## Annals of Applied Probability

### Continuous-time GARCH processes

#### Abstract

A family of continuous-time generalized autoregressive conditionally heteroscedastic processes, generalizing the COGARCH(1,1) process of Klüppelberg, Lindner and Maller [J. Appl. Probab. 41 (2004) 601–622], is introduced and studied. The resulting COGARCH(p,q) processes, qp≥1, exhibit many of the characteristic features of observed financial time series, while their corresponding volatility and squared increment processes display a broader range of autocorrelation structures than those of the COGARCH(1,1) process. We establish sufficient conditions for the existence of a strictly stationary nonnegative solution of the equations for the volatility process and, under conditions which ensure the finiteness of the required moments, determine the autocorrelation functions of both the volatility and the squared increment processes. The volatility process is found to have the autocorrelation function of a continuous-time autoregressive moving average process.

#### Article information

Source
Ann. Appl. Probab., Volume 16, Number 2 (2006), 790-826.

Dates
First available in Project Euclid: 29 June 2006

https://projecteuclid.org/euclid.aoap/1151592251

Digital Object Identifier
doi:10.1214/105051606000000150

Mathematical Reviews number (MathSciNet)
MR2244433

Zentralblatt MATH identifier
1127.62074

#### Citation

Brockwell, Peter; Chadraa, Erdenebaatar; Lindner, Alexander. Continuous-time GARCH processes. Ann. Appl. Probab. 16 (2006), no. 2, 790--826. doi:10.1214/105051606000000150. https://projecteuclid.org/euclid.aoap/1151592251

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