Which method is commonly used to measure operational risk?

The Loss Distribution Approach (LDA) is a widely accepted method used to measure operational risk within financial institutions. This approach focuses on collecting historical data on losses resulting from operational risks and then modeling the distribution of these losses. By analyzing past events and their severities, LDA allows organizations to estimate potential future losses and the likelihood of various loss scenarios.

One of the strengths of LDA is its reliance on empirical data, which helps in building a more robust understanding of the operational risk profile of an organization. This method not only incorporates frequency and severity of loss events, but it can also consider various risk drivers and external factors influencing operational vulnerabilities.

In contrast, the Mean-Variance Optimization is primarily used for portfolio construction, focusing on the trade-off between risk and return, while Value at Risk (VaR) is a measure that provides an estimate of potential losses in investment portfolios over a specified time frame, rather than directly addressing operational risk. The Capital Asset Pricing Model (CAPM) is used to determine the expected return on an asset based on its systematic risk and is not applicable to assessing operational risk. Therefore, LDA stands out as the most relevant method among the choices for measuring operational risk.