Model[Swing_Option]__Pricing_Method

Available

Corresponds to the QuantLib FdSimpleBSSwing Engine.

This model assumes the underlying price follows a Black-Scholes-Merton dynamics, which is then discritized using a 1-factor finite differences grid.

As such, the dividend yield (or storage cost), spot underlying price and volatility must all be supplied as input in the market data.

Corresponds to the QuantLib FdSimpleExtOUJumpSwing Engine, which is based on a two-factor finite differences discretization method.

Note this engine still lies in the QuantLib's experimental folder, which means it has not been adequately tested!

This model assumes the underlying price follows an exponential Ornstein Uhlenbeck stochastic process with jumps (details in Exp OU Process), which is then discritized using a 2-factor finite differences grid.

As such, no dividend yield (or storage cost), spot underlying price or volatility are required as input in the market data.

The burden falls upon specifying the parameters of the stochastic process.

No calibration routine is currently available.

One may use the Excel solver to fine tune some of the parameters by pricing swing options whose price is known, for example swing options with one allowed exercise that behave like vanilla european options.