A Multi - Horizon Scale for Volatility Alexander SUBBOTIN
نویسنده
چکیده
We decompose volatility of a stock market index both in time and scale using wavelet filters and design a probabilistic indicator for volatilities, analogous to the Richter scale in geophysics. The peakover-threshold method is used to fit the generalized Pareto probability distribution for the extreme values in the realized variances of wavelet coefficients. The indicator is computed for the daily Dow Jones Industrial Average index data from 1896 to 2007 and for the intraday CAC40 data from 1995 to 2006. The results are used for comparison and structural multi-resolution analysis of extreme events on the stock market and for the detection of financial crises.
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