[Quantlib-dev] Implementing high-low volatility model

[Joseph W. <jo...@gn...>]

I'm in the process of trying to implement a class that does a Garman-Klass 
estimation of volatility based on high-low data.

Right now what I have in mind is a class called IntervalQuote(?) that contains 
open, close, high, low information, and this will be used with the TimeSeries 
template to produce

TimeSeries<IntervalQuote>

which will be the input into the calculation classes.  There will be a helper 
class that creates TimeSeries<IntervalQuote> from a vector of dates, open, 
close, high, and low data.

It seems that one should break up the VolatilityModel into two parts.  One 
part is LocalEstimator (?), the second part combinings the daily estimation 
into a time series using constant combining or GARCH, which would be 
subclasses of EstimationCombiner (?)

Since the LocalEstimator will need different types of inputs, there may be a 
need to create a trait.

Thoughts?  I'm especially interested in feedback as to getting the naming 
conventions right.