A risk analyst is estimating the variance of returns on a stock index for the next trading day. The analyst uses the following GARCH (1,1) model:

$$\sigma_n^2 = \alpha r_{n-1}^2 + \beta \sigma_{n-1}^2 + \gamma V_L$$

where $\sigma_n^2$, $r_{n-1}$, and $\sigma_{n-1}$ represent the index variance on day $n$, return on day $n-1$, and volatility on day $n-1$, respectively. If the expected value of the return is constant over time, which combination of values for $\alpha$ and $\beta$ would result in a stable GARCH (1,1) process?