[R-SIG-Finance] ugarchfit and arima seem contradictory?

[alexios]

1. Read the documentation of Box.test, and in particular on the option 
"fitdf" which needs to be adjusted when passing the
residuals of an ARMA filtration.
2. rugarch uses: type = "Ljung-Box"
3. Observe email etiquette by using your name when posting (this is your 
third email without one).

Alexios




On 11/02/12 14:18, ecsniffer林娟 wrote:
>
> I use ARMAX(4,1) model to estimate the volatility and include interest rate r_t as the exogenous variable. I use the arima function and ugarchfit function from RUGARCH package, respectively. The results seem to contradict with each other.
>
> If I use arima function,
> my code is as follows,
> data<-read.csv("...")
> volatility<-ts(data$volatility);
> rate<-ts(data$diff_rate);
> result=arima(volatility,order=c(4,0,1),xreg=rate)
> Box.test(result$residuals, lag =10, type = c("Box-Pierce", "Ljung-Box"))
>
> The output is as follows,
>   Box-Pierce test
> data:  result$residuals
> X-squared = 13.1749, df = 10, p-value = 0.2141
> which means no correlation among the residuals.
>
> However, if I use RUPACKAGE,
> my code is as follows,
> spec=ugarchspec(variance.model=list(model="sGARCH",garchOrder=c(1,1),submodel=NULL,
> + external.regressors=as.matrix(rate), variance.targeting = FALSE),
> + mean.model = list(armaOrder = c(4,1), include.mean = TRUE, garchInMean = FALSE,
> + inMeanType = 1, arfima = FALSE, external.regressors =as.matrix(rate)), distribution.model = "std",
> + start.pars = list(), fixed.pars = list())
> fit=ugarchfit(spec,data=as.matrix(volatility))
> fit
>
> The output is as follows,
> Q-Statistics on Standardized Residuals
> ------------------------------------
>                 statistic   p-value
> Lag10     15.76      0.0075508
> Lag15     21.98      0.0152135
> Lag20     42.29      0.0002031
> H0 : No serial correlation
> which means there exisits correlation among the residuals.
>
>
>
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