What is a defining feature of a stochastic model?

A defining feature of a stochastic model is the introduction of variability through repeated iterations. This type of model incorporates randomness and uncertainty, allowing it to simulate a range of possible outcomes based on varying input assumptions. By running multiple iterations, a stochastic model can account for different potential scenarios and their probabilities, providing a more comprehensive view of the risks and rewards associated with a particular situation or investment.

In contrast to deterministic models, which rely on fixed assumptions for predictable results, stochastic models embrace uncertainty, making them particularly useful in fields like finance and risk management where outcomes can significantly fluctuate. This variability provides stakeholders with insights into potential variability in projections, helping them to make informed decisions that take into account the spectrum of possible future states rather than a single, fixed outcome.

This characteristic allows analysts to better understand the likelihood of different scenarios occurring, which can greatly influence strategic planning and risk assessment.