modelDynamics: Jump-diffusion model dynamics

In piotrek-orlowski/divergenceModelR: Divergence pricing and divergence-based affine model estimation

Description

This function creates mean and covariance structures that can be passed to linCombMean to combine into an estimate of the conditional first and second (cross-)moments of the stock return and volatility factors.

Usage

modelDynamics(params.P, params.Q, dT = 5/252, rtol = 1e-14,
  N.factors = 3, N.points = 2,
  jumpTransform = getPointerToJumpTransform("expNormJumpTransform")$TF,
  mod.type = "standard", ...)

Arguments

params.P	parameter list
params.Q	parameter list risk-neutral
dT	The Time horizon
rtol	The relative tolerance required in the integration
N.factors	The number of stochastic vol factors assumed.
N.points	Number of points in sparse grid quadratures. 2 usually works pretty good, more than 3 is overkill.
jumpTransform	pointer to jump trasform c++ function
mod.type	character, 'standard' or 'casc.vol'

Value

Returns 2 lists and a matrix.

piotrek-orlowski/divergenceModelR documentation built on July 21, 2020, 11:51 a.m.