Data analysis with GARCH modeling I'm currently analyzing the relationship between stock, bonds, and real estate returns in Germany. I've gathered my data and am planning on estimating this equation:

$\sigma_t = \beta_0 + \beta_1 R_{t+} + \beta_2 R_{t-} + y_t$

through a GARCH model. In the article where I found equation 1 (Chan and Chang, 2014), they
    have delineted the parameters as so: $R_{t+}= \max [0, R_t]$, $R_{t–} = \min
[0, R_t]$, and $R_t$ is the monthly return of stock, bond, or real
    estate. We use a three-month rolling return to calculate the
    standard deviation of the return." Does this mean they use the Max
    and Min of the series as parameters or the Max and Min of each
    rolling average across the series?
Well I havent read the paper but this is what it looks like to me:


Compute $R_t$ - the rolling average for month t.
$R_t &gt; 0 \Rightarrow  R_{t+} = R_t \wedge R_{t-} = 0$ and$R_t &lt; 0 \Rightarrow  R_{t-} = R_t \wedge R_{t+} = 0$