SML Anomalies Explained

This question focuses on interpreting deviations from the Security Market Line in a CAPM setting and asking which kind of empirical anomaly is more consistent with how returns and betas actually behave in data. The candidate must reason about how average realized returns could systematically lie above or below the theoretical linear relationship implied by CAPM, while still starting at the risk-free rate and remaining upward sloping. It tests the ability to connect the geometry of the SML in expected return–beta space with realistic cross-sectional patterns in asset returns observed in practice.

To answer well, a candidate needs comfort with CAPM equilibrium logic, beta estimation, and how empirical "flattening" or "steepening" of the return–beta relationship reflects violations of the model's assumptions. It leans on understanding additional priced factors, mispricing, or investor constraints that can alter the slope or level of the SML. Interviewers watch for clear identification of which assumptions fail in each scenario: completeness of diversification, single-factor pricing, homogeneous expectations, frictionless markets, or correct measurement of the market portfolio and risk premium. They also look for disciplined empirical reasoning rather than ad hoc storytelling.

What it tests

The core structure of CAPM-type problems is the mapping between systematic risk (as measured by `beta`) and expected return, assuming all relevant risk is captured by a single market factor. The Security Market Line (SML) is a direct consequence of this: under the model's assumptions, every asset's expected return is a linear function of its `beta`, with the intercept at the risk-free rate and the slope equal to the market risk premium. This linearity arises because, in equilibrium, only non-diversifiable (market) risk is rewarded, and all investors agree on the risk and return characteristics of all assets. If empirical data deviate from this line, it signals either a breakdown in these assumptions—such as the presence of additional priced risks, heterogeneous beliefs, or market frictions—or a misestimation of the market risk premium itself. The SML's shape thus encodes the market's consensus about risk pricing, and any systematic deviation points to a deeper structural issue in the model's assumptions or in the market's functioning.