A note on non-negative continuous time processes
Recently there has been much work on developing models that are suitable for analysing the volatility of a continuous time process. One general approach is to define a volatility process as the convolution of a kernel with a non-decreasing Lévy process, which is non-negative if the kernel is non-negative. Within the framework of time continuous autoregressive moving average (CARMA) processes, we derive a necessary and sufficient condition for the kernel to be non-negative. This condition is in terms of the Laplace transform of the CARMA kernel, which has a simple form. We discuss some useful consequences of this result and delineate the parametric region of stationarity and non-negative kernel for some lower order CARMA models. Copyright 2005 Royal Statistical Society.
Year of publication: |
2005
|
---|---|
Authors: | Tsai, Henghsiu ; Chan, K. S. |
Published in: |
Journal of the Royal Statistical Society Series B. - Royal Statistical Society - RSS, ISSN 1369-7412. - Vol. 67.2005, 4, p. 589-597
|
Publisher: |
Royal Statistical Society - RSS |
Saved in:
Saved in favorites
Similar items by person
-
Quasi-Maximum Likelihood Estimation for a Class of Continuous-time Long-memory Processes
Tsai, Henghsiu, (2005)
-
Tsai, Henghsiu, (2005)
-
Temporal Aggregation of Stationary and Non-stationary Continuous-Time Processes
TSAI, HENGHSIU, (2005)
- More ...