Institute of Information Theory and Automation

You are here

Bibliography

Journal Article

How are rescaled range analyses affected by different memory and distributional properties? A Monte Carlo study

Krištoufek Ladislav

: Physica. A : Statistical Mechanics and its Applications vol.391, 17 (2012), p. 4252-4260

: 118310, GA UK, 261 501, SVV, GA402/09/0965, GA ČR

: Rescaled range analysis, Modified rescaled range analysis, Hurst exponent, Long-term memory, Short-term memory

: 10.1016/j.physa.2012.04.005

: http://library.utia.cas.cz/separaty/2012/E/kristoufek-how are rescaled range analyses affected by different memory and distributional properties.pdf

(eng): In this paper, we present the results of Monte Carlo simulations for two popular techniques of long-range correlation detection — classical and modified rescaled range analyses. A focus is put on an effect of different distributional properties on an ability of the methods to efficiently distinguish between short-term memory and long-term memory. To do so, we analyze the behavior of the estimators for independent, short-range dependent, and long-range dependent processes with innovations from eight different distributions. We find that apart from a combination of very high levels of kurtosis and skewness, both estimators are quite robust to distributional properties. Importantly, we show that R/S is biased upwards (yet not strongly) for short-range dependent processes, while M-R/S is strongly biased downwards for long-range dependent processes regardless of the distribution of innovations.

: AH

2019-01-07 08:39