Monte Carlo simulations involve the creation of a computer-based model into which the variabilities and interrelationships between random variables are entered. A spread of results is obtained when the model is run many times – 100s or 1000s. The method is very useful when the number of random variables is too high making the analysis using ordinary methods very complex.
In finance, we use Monte Carlo simulations to define potential risk. As an example, a mutual fund manager may use the method to manage assets and liabilities to try and establish any downward risk – the risk that liabilities will outgrow the assets leading to a loss.
The method can also be used in project appraisal, where the project manager tries to establish the financial viability of a project. In most cases, there is usually an initial cash outlay followed by subsequent costs during the project’s productive life. The project also generates profit at specified times during the life of the project. If the present value of profit outweighs that of costs, the project is considered as financially feasible. Both profits and costs are likely to be affected by numerous underlying variables which may include interest rate movements, exchange rate fluctuations, technological changes, labor supply costs among others. Monte Carlo simulation is able to incorporate all the variables into a model that can be iterated to highlight all the possible future outcomes of the project. The outcomes are then summarized in terms of probabilities. The least likely outcome and the most likely one can then be deduced.
Monte Carlo Simulation: Steps Involved in Project appraisal
- Create a model of the project and establish all the interdependencies as well as serial correlations between the variables
- Specify the probability for the distribution of each key variable present in the model
- Using random values extracted randomly from the distribution of the variables, simulate the cash flows repeatedly. 100s or 1000s of simulations are usually performed.
- Record and order all the outputs and establish their probability distributions.
From the chart above, we can determine the mean profit, the variance as well as skewness of the distribution.
Nowadays, there exists financial modeling software that can be purchased, specifically designed to carry out such simulations.
Major Applications of Monte Carlo Simulation
- It is used to value projects that require significant amounts of funds and which may have future financial implications on a company
- It can be used to simulate profits or losses in online trading of stocks
- Simulation of the values of assets and liabilities of a pension benefit scheme
- It can also be used to value complex securities such as American/European options.
The limitations of Monte Carlo simulation include:
- It only provides us with statistical estimates of results, not exact figures
- It is fairly complex and can only be carried out using specially designed software that may be expensive.
- The complexity of the process may cause errors leading to wrong results that can be potentially misleading.
Reading 10 LOS 10p:
Explain Monte Carlo simulation and describe its major applications and limitations