What is a key objective of mean-variance portfolio optimization?

• A. To ignore statistical modeling
• B. To maximize returns with any level of risk
• C. To find the most efficient asset allocation
• D. To focus on survivor bias in the dataset

Answer: (C)

A key objective of mean-variance portfolio optimization is to find the most efficient asset allocation. The mean-variance framework, developed by Harry Markowitz, focuses on constructing a portfolio that maximizes returns for a given level of risk or minimizes risk for a given level of expected return. In doing so, it evaluates the trade-off between risk (typically measured by the variance of returns) and return.

The efficient frontier, which is a core concept in mean-variance optimization, visually represents the optimal combinations of risk and return, allowing investors to select a portfolio that aligns with their risk tolerance and investment objectives. This method emphasizes diversification and the correlation between assets, enabling investors to achieve a more favorable risk-return profile through careful asset allocation.

The other options illustrate concepts that do not align with the primary objective of mean-variance optimization. Ignoring statistical modeling would contradict the analytical nature of the framework, maximizing returns with any level of risk fails to acknowledge the inherent trade-offs involved, and focusing on survivor bias diverts attention from the core goal of optimizing the risk-return relationship in portfolio construction.