Complete Guide on Monte Carlo Simulation

Monte Carlo Simulation is an important statistical method used extensively in several fields including quantitative finance like the CAPM (Capital Asset Pricing Model).

What is Monte Carlo Simulation?
It is a computerized mathematical technique that allows people to account for risk in quantitative analysis and decision making. It is used to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables.

Why is it important?
It provides a range of possible outcomes and the probabilities they will occur for any choice of action. This provides decision makers with a risk assessment detailing each potential decision.

How does it work?
It relies on random sampling and statistical results. During simulation, the mathematical model is run many times, each time using a different set of random values from the probability functions that frames them.

How to Answer Questions on Monte Carlo Simulation in an exam?
1. Understand the basics of Monte Carlo Simulation, its applications, and how it works in real scenarios.
2. Practice questions to understand how to apply the theory in practical situations.
3. Diagrams can often explain the subject matter simply and effectively.
4. Understand the pros and cons of using a Monte Carlo Simulation.

Exam Tips: Answering Questions on Monte Carlo Simulation
1. Provide a clear definition and explain its purpose.
2. Use examples wherever possible to demonstrate your understanding.
3. Introduce the concept of how randomness is incorporated into the model in a real world scenario.
4. Discuss the limitations, such as the reliance on the quality of the input, and how it affects the output.
5. Address the computation requirements and how modern technology has made it easier to use this method.