The impact of behavioral factors on annuitisation decisions and decumulation strategies

The ongoing shift from Defined Benefit (DB) pension plans to Defined Contribution (DC) pension plans in private sectors has transferred investment risk and longevity risk from pension providers to individuals. Professional advice on how to best generate retirement incomes from accumulated pension savings is therefore in great demand. A common solution is buying an immediate annuity; however the immediate annuity market has long been experiencing low demand. Another solution is following a safe drawdown rate during retirement; however this exposes retirees to the risk of outliving their pension savings. In recent years, behavioral factors have been successful in explaining individuals’ decision-making process, this thesis is therefore devoted to the investigation of the low demand of immediate annuities by considering behavioral models; and the use of annuity products in optimal decumulation strategy designs. This thesis has two major contributions. First, both Cumulative Prospect Theory (CPT) and Hyperbolic discount model can explain the low demand of immediate annuities and suggest that people would be willing to purchase deferred annuities. This has laid a research foundation for introducing and promoting the deferred annuity product. Second, we provide an optimal partial annuitisation strategy involving deferred annuities in a utility maximisation decumulation plan. In the proposed strategy the retirement period is divided into two stages: a stage where pensioners use their savings to cover their living expenses and a second stage where a payment stream from deferred annuities is available. This strategy effectively helps retirees manage the longevity risk at advanced ages and turns the drawdown plan from accumulated savings into an easier decision than before – because of a fixed rather than unknown drawdown period.

Name dc:type.qualificationname

phd

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

City, University of London

Year dc:date.issued

2017

Author dc:creator

• Chen, A.

• HD61 Risk Management