AllPricingApproaches

Corresponds to the QuantLib AnalyticBarrier Engine.

Corresponds to the QuantLib AnalyticBSMHullWhite Engine.

2-factor model, with a closed-form solution, driven by stochastic underlying price and interest rates.

In particular, the underlying price is modelled to follow a Black-Scholes type, lognormal diffusion whereas the interest rate is modelled according to Hull White Model

The two processes are correlated with a given flat correlation number.

Corresponds to the QuantLib AnalyticDigitalAmerican Engine.

Corresponds to the QuantLib AnalyticDividendEuropean Engine.

Corresponds to the QuantLib AnalyticEuropean Engine.

It uses the Black-Scholes analytical formula for pricing european options. Web reference available here

Corresponds to the QuantLib AnalyticGJRGARCH Engine.

The underlying price is modelled according to GJRGARCH Model

Corresponds to the QuantLib AnalyticHeston Engine.

2-factor model, with a closed-form solution, driven by stochastic underlying price and volatility.

The underlying price process is modelled according to Heston Model

Allows the specification of:

Model[Vanilla Option]::Complex Log Formula

Model[Vanilla Option]::Integration

and also of the absolute/relative tolerance, maximum number of evaluations and the Andersen Piterbarg epsilon wrt the Fourier integration.

Corresponds to the QuantLib AnalyticHestonHullWhite Engine.

3-factor model, with a semi closed-form solution for call options, driven by stochastic underlying price, volatility and interest rates.

In particular, the underlying price is modelled to follow a Heston stochastic volatility process as in Heston Model, whereas the interest rate is modelled according to Hull White Model

References: Karel in't Hout, Joris Bierkens, Antoine von der Ploeg, Joe in't Panhuis.

Corresponds to the QuantLib AnalyticPTDHeston Engine, which is the Piecewise Time Dependent version of the regular AnalyticHeston Engine.

2-factor model, with a semi closed-form solution, driven by stochastic underlying price and volatility.

The underlying price process is modelled according to PTD Heston Model

Corresponds to the QuantLib BaroneAdesiWhaleyApproximation Engine.

It uses an approximating semi-analytical formula for pricing american options. Web reference available here

Corresponds to the QuantLib Bates Engine.

4-factor model, with a closed-form solution, driven by stochastic underlying price, volatility and jumps with random occurence and size.

The underlying price process is modelled according to Bates Model

Corresponds to the QuantLib BinomialVanilla Engine.

It uses a binomial tree model for pricing all types of options.

This method requires the specification of an object of type Tree

Corresponds to the QuantLib BjerksundStenslandApproximation Engine.

It uses an approximating semi-analytical formula for pricing american options. Web reference available here

Corresponds to the QuantLib FDAmerican Engine.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdBatesVanilla Engine.

3-factor model driven by stochastic underlying price, volatility and jumps.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

The underlying price is modelled according to Bates Model

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FDBermudan Engine.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdBlackScholesBarrier Engine, which internally calls the FdBlackScholesRebate engine if rebates are present.

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdBlackScholesVanilla Engine.

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FDDividendAmerican Engine.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FDDividendEuropean Engine.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

Known issue:

Although this method can only handle european options, it does not complain when the option being priced is not european.

The pricing proceeds silently as if were european!

This is a QuantLib treatment, which Deriscope does not attempt to alter.

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FDEuropean Engine.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

Known issue:

Although this method can only handle european options, it does not complain when the option being priced is not european.

The pricing proceeds silently as if were european!

This is a QuantLib treatment, which Deriscope does not attempt to alter.

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdHestonBarrier Engine, which internally calls the FdHestonRebate engine if rebates are present.

2-factor model driven by stochastic underlying price and volatility.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

The underlying price is modelled according to Heston Model

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdHestonHullWhiteVanilla Engine.

3-factor model driven by stochastic underlying price, volatility and interest rates.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

The underlying price is modelled to follow a Heston stochastic volatility process as in Heston Model, whereas the interest rate is also stochastic and modelled according to Hull White Model

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib FdHestonVanilla Engine.

2-factor model driven by stochastic underlying price and volatility.

It makes use of the implicit finite differences numerical scheme developed by John Crank and Phyllis Nicolson. Web reference available here

The underlying price is modelled according to Heston Model

This method requires the specification of an object of type Finite Differences

Corresponds to the QuantLib Integral Engine.

It prices european options through numerical computation of the integral of the payoff function over all possible stock price states at expiry. Web reference available here

Corresponds to the QuantLib JumpDiffusion Engine.

3-factor model, with a semi closed-form solution, driven by stochastic underlying price and jumps with random occurence and size.

The underlying price process is modelled according to Merton76 Model

Corresponds to the QuantLib JuQuadraticApproximation Engine.

It uses an approximating semi-analytical formula for pricing american options. Web reference available here

Warning: Barone-Adesi-Whaley critical commodity price calculation is used.

It has not been modified to see whether the method of Ju is faster.

Ju does not say how he solves the equation for the critical stock price, e.g. Newton method.

He just gives the solution.

The method of BAW gives answers to the same accuracy as in Ju (1999).

Corresponds to the QuantLib MCAmerican Engine.

It uses the Longstaff Schwarz Monte Carlo approach for pricing american options. Web reference available here

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCBarrier Engine.

It uses a Monte Carlo method for pricing barrier options.

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCDigital Engine.

It uses a Monte Carlo method for pricing american style digital options.

In particular, it uses the Brownian Bridge correction for the barrier found in Web reference available here

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCEuropean Engine.

It uses a Monte Carlo method for pricing european options.

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCEuropeanGJRGARCH Engine.

It uses a Monte Carlo GJR-GARCH method for pricing european options.

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCEuropeanHeston Engine.

It uses a Monte Carlo method to implement the Heston stochastic volatility model for pricing european options.

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

Corresponds to the QuantLib MCHestonHullWhite Engine.

It uses a Monte Carlo method to implement the Heston-Hull&White stochastic volatility and interest rates model for pricing european options.

For a general discussion on the Monte Carlo approach click here

This method requires the specification of an object of type Model[Simulation]

[Forthcoming] Deriscope version!Corresponds to a forthcoming QuantLib Trinomial Engine.