We investigate the large-volatility dynamics in financial markets, based on the minutely and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after large volatilities is characterized by a power law, and the exponents p_\pm usually vary with the strength of the large volatilities. The large-volatility dynamics is time-reversal symmetric at the minutely time scale , while asymmetric at the daily time scale. Careful analysis reveals that the time-reversal asymmetry is mainly induced by exogenous events. It is also the exogenous events which drive the financial dynamics to a non-stationary state. In general, the Chinese Indices and German DAX are in different universality classes. An interacting herding model without and with exogenous driving forces could qualitatively describe the large-volatility dynamics .
We investigate the large-volatility dynamics in financial markets, based on the minute-to-minute and daily data of the Chinese Indices and German DAX. The dynamic relaxation both before and after large volatilities is characterized by a power law, and the exponents p_\pm usually vary with the strength of the large volatilities. The large-volatility dynamics is time-reversal symmetric at the time scale in minutes , while asymmetric at the daily time scale. Careful analysis reveals that the time-reversal asymmetry is mainly induced by exogenous events. It is also the exogenous events which drive the financial dynamics to a non-stationary state. Different characteristics of the Chinese and German stock markets are uncovered .
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minutely
minute-to-minute
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minutely time scale
time scale in minutes
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In general, the Chinese Indices and German DAX are in different universality classes. An interacting herding model without and with exogenous driving forces could qualitatively describe the large-volatility dynamics
Different characteristics of the Chinese and German stock markets are uncovered