🤖 AI Summary
This study addresses the limitations of traditional target-date funds (TDFs), which lack an explicit link to a defined retirement income goal and fail to model risk control at the portfolio level. The authors propose a novel framework centered on an exogenously specified income target, incorporating a time-declining conditional value-at-risk (CVaR) constraint path that enables dynamic asset allocation within a feasible risk set. Two new evaluation metrics—probability of goal attainment and cumulative risk—are introduced. The approach eschews period-by-period optimality assumptions, instead combining stochastic asset allocation sampling with multi-asset backtesting, validated in the context of Chile’s pension reform. Findings reveal that the age at which risk reduction begins is critically important, and that contribution density has a hard lower bound below which investment returns alone cannot compensate for structural underfunding.
📝 Abstract
We propose a framework for designing Target-Date Funds (TDFs) around an explicit return objective while controlling risk directly at the portfolio level through a declining Conditional Value-at-Risk (CVaR) constraint. In this approach, the regulator or sponsor specifies a CVaR glidepath that gives the portfolio manager enough flexibility to reach a target return with a reasonably high probability. The target return is determined exogenously from pension-design inputs such as retirement age, contribution rate, working years, life expectancy, and replacement-rate goals. This differs from conventional TDF design, where age-dependent asset-class limits are set without an explicit link to a required return.
A key feature of the method is that it does not assume the manager selects an optimal portfolio each period. Instead, each month the manager draws an allocation from the set of portfolios satisfying the CVaR constraint. This yields a conservative evaluation of each glidepath: success probabilities are averages over admissible allocations, rather than best-case outcomes. We introduce two figures of merit: the probability of meeting the target return and the cumulative risk assumed over the life of the TDF.
As a proof of concept, we apply the framework to Chile's 2025 pension reform using nine Chilean and global asset classes and a 40-year accumulation horizon. The results show that the transition age at which risk starts to decline is the most consequential design parameter, and that contribution density acts as a hard constraint: below a critical threshold, portfolio design alone cannot compensate for structurally low contributions. The framework is general and can be applied to any TDF designed around an explicit return objective.