2016). A Hybrid EMD-ANN Model for Stock Price Prediction. In: Panigrahi, B., Suganthan, P., Das, S., Satapathy, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2015. Lecture Notes in Computer Science(), vol 9873. Springer, Cham. https://doi.org/10.1007/978-3-319-48959-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-48959-9_6

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