Abstract
In this paper we introduce an ACD-ECOGARCH(1, 1) model. An exponential autoregressive conditional durationmodel is used to describe the dependence structure in durations of ultra-high-frequency financial data. The innovation process of the ACD model then defines the interarrival times of a compound Poisson process. We use this compound Poisson process as the background driving Lévy process of an exponential continuous time GARCH(1, 1) process. The dynamics of the random time transformed log-price process are then described by the latter process. To estimate its parameters we construct a quasi maximum likelihood estimator under the assumption that all jumps of the log-price process are observable. Finally, the model is fitted for illustrative purpose to General Motors tick-by-tick data of the New York Stock Exchange.
Original language | English |
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Article number | nbp023 |
Pages (from-to) | 335-344 |
Number of pages | 10 |
Journal | Journal of Financial Econometrics |
Volume | 8 |
Issue number | 3 |
DOIs | |
State | Published - 4 Nov 2009 |
Keywords
- ACD
- ECOGARCH
- Leverage effect
- QMLE
- Ultra-high-frequency data