A Note on "Quasi-Maximum-Likelihood Estimation in Conditionally Heteroscedastic Time Series: A Stochastic Recurrence Equations Approach"
By: Frederik Krabbe
Potential Business Impact:
Makes computer predictions get more accurate over time.
Bougerol (1993) and Straumann and Mikosch (2006) gave conditions under which there exists a unique stationary and ergodic solution to the stochastic difference equation $Y_t \overset{a.s.}{=} \Phi_t (Y_{t-1}), t \in \mathbb{Z}$ where $(\Phi_t)_{t \in \mathbb{Z}}$ is a sequence of stationary and ergodic random Lipschitz continuous functions from $(Y,|| \cdot ||)$ to $(Y,|| \cdot ||)$ where $(Y,|| \cdot ||)$ is a complete subspace of a real or complex separable Banach space. In the case where $(Y,|| \cdot ||)$ is a real or complex separable Banach space, Straumann and Mikosch (2006) also gave conditions under which any solution to the stochastic difference equation $\hat{Y}_t \overset{a.s.}{=} \hat{\Phi}_t (\hat{Y}_{t-1}), t \in \mathbb{N}$ with $\hat{Y}_0$ given where $(\hat{\Phi}_t)_{t \in \mathbb{N}}$ is only a sequence of random Lipschitz continuous functions from $(Y,|| \cdot ||)$ to $(Y,|| \cdot ||)$ satisfies $\gamma^t || \hat{Y}_t - Y_t || \overset{a.s.}{\rightarrow} 0$ as $t \rightarrow \infty$ for some $\gamma > 1$. In this note, we give slightly different conditions under which this continues to hold in the case where $(Y,|| \cdot ||)$ is only a complete subspace of a real or complex separable Banach space by using close to identical arguments as Straumann and Mikosch (2006).
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