B is correct. Alexa is indeed encountering selection bias in both active and passive funds, along with a look-ahead bias in passive funds. In the case of active funds, the exclusion of funds that closed due to poor performance represents a clear example of selection bias or survivorship bias. By omitting these underperforming funds, the dataset becomes skewed towards more successful active funds, potentially leading to an overestimation of their performance.

Similarly, in the context of passive funds, selecting only those funds that have recently outperformed the market introduces both selection bias and a look-ahead bias. The selection bias arises because only the outperforming funds are included, ignoring the underperforming ones that might have been removed or terminated. Simultaneously, there's a look-ahead bias because the decision to include these funds is based on future information (their recent outperformance) that would not have been available at the time of the actual investment.

A is incorrect because Alexa is facing selection bias in active funds, not look-ahead bias. Similarly, in passive funds, she is dealing with look-ahead bias, not selection bias.

C is incorrect because Alexa is not dealing with look-ahead bias in both fund types. She is encountering selection bias in both, and look-ahead bias in passive funds.

D is incorrect because Alexa is not encountering look-ahead bias in both fund types. She is dealing with selection bias in both, and look-ahead bias in passive funds.

Things to Remember

• "Selection bias" refers to situations where the data sample is not representative of the entire population. For instance, excluding poorly performing active funds from the analysis can overstate the overall performance, presenting a distorted view of reality.