The Growth and Performance of Artificial Intelligence in Asset Management
The Growth and Performance of Artificial Intelligence in Asset Management
We use Target Date Funds (TDFs) to study how managers of funds behave when shielded from their investors' short-term needs. We document that asset managers exploit reduced investor attention to deliver lower performance quantifiable in 21% for an average investor holding the fund for 50 years. This underperformance is driven by fund families using TDFs to smooth the flow shocks of affiliated open-end funds and to boost fees by investing in the affiliated expensive share classes. We use the Pension Protection Act of 2006 as an exogenous shock that made TDFs the default investment option within 401(k) retirement plans.
We use Target Date Funds (TDFs) to study how managers of funds behave when shielded from their investors' short-term needs. We document that asset managers exploit reduced investor attention to deliver lower performance quantifiable in 21% for an average investor holding the fund for 50 years. This underperformance is driven by fund families using TDFs to smooth the flow shocks of affiliated open-end funds and to boost fees by investing in the affiliated expensive share classes. We use the Pension Protection Act of 2006 as an exogenous shock that made TDFs the default investment option within 401(k) retirement plans.

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