Module net.finmath.lib
Package net.finmath.montecarlo.interestrate.models.covariance

Class LIBORCovarianceModelStochasticVolatility

java.lang.Object
net.finmath.montecarlo.interestrate.models.covariance.AbstractLIBORCovarianceModel
net.finmath.montecarlo.interestrate.models.covariance.AbstractLIBORCovarianceModelParametric
net.finmath.montecarlo.interestrate.models.covariance.LIBORCovarianceModelStochasticVolatility
All Implemented Interfaces:
Serializable, LIBORCovarianceModel, LIBORCovarianceModelCalibrateable
public class LIBORCovarianceModelStochasticVolatility
extends AbstractLIBORCovarianceModelParametric
Simple stochastic volatility model, using a process \[ d\lambda(t) = \nu \lambda(t) \left( \rho \mathrm{d} W_{1}(t) + \sqrt{1-\rho^{2}} \mathrm{d} W_{2}(t) \right) \text{,} \] where \( \lambda(0) = 1 \) to scale all factor loadings \( f_{i} \) returned by a given covariance model. The model constructed is \( \lambda(t) F(t) \) where \( \lambda(t) \) is the (Euler discretization of the) above process and \( F = ( f_{1}, \ldots, f_{m} ) \) is the factor loading from the given covariance model. The process uses the first two factors of the Brownian motion provided by an object implementing BrownianMotion. This can be used to generate correlations to other objects. If you like to reuse a factor of another Brownian motion use a BrownianMotionView to delegate \( ( \mathrm{d} W_{1}(t) , \mathrm{d} W_{2}(t) ) \) to a different object. The parameter of this model is a joint parameter vector, consisting of the parameter vector of the given base covariance model and appending the parameters ν and ρ at the end. If this model is not calibrateable, its parameter vector is that of the covariance model, i.e., ν and ρ will be not part of the calibration. For an illustration of its usage see the associated unit test.
Version:
1.0
Author:
Christian Fries
See Also:
Serialized Form