Physics – Data Analysis – Statistics and Probability
Scientific paper
2007-05-23
EPL, 80 (2007) 30005
Physics
Data Analysis, Statistics and Probability
6 pages, 4 figures
Scientific paper
10.1209/0295-5075/80/30005
The ARCH process (R. F. Engle, 1982) constitutes a paradigmatic generator of stochastic time series with time-dependent variance like it appears on a wide broad of systems besides economics in which ARCH was born. Although the ARCH process captures the so-called "volatility clustering" and the asymptotic power-law probability density distribution of the random variable, it is not capable to reproduce further statistical properties of many of these time series such as: the strong persistence of the instantaneous variance characterised by large values of the Hurst exponent (H > 0.8), and asymptotic power-law decay of the absolute values self-correlation function. By means of considering an effective return obtained from a correlation of past returns that has a q-exponential form we are able to fix the limitations of the original model. Moreover, this improvement can be obtained through the correct choice of a sole additional parameter, $q_{m}$. The assessment of its validity and usefulness is made by mimicking daily fluctuations of SP500 financial index.
No associations
LandOfFree
On a generalised model for time-dependent variance with long-term memory does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with On a generalised model for time-dependent variance with long-term memory, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On a generalised model for time-dependent variance with long-term memory will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-401083