Monte Carlo analysis gives you an excellent view of how robust your strategy is and how it is vulnerable to changes in the conditions of the market.
Monte Carlo analysis (or simulation) is a technique that gives you a better view of the profitability and vulnerability of your strategy: thus you find out if your strategy really works and if it has the potential to be profitable in the future, or if it’s overoptimized and can easily fail in real trading.
Why would you use Monte Carlo analysis?
Historical results of the strategy give us an idea, how the strategy behaved in the past and to some extent certain expectations for the future. However, the market can change in the future and therefore it’s necessary to measure how the strategy is vulnerable to changes such as market cycles, sequence of transactions, etc. To do this, Monte Carlo analysis is used. It helps us get the realistic idea of what we can expect from the strategy.
How does the Monte Carlo analysis work?
The main principle of the Monte Carlo analysis is that many simulations are run, each time with a small change. The more simulations we run, the more reliable results we get.
Extension of Monte Carlo simulations
Every Monte Carlo simulation is created by means of a simple snippet.
If you have programming skills, you can use QuantEditor to create your own conditions for Monte Carlo simulation.