On Mon, May 21, 2012 at 9:20 PM, Hideyoshi Maeda <hideyoshi.ma...@gmail.com>wrote:
> Doing a quick comparison of the difference in code for the volatility > estimate in using 'yang.zhang' as a calculation method, > on S&P 500 data, going back from the beginning of 2001 till today (22 May 2012). These were the results from the following lines of code: > > N.B. volatility.new is the edited code with the suggestion of using runVar > instead of runSum, as suggested by James > N.B SPX.ohlc is an xts object of that contains OHLC data for the Bloomberg > ticker "SPX Index" > > > original.vol.code <- volatility(SPX.ohlc, calc="yang.zhang") > > new.vol.code <- volatility.new(SPX.ohlc, calc="yang.zhang") > > plot((new.vol.code-original.vol.code)*100/original.vol.code, main="% > difference in volatility esitimates > + when comparing new and old code") > > Some quite significant percentage differences getting up to approx. -10% > viewing it as a histogram in terms of differences, you get... > I was actually surprised that the calculation isn't off by more, but the inner runSum which calculates a rolling mean is usually fairly stable, especially for longer n. I don't know if Bloomberg can calculate volatility via yang.zhang, but that would be a worthwhile reference to compare. Best, James [[alternative HTML version deleted]] _______________________________________________ R-SIG-Finance@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.