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The Application of Random Noise Reduction By Nearest Neighbor Method To Forecasting of Economic Time Series

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  • Miśkiewicz-Nawrocka Monika

    (University of Economics in Katowice, Faculty of Management, Department of Mathematics, 1 Maja 50, 40-287 Katowice, Poland)

Abstract

Since the deterministic chaos appeared in the literature, we have observed a huge increase in interest in nonlinear dynamic systems theory among researchers, which has led to the creation of new methods of time series prediction, e.g. the largest Lyapunov exponent method and the nearest neighbor method. Real time series are usually disturbed by random noise, which can complicate the problem of forecasting of time series. Since the presence of noise in the data can significantly affect the quality of forecasts, the aim of the paper will be to evaluate the accuracy of predicting the time series filtered using the nearest neighbor method. The test will be conducted on the basis of selected financial time series.

Suggested Citation

  • Miśkiewicz-Nawrocka Monika, 2014. "The Application of Random Noise Reduction By Nearest Neighbor Method To Forecasting of Economic Time Series," Folia Oeconomica Stetinensia, Sciendo, vol. 13(2), pages 96-108, July.
    • Handle: RePEc:vrs:foeste:v:13:y:2014:i:2:p:13:n:9
    DOI: 10.2478/foli-2013-0020
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    References listed on IDEAS

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    More about this item

    Keywords

    random noise reduction; nearest neighbor method; largest Lyapunov exponent; financial time series forecasting;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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