Wavelet-based analysis of the Mexican stock market
Keywords:
wavelets, multiresolution analysis, variance, aggregative- Gaussianity, stock marketsAbstract
This paper analyzes the main Mexican equity index (IPC) behavior at different time scales under a wavelet-based approach, which aims to obtain detailed information about it rather than a global approach. The former is performed by decomposing the IPC returns at different resolution levels using the maximal overlap discrete wavelet transform (MODWT) and the least asymmetric LA (8) Daubechies wavelet as the filtering function. Results show evidence of aggregative-Gaussianity, a type of asymmetric phenomenon in which returns distribution varies at different time scales. Also, the wavelet variance showed a greater value at scales with short-time spans than longer ones, which may result under the Value-at-Risk (VaR) framework in greater potential losses at short-time investment horizons.
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