Monte Carlo simulation

A Monte Carlo simulation can be used in liquidity risk to simulate a variety of
different scenarios for the portfolio cash flow for a target date (in the future). The
basic concept of a Monte Carlo simulation is to simulate repeatedly a random process
for a financial variable (e.g. interest rates, volatilities etc.) in a given value range of
this variable. Using enough repetitions the result is a distribution of possible cash
flows on the target date.
In order to get a simulation running it is necessary to find a particular stochastic
model which describes the behavior of the cash flows of the underlying position, by
using any or all of the above-mentioned financial variables.
In general the Monte Carlo approach for ECL, we suggest here, is much the same
as that used in the VaR concept. Instead of the consideration of the PV, the focus is
now on the cash flow simulation itself.
Having reached this point it is crucial to find a suitable stochastic model which:
Ω Describes the cash flow behavior of the underlying instrument
Ω Describes the cash flow development of new business (necessary for DCL)
Ω Is not using that many parameters to make computation still efficient
Based on the distribution generated by the Monte Carlo run the following becomes
clear:
Ω The mean of the distribution is a forecast for ECL or DCL
Ω The tails which fulfil a given confidence level (e.g. the 99% quantile in which 99%
of the upcoming cash flows are floating in, the 1% quantile respectively) define
the two limits for the envelope encompassing expected future cash flows.