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Using Monte Carlo to Uncover Hidden Risk
- How did Monte Carlo simulation get its name?
Monte Carlo simulation was named for Monte Carlo, Monaco, where the primary attractions are casinos containing games of chance. Games of chance such as roulette, dice, and cards exhibit random behavior.
The random behavior in games of chance is similar to how Monte Carlo simulation selects variable values at random to simulate a model. When you roll a die, you know a 1, 2, 3, 4, 5, or 6 will come up, but you don't know which for any particular roll. It's the same with the variables that have a known range of values but an uncertain value for any particular time or event (e.g. interest rates, staffing needs, stock prices, inventory, and phone calls per minute).
- How do Monte Carlo simulations work?
Monte Carlo simulations can be used in various ways. A typical Monte Carlo simulation will analyze historical data to determine a probability distribution. Once the program has this data, it can then create random data points based on the probability distribution. These random data points are returned to the user to be analyzed as out of sample data.
- How do Monte Carlo simulations apply to trading?
Monte Carlo simulations are typically used in trading to help assess risk. Generally a sample of returns (Trade P&L or daily P&L) is used to generate a probability distribution. This distribution is then used to create hundreds, if not thousands of simulated trades. These trades can then be analyzed to see if there was any abnormal drawdown during the simulation.
Notes and references
- http://www.decisioneering.com/monte-carlo-simulation.html
See also
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