Which of the following is NOT one of the dynamic risk exposure models?

The choice of standard deviation analysis as the correct answer is grounded in the distinction between risk exposure models and statistical methods used to measure or analyze risk. Dynamic risk exposure models are specifically designed to assess how risk exposure can change over time and consider various factors that could contribute to these changes. They often employ regression techniques to understand relationships and make predictions based on historical data.

Standard deviation analysis, however, is a statistical measure that quantifies the amount of variation or dispersion in a set of values. While it plays a crucial role in risk assessment by providing insight into the volatility of returns, it does not serve as a dynamic risk exposure model. It is more of a descriptive statistic that does not inherently incorporate dynamic changes or the complexities of risk exposure over time like the other options listed.

In contrast, the dummy variable regression, quadratic curve regression model, and separate regressions model are forms of regression analysis that can account for changing relationships in a dataset and can include various factors that capture dynamic risks. Thus, standard deviation analysis stands out as the method that does not fit within the framework of dynamic risk exposure models.