Option with IV compromised of two components that changes over time

classic Classic list List threaded Threaded
2 messages Options
Reply | Threaded
Open this post in threaded view
|

Option with IV compromised of two components that changes over time

Mini Trader
I have an option which I am saying has an IV that is the weighted aggregate of two underlying volatilities.

E.g. Aggregate volatility is made up of 90% part A vol and 10% part B vol.  The aggregate is just a weighted average of the two.

The weight itself can change through time e.g. part B might be the result of an upcoming event (earnings) so once the event completes I would expect the the weighting to move back entirely to Part A that is Aggregate volatility becomes 100% part A and 0% part B.

What components of quantlib could assist in modelling this type of behavior?

------------------------------------------------------------------------------

_______________________________________________
QuantLib-users mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-users
Reply | Threaded
Open this post in threaded view
|

Re: Option with IV compromised of two components that changes over time

Luigi Ballabio
Hello,
    there's no such class.  If you wanted to write it, you might inherit it from BlackVolatilityTermStructure. Its constructor would take two instances of Handle<BlackVolTermStructure> representing volatilities A and B and an instance of Handle<Quote> representing the weight; and its blackVolImpl() method would combine the two underlying volatilities. Calling the setValue() method on the quote and passing a new weight would change the composition. (Kind of sketchy, I know. Write back if you need more details.)

Hope this helps,
    Luigi


On Sun, Mar 6, 2016 at 4:16 PM Mini Trader <[hidden email]> wrote:
I have an option which I am saying has an IV that is the weighted aggregate of two underlying volatilities.

E.g. Aggregate volatility is made up of 90% part A vol and 10% part B vol.  The aggregate is just a weighted average of the two.

The weight itself can change through time e.g. part B might be the result of an upcoming event (earnings) so once the event completes I would expect the the weighting to move back entirely to Part A that is Aggregate volatility becomes 100% part A and 0% part B.

What components of quantlib could assist in modelling this type of behavior?
------------------------------------------------------------------------------
_______________________________________________
QuantLib-users mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-users

------------------------------------------------------------------------------
Transform Data into Opportunity.
Accelerate data analysis in your applications with
Intel Data Analytics Acceleration Library.
Click to learn more.
http://pubads.g.doubleclick.net/gampad/clk?id=278785111&iu=/4140
_______________________________________________
QuantLib-users mailing list
[hidden email]
https://lists.sourceforge.net/lists/listinfo/quantlib-users