simulateDataToHorizon: Simulate prices to horizon based on fitted marginal...

In erolbicero/propfolio: Propfolio Management

Description

Simulate prices to horizon based on fitted marginal distributions and copula - using Meucci's methods

Usage

simulateDataToHorizon(numSimulations, numPeriodsForward, vineCopulaFit,
  signalMarginalFit, residualMarginalFit,
  eigenVectors = diag((length(signalMarginalFit) +
  length(residualMarginalFit))))

Arguments

numSimulations	is a scalar dictating number of simulations (rows) to conduct
numPeriodsForward	is a scalar dictating number of periods forward (columns) the investment horizon is
vineCopulaFit	is a vine copula object
signalMarginalFit	is a list of marginal distribution fits for the signal risk factors
residualMarginalFit	is a list of marginal distribution fits for the noisy risk factors
eigenVectors	is a matrix of eigenVectors used to convert the horizon risk factors back into invariants

Value

a matrix of invariants projected to the investment horizon - to then be used in the pricing function

Examples

none

erolbicero/propfolio documentation built on May 16, 2019, 8:48 a.m.