[R-SIG-Finance] A question on volatility

[Adrian Trapletti]

I forgot to mention: Usually it is better to work with the logarithmic 
vola proxy, i.e., use

r<-log(r)

after the merge.

Best regards
Adrian

Adrian Trapletti wrote:
> Hi Megh,
>
> As a practitioner I would use something like
>
> x1 <- get.hist.quote(instrument = "^gspc", start = "1990-01-01")
> x2 <- get.hist.quote(instrument = "^dji", start = "1990-01-01")  ## 
> both need to be synchronized in time
>
> r1 <- log(x1[, 2])-log(x1[, 3]) ## range as proxy for vola
> r2 <- log(x2[, 2])-log(x2[, 3]) ## not ()^2 to avoid possibly 
> non-finite fourth moment
>
> r <- merge(r1, r2)
>
> plot(r)
>
> rcor <- rollapply(r, width = 250, FUN = function(z) cor(z[, 1], z[, 
> 2], method = "pearson"),
>                  by.column = FALSE, align = "left") ## method != 
> "pearson" for rank correlations
>
> plot(rcor)
>
> as a starting point. As a next step I would use a better proxy for 
> vola from the zoo of realized vola based estimators.
>
> Best regards
> Adrian
>
>> Dear all, I was trying to understand the correlation among 
>> the?volatilities?in different financial market, however am in dilemma 
>> what could be the rightful and acceptable-to-everyone approach. I 
>> thought to estimate the volatilities of?individual?markets using some 
>> GARCH modeling, then just calculate the correlation coefficient on 
>> the estimated time series of estimated daily volatilities.?
>>
>> Is it correct approach to understand the correlation? Can somebody 
>> point me any online paper or any idea on the same?
>>
>> Thanks for your time.
>

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