The pattern prediction results from the Sony 2006 and Toshiba share data have been analyzed using Adaplet Method, a wavelet based adaptive filter (adaptive filter which its initial coefficients are wavelet coefficients), which is based on Coiflet, Symlet and Daubechies Wavelets. According to these wavelets, it has shown that, for all data, as its wavelet level increased the anomaly patterns at the beginning of data also increase. For Coiflet wavelet, each result is different but the error correlations are going to smooth (approaching zero). For Symlet Wavelet, the result is not quite different and the error correlations also not so good. For Daubechies Wavelet, the result is not quite different between wavelet levels, and the error correlations is not so good (always oscillates). So the wavelet chosen affects the prediction pattern results and the error correlations, which for these data, the Coiflet Wavelet offer good prediction pattern result and good error correlation.

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6 Responses to “Prediction Results Analysis of Sony 2006 and Toshiba 2006 Share Data using Adaplet Method (Wavelet based Adaptive Filter)”

  1. thank you for sharing

  2. thank you for sharing it’s so helpful

  3. thanks for sharing

  4. Thanks, that was very useful.

  5. Thank you so much for the beautiful material


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