Volatility Dynamics of Wavelet-Filtered Stock Prices
Physics and Society
2008-12-02 v1 Statistical Finance
Abstract
Volatility dynamics of wavelet - filtered stock price time series is studied. Using the universal thresholding method of wavelet filtering and a principle of minimal linear autocorrelation of noise component we find that the quantitative characteristics of volatility dynamics of denoised series are noticeably different from those of the raw data and the noise.
Keywords
Cite
@article{arxiv.physics/0612170,
title = {Volatility Dynamics of Wavelet-Filtered Stock Prices},
author = {I. M. Dremin and A. V. Leonidov},
journal= {arXiv preprint arXiv:physics/0612170},
year = {2008}
}