title: Extract residuals of dccroll function in rmgarch package in R
body: <p>I have a dataset containing returns of 6 assets. I want to forecast the conditional covariance matrix for the out-of-sample period. I use the package rmgarch and assume for a multi skewed t-distribution. The codes I write as follows:</p>
  <pre><code>adcc.garch11.spec_ = ugarchspec(mean.model = list(armaOrder = c(1,1)),
                                    variance.model = list(garchOrder = c(1,1),
                                                          model = &quot;eGARCH&quot;),
                                    distribution.model = &quot;std&quot;, fixed.pars = c(&quot;gamma1&quot;))
  
  # dcc specification - GARCH(1,1) for conditional correlations
  adcc.garch11.spec = dccspec(uspec = multispec(replicate(6, adcc.garch11.spec)), 
                                     dccOrder = c(1,1), distribution = &quot;mvt&quot;,model = &quot;aDCC&quot;)
  
  
  adcc.roll = dccroll(adcc.garch11.spec, data = dataset.xts[-1, c(&quot;ret_1&quot;,&quot;ret_2&quot;,&quot;ret_3&quot;,&quot;ret_4&quot;,&quot;ret_5&quot;,&quot;ret_6&quot;)],n.ahead = 1,
                            forecast.length = 1200, refit.every = 20, refit.window = &quot;moving&quot;, window.size = 2806, solver = &quot;solnp&quot;, solver.control = list(), save.fit = FALSE, save.wdir = NULL, trace=TRUE)
  </code></pre>
  <p>It is worthwile to mention that I did the same thing for a dcc and go-garch model (for go-garch model I used the <code>gogarchroll</code> function). So, I want to use the Diebold-Mariano test (in <code>multDM</code> package) to compare the predictive power of the three models amd I need the errors o each model but, when I used this code to extract the residuals:</p>
  <pre><code>df.residual(adcc.roll)
  </code></pre>
  <p>I get the error message:</p>
  <pre><code>Error: $ operator not defined for this S4 class
  </code></pre>
  <p>Does anyone know how to get this residuals?</p>
  <p>Thank you very much for the help!!!</p>