What can simulation techniques help assess in risk management?

Simulation techniques in risk management are powerful tools that allow analysts to model and evaluate the uncertainty and variability in financial outcomes. By using simulations, practitioners can generate a wide range of potential outcomes based on the input variables, which often follow probability distributions.

Choosing the standard deviation of forecast Net Present Values (NPVs) as the correct answer reflects the primary function of simulation techniques in assessing risk. When you simulate a financial model numerous times, each simulation can yield different NPVs due to variations in assumptions, inputs, and external factors. By analyzing the resulting distribution of NPVs from these simulations, one can calculate key statistical measures, including the average NPV and its standard deviation. The standard deviation, in particular, provides insights into the level of risk associated with the investment: a higher standard deviation indicates greater variability and, consequently, higher risk.

Simulation does not limit assessments to just the most likely outcomes—it encompasses a spectrum of possible scenarios, including those that are less probable but potentially impactful. Moreover, simulation techniques do not guarantee exact outcomes of investments; rather, they illustrate a range of possible future scenarios based on modeled inputs and assumptions.

Therefore, the ability of simulation techniques to calculate the standard deviation of forecast NPVs makes it an invaluable method for understanding the risks