12. Monte Carlo Simulation
q. explain Monte Carlo simulation and describe its applications and limitations;
r. compare Monte Carlo simulation and historical simulation.
What is a Monte Carlo Simulation?
Monte Carlo simulation involves trying to simulate the conditions that apply to a specific problem by generating a large number of random samples using a random number generator on a computer.
Where does the name "Monte Carlo simulation" derive from?
It comes from the idea of generating a large number of random samples, such as might occur in the Monte Carlo Casino.
What is the Monte Carlo simulation used for?
- It allows us to experiment with a proposed policy and assess the risks before actually implementing it.
- It is used to develop Value at Risk (VAR) to estimate the probability that portfolio losses exceed a predefined level.
- It is used to value complex securities such as European options and mortgage-backed securities with complex embedded options
- Researchers use it to test their models and tools
How are numbers generally picked for the Monte Carlo Simulation?
Generally, a historical record of returns (or other underlying variables) are used because they provide direct evidence of distributions. A drawback is that any outcome which is not in the historical (such as a stock market crash or black swan events) will not be included.