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I found excellent notes on ARCH and GARCH models here. On page 3 it is given that:

Standard time series models:

\begin{eqnarray*} Y_{t} & = & E\left(Y_{t}|\Omega_{t-1}\right)+\epsilon_{t}\\ E\left(Y_{t}|\Omega_{t-1}\right) & = & \mu_{t}\left(\theta\right)\\ E\left(Y_{t}|\Omega_{t-1}\right) & = & E\left(\epsilon_{t}^{2}|\Omega_{t-1}\right)=\sigma^{2} \end{eqnarray*}

What does this $\Omega$ means here? Any help will be highly appreciated. Thanks

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Roughly speaking, $\Omega_{t-1}$ is all the information available up to time $t-1$. For example, it can be considered as the observed values of your time series i.e. $Y_0, Y_1, Y_2, ..., Y_{t-1}$. If I want to be more precise, it is the $\sigma$-algebra generated by all these random variables i.e. $\Omega_{t-1}=\sigma\{Y_0, Y_1, Y_2, ..., Y_{t-1}\}$.

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