Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
979629 | Physica A: Statistical Mechanics and its Applications | 2007 | 11 Pages |
Abstract
The measure of long-term memory is important for the study of economic and financial time series. This paper estimates the Hurst exponent from a Scaled Variance Ratio model for 17 commodity price series under the efficient market null H0:H=0.5. The distribution about the estimates of H are obtained from 90%, 95% and 99% confidence intervals generated from 20,000 Monte Carlo replications of a geometric Brownian motion. The results show that the scaled variance ratio provides a very good and stable estimate of the Hurst exponent, but the estimates can be quite different from the measure obtained from rescaled range or R-S analysis. In general commodity prices are consistent with the underlying assumption of a geometric Brownian motion.
Related Topics
Physical Sciences and Engineering
Mathematics
Mathematical Physics
Authors
Calum G. Turvey,