A Monte Carlo Simulation (MCS) consists of executing a model using random variable inputs. The following note describes versions of the compound interest factor models suitable for MCS and some techniques for generating random variables.
It is also usual to summarize the results usuing the statistical techniques. Versions of some of these techniques are also given.
You should be familiar with the Compound Interest Mmodel before proceeding with the material below.
The set of Compound interest functions described in MYSYS TVX and from the UTILS [f] file are designed to match each value of i with each value of n. This produces arrays of the number of i by the number of n.
The following set of corresponding functions matches the i and n values in pairs which is suitable for simulation.`
You may define the functions that you wish to use by keying [Enter] on the first line of the fn and continuing to key [Enter] on each new line until definition is complete. Note you will get a DEF ERROR if the fn is already in the ws.
There are many techniques for generating suitable random variable values. The direct method using ? is shown below. Another method based on a table of values is used in the fn RISK. See file 'x57' for versions of the some standard distribution functions. Key [Enter] on following line to view 'x57': LESSON 'x57'`
Remember that the above proceedures generate variables with many values and if you intend to save this workspace then you may wish to erase these large variables or reassign them to sigletons.
End to date, ams 990713