Simulate Cox-Ingersoll-Ross sample paths with transition density
[
simulates Paths
,Times
] = simByTransition(MDL
,NPeriods
)NTrials
sample paths of NVars
independent state variables driven by the Cox-Ingersoll-Ross (CIR) process sources
of risk over NPeriods
consecutive observation periods.
simByTransition
approximates a continuous-time CIR model
using an approximation of the transition density function.
[
specifies options using one or more name-value pair arguments in addition to the
input arguments in the previous syntax.Paths
,Times
] = simByTransition(___,Name,Value
)
Use the simByTransition
function to simulate any vector-valued CIR
process of the form
where
Xt is an
NVars
-by-1
state vector of process
variables.
S is an
NVars
-by-NVars
matrix of mean
reversion speeds (the rate of mean reversion).
L is an
NVars
-by-1
vector of mean
reversion levels (long-run mean or level).
D is an
NVars
-by-NVars
diagonal matrix,
where each element along the main diagonal is the square root of the
corresponding element of the state vector.
V is an
NVars
-by-NBrowns
instantaneous
volatility rate matrix.
dWt is an
NBrowns
-by-1
Brownian motion
vector.
[1] Glasserman, P. Monte Carlo Methods in Financial Engineering. New York: Springer-Verlag, 2004.