title: Multivariate GARCH(1,1) in R
body: <p>I use R to estimate a Multivariate GARCH(1,1) model for 4 time series. I tried it with the rmgarch package. Seems like I'm using it wrong but I don't know what my mistake is. First time using.</p>
  
  <pre><code>library(quantmod)
  library(fBasics)
  library(rmgarch)
  #load data, time series closing prices, 10 year sample
  #DAX 30
  getSymbols('^GDAXI', src='yahoo', return.class='ts',from="2005-01-01",    to="2015-01-31")
  GDAXI.DE=GDAXI[ , "GDAXI.Close"]
  #S&amp;P 500
  getSymbols('^GSPC', src='yahoo', return.class='ts',from="2005-01-01", to="2015-01-31")
  GSPC=GSPC[ , "GSPC.Close"]
  #Credit Suisse Commodity Return Strat I
  getSymbols('CRSOX', src='yahoo', return.class='ts',from="2005-01-01", to="2015-01-31")
  CRSOX=CRSOX[ , "CRSOX.Close"]
  #iShares MSCI Emerging Markets
  getSymbols('EEM', src='yahoo', return.class='ts',from="2005-01-01", to="2015-01-31")
  EEM=EEM[ , "EEM.Close"]
  #calculating log returns of the time series
  log_r1=diff(log(GDAXI.DE[39:2575]))
  log_r2=diff(log(GSPC))
  log_r3=diff(log(CRSOX))
  log_r4=diff(log(EEM))
  #return vector
  r_t=cbind(log_r1, log_r2,log_r3, log_r4)
  #specifying and fitting the model
  model = multispec(replicate(4, ugarchspec(variance.model = c(1,1))))
  model_order = mgarchspec(model, Order = c(1, 1), distribution ='mvnorm')
  fit = mgarchfit(model_order, data = r_t, solver = 'solnp',fit.control =    list(eval.se = TRUE))
  print(fit.1)
  </code></pre>