I learnt something called as a Monte Carlo Simulation today. Monte Carlo Simulation stands as a mathematical approach employed to approximate the potential outcomes of events characterized by uncertainty, thereby enhancing decision-making processes.
How do they work?: The mechanism involves constructing a model that gauges the probability of diverse outcomes within a system with unpredictability, owing to the intervention of random variables. Leveraging random sampling, the technique generates numerous potential outcomes and computes the average result.
How to run one?: To initiate a Monte Carlo Simulation, a three-step process is followed:
- Establishment of Predictive Model: Define the dependent variable to be predicted and identify independent variables.
- Probability Distribution of Independent Variables: Utilize historical data to delineate a range of plausible values for independent variables and allocate weights accordingly.
- Iterative Simulation Runs: Conduct simulations iteratively by generating random values for independent variables until a representative sample is obtained, encompassing a substantial number of potential combinations.
The precision of the sampling range and the accuracy of estimations are directly proportional to the frequency of sampling. In essence, a higher number of samples yield a more refined sampling range, consequently enhancing the accuracy of estimations