Measuring the Benefits of Dynamic Asset Allocation Strategies in the Presence of Liability Constraints

The recent pension crisis has triggered a fierce debate in most developed countries between advocates of a tighter regulation designed to provide explicit incentives for pension funds to increase their focus on risk management, and those arguing that imposing short-term funding constraints and solvency requirements on such long-term investors would only increase the cost of pension financing.


Lionel Martellini

professor of finance at EDHEC Business School and scientific director of the EDHEC Risk and Asset Management Research Centre.

Vincent Milhau

Research Engineer at the EDHEC Risk and Asset Management Research Centre.

We analyse this question in the context of a formal continuous-time dynamic asset allocation model for an investor facing liability commitments subject to inflation and interest rate risks. In an empirical exercise, we find that the presence of short-term funding ratio constraints indeed involves a positive welfare cost, but that cost is not found to be prohibitive for reasonable parameter values. Recognising that the presence of minimum funding ratio constraints, whether desirable or not, should affect the optimal allocation policy, we then provide the formal solution to the asset allocation problem in the presence of such constraints. We compare these risk-controlled strategies to unconstrained allocation strategies coupled with additional contributions, and find that the latter involve severe welfare costs in the presence of irreversible contributions and regulatory short-termism, especially when marginal utility decreases sharply beyond a given threshold. In essence, we show that risk-management strategies can turn reversible contributions and short-term constraints into irreversible contributions and long-term constraints. Overall, our results suggest that it is not so much the presence of short-term funding ratio constraints that is in itself costly for pension funds as their reluctance to implement risk-management strategies that are optimal given such regulatory constraints.

Type: EDHEC Publication
Date: le 26/05/2009
Research Cluster : Finance

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