Briefly

Increasingly simulation is being joined together with time value calculations to evaluate high risk projects such as mine sites and major projects. We examine all of the major concepts in this workshop and the principle components of Monte Carlo simulation. The workshop includes developing a simulation version of the case study developed in Workshop 4. Included is a brief look at the simulation third party Add-in @RISK which aids the use of the technique. Make sure you understand uncertainty as probability before tackling this one.

Detailed Outline - A full one day workshop                                      

For Whom:
Professionals using Excel in decision making environments with a particular interest in developing models with uncertain variables and multiple outcomes. Participants should want an understanding of Monte Carlo simulation to a variety of financial modelling situations, since the principles can be applied to any business environment with uncertain financial outcomes and quantifiable risk assessment.

Assumed expertise:
Applicants should be competent in Excel 2002/3 with a good understanding of functions and arguments, and NPV concepts. A clear if basic understanding of the measurement of uncertainty as a probability distribution is assumed though participants will be using Excel’s functions to replace any tedious statistics. Macros may be used in this workshop’s examples, but they are given, macro knowledge is not required.   

Detail:
The workshop begins by focussing on the basic principles of the Monte Carlo technique before applying Excel’s simulation features to an investment appraisal model. We then:

- Establish the structure of an investment appraisal model using uncertain variables - defining the variables - define the uncertain nature of those variables.

- Use Excel’s functions to create variable values from distributions - the most common distributions used in financial models - the discrete or continuous approximates to reality.

- Consider random sequences in Monte Carlo which are included in using an asset valuation model with Excel in manual iteration mode.

- Illustrate cumulative probability functions using Excel functions to create variable values are illustrated.

- Use Excel’s random generator features within the context of an uncertain environment, recording the Monte Carlo outcomes to create significant values. (Single and multi-variable simulation, dependent and independent variables).

- Create the reports for decision makers - critical variables.

- ‘Financial Planning’ with Monte Carlo - asset values at risk considering re-alignment of funding to assets and the asset ‘mix’ using independent uncertain variables. (The example here includes a macro).

- Using an adaption of Monte Carlo (Queuing) to evaluate resource use including manning levels.

- Case Study - mine feasibility study (same as Workshop 4) using simulation on the key variables.