Abstract
We have adapted and extended the Petruccelli-Davies test, Petruccelli's test and Tsay's test for non-linearity in time series to cope with partially observed series. The Kalman filtering algorithm is used in the estimation stage to realize the adaptation. Two of the adapted tests are checked with a Monte Carlo study and all three tests are applied to three real series from the financial world. The fine tuning achieved by allowing for closing date effects offers further insights.
| Original language | English |
|---|---|
| Pages (from-to) | 43-62 |
| Journal | Journal of the Royal Statistical Society. Series C: Applied Statistics |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 1991 |
Bibliographical note
Research Unit(s) information for this publication is provided by the author(s) concerned.Research Keywords
- Hang Seng index
- IBM stock price
- Kalman filter
- Non-linearity
- Partial observations
- Petruccelli-Davies test
- Petruccelli's test
- Self-exciting threshold autoregression
- Share price
- Tsay's test