Cumulative prospect theory and deferred annuities

Anran Chen (Faculty of Actuarial Science and Insurance, Cass Business School, London, UK)
Steven Haberman (Faculty of Actuarial Science and Insurance, Cass Business School, London, UK)
Stephen Thomas (Faculty of Actuarial Science and Insurance, Cass Business School, London, UK)

Review of Behavioral Finance

ISSN: 1940-5979

Publication date: 12 August 2019



Although it has been proved theoretically that annuities can provide optimal consumption during one’s retirement period, retirees’ reluctance to purchase annuities is a long-standing puzzle. The purpose of this paper is to use behavioral model to analyze the low demand for immediate annuities.


The authors employ cumulative prospect theory (CPT), which contains both loss aversion and probability transformations, to analyze the annuity puzzle.


The authors show that CPT can explain the unattractiveness of immediate annuities. It also shows that retirees would be willing to buy a long-term deferred annuity at retirement. By considering each component from CPT in turn, the loss aversion is found to be the major reason that stops people from buying an annuity while the survival rate transformation is an important factor affecting the decision of when to receive annuity incomes.


This paper identifies CPT as one of the reasons for the low demand of immediate annuities. It further suggests that long-term deferred annuities could overcome behavioral obstacles and become popular among retirees.



Chen, A., Haberman, S. and Thomas, S. (2019), "Cumulative prospect theory and deferred annuities", Review of Behavioral Finance, Vol. 11 No. 3, pp. 277-293.

Download as .RIS



Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

Please note you might not have access to this content

You may be able to access this content by login via Shibboleth, Open Athens or with your Emerald account.
If you would like to contact us about accessing this content, click the button and fill out the form.
To rent this content from Deepdyve, please click the button.