[R-SIG-Finance] [R-sig-finance] Moving volatility

[Joshua Ulrich]

Eduard,

Please read the documentation.  ?addVolatility notes that it uses the
volatility function in TTR.

TTR's moving window functions (see ?runFun) call compiled code, so
they are very fast.  They also use xts internally, so they accept and
return a variety of time series classes (ts, zoo, timeSeries, etc.).

Best,
Josh
--
http://www.fosstrading.com



On Tue, Aug 4, 2009 at 8:08 AM, Shane Conway<shane.conway at gmail.com> wrote:
> You can use the rollVar() function in rmetrics or the volatility() function
> in TTR.
>
> On Tue, Aug 4, 2009 at 8:41 AM, ehxpieterse
> <eduard.pieterse at macquarie.com>wrote:
>
>>
>> Hi,
>>
>> I have found a function online to calculate moving volatility. I am aware
>> of
>> addVolatility in the quantmod package, but that only adds the vol to a
>> graph. Does any one know if there exists a better function to use than the
>> one shown below? I find the current one quite slow when working with large
>> data sets.
>>
>> movsd <- function(series,lag)
>> {
>> movingsd <- vector(mode="numeric")
>> for (i in lag:length(series))
>>
>>        {
>>        movingsd[i] <- sd(series[(i-lag+1):i])
>>        }
>>
>> assign("movingsd",movingsd,.GlobalEnv)
>> }
>>
>> to.dat <- as.Date(Sys.Date(), format="%m/%d/%y")
>> getSymbols("^GSPC", src="yahoo", from = "2000-01-01", to = to.dat)
>> CloseData <- Cl(GSPC)
>>
>> x <- movsd(Delt(CloseData),40)
>> xx <- x*100
>> plot(xx, type="l")
>>
>> --
>> View this message in context:
>> http://www.nabble.com/Moving-volatility-tp24807675p24807675.html
>> Sent from the Rmetrics mailing list archive at Nabble.com.
>>
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