*Tid:* **8 september, 2017, kl 14.00-14.30.**
**Seminarierummet F11**, Institutionen för
matematik, KTH, Lindstedtsvägen 22.
Karta!
*Föredragshållare:*
**
Simon Carmelid
**
**Titel:**
Calibrating the Hull-White model using
Adjoint Algorithmic Differentiation
**Abstract**
This thesis includes a brief introduction to Adjoint Algorithmic Differentiation
(AAD), accompanied by numerical examples, step-by-step explanations
and runtime comparisons to a finite difference method. In order to show the
applicability of AAD in a stochastic setting, it is also applied in the calculation
of the arbitrage free price and partial derivatives of a European call option,
where the underlying stock is has Geometric Browninan motion dynamics.
Finally the Hull-White model is calibrated using a set of zero coupon bonds,
and a set of swaptions. Using AAD, the partial derivatives of the model are
found and used in a Newton-Raphson method in order to find the market?s
implied volatility. The end result is a Monte Carlo simulated short rate curve
and its derivatives with respect to the calibration parameters, i.e. the zero
coupon bond and swaption prices.
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