Abstract
This article considers short memory characteristics in a long memory process. We derive new asymptotic results for the sample autocorrelation difference ratios. We used these results to develop a new portmanteau test that determines if short memory parameters are statistically significant. In simulations, the new test can detect short memory components more often than the Ljung-Box test when these short memory components are in fact within a long memory process. Interestingly, our test finds short memory autocorrelations in U.S. inflation rate data, whereas the Ljung-Box test fails to find these autocorrelations. Modeling these short memory autocorrelations of the inflation rate data leads to improved model accuracy and more precise prediction.
Original language | English (US) |
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Pages (from-to) | 182-190 |
Number of pages | 9 |
Journal | American Statistician |
Volume | 69 |
Issue number | 3 |
DOIs | |
State | Published - Jul 3 2015 |
Externally published | Yes |
Keywords
- Autoregressive fractionally integrated moving-average
- Goodness-of-fit test
- Portmanteau test
- Sample autocorrelation
ASJC Scopus subject areas
- Statistics and Probability
- General Mathematics
- Statistics, Probability and Uncertainty