Abstract
Time series of increments can be created in a number of different ways from a variety of physical phenomena. For example, in the phenomenon of volatility clustering—well-known in finance—magnitudes of adjacent increments are correlated. Moreover, in some time series, magnitude correlations display asymmetry with respect to an increment’s sign: the magnitude of depends on the sign of the previous increment . Here we define a model-independent test to measure the statistical significance of any observed asymmetry. We propose a simple stochastic process characterized by a an asymmetry parameter and a method for estimating . We illustrate both the test and process by analyzing physiological data.
- Received 24 March 2009
DOI:https://doi.org/10.1103/PhysRevE.80.015101
©2009 American Physical Society