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An algorithm using GARCH process , Monte-Carlo simulation and wavelets analysis for stock prediction

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  • Giovanis, Eleftherios

Abstract

This paper examines and presents a simple algorithm for prediction stock written in MATLAB code. We apply it to thirty stocks of the Athens exchange stock market . We obtain the stock returns and we would like to predict, not the actual price , but the sign of stock returns. The results are very satisfying while we predict the right sign for 25 out of 30 cases or else we have a success of 83.33%. The problem with the algorithm is that we don’t have the ability to predict zero returns.

Suggested Citation

  • Giovanis, Eleftherios, 2008. "An algorithm using GARCH process , Monte-Carlo simulation and wavelets analysis for stock prediction," MPRA Paper 10674, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:10674
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    References listed on IDEAS

    as
    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Leung, Mark T. & Daouk, Hazem & Chen, An-Sing, 2000. "Forecasting stock indices: a comparison of classification and level estimation models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 173-190.
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    More about this item

    Keywords

    GARCH˙ wavelets˙ forecasting˙ Monte-Carlo˙ wavelet discrete transformation;

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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