The Analytics of a Single-Period Tontine

Sabin, Michael J.; Forman, Jonathan Barry

doi:10.2139/ssrn.2874160

Cited by 14 publications

(17 citation statements)

References 14 publications

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“…The variance of the group gain in the enlarged pool will be reduced by the factor , and the standard deviation by . For a derivation of this result, see Sabin and Forman (2016). So, if we were to double the number of new members added each year in our simulation, we would expect the standard deviation to be reduced by a factor of .…”

Section: Simulation Insightsmentioning

confidence: 91%

“…For this reason, we elect a less complicated method of forfeiture distribution that we feel is much easier for providers to explain and investors to understand. This method, referred to as the "nominal-gain method" in Sabin and Forman (2016), is appealing in that all forfeiture allocations are easily decomposed into two transparent components: 1) a nominal tontine yield for each member, which is easily obtained from the tontine's publicly disclosed mortality table, and 2) a common adjustment factor that accounts for the difference between the amount of forfeitures actually experienced by the pool and the amount that was expected per the mortality table.…”

Section: Forfeiture Allocationmentioning

confidence: 99%

“…That is, there is a bias that favors some members over others. An analysis of this bias is provided in Sabin and Forman (2016). The analysis is complicated, but for our purposes the bottom line is that the bias is negligible in a tontine pool of the size and type we consider for an ITA.…”

Section: Forfeiture Allocationmentioning

confidence: 99%

“…Although modeling it is a challenge that we choose not to tackle here, it is worthwhile nevertheless to show how ITAs behave in the presence of systematic mortality risk. An analytical discussion of the topic is presented in Sabin and Forman (2016). Here, we illustrate it by rerunning our simulation using the same assumptions we made originally except for the rate at which individuals actually die.…”

Section: The Effect Of Systematic Mortality Riskmentioning

confidence: 99%

“…The standard deviation of the group gain is largely unchanged, having decreased only slightly. See Sabin and Forman (2016) for a more thorough discussion of these statistics.…”

Section: Figure 12 Group Gain When Mortality Evolves According To Iarmentioning

confidence: 99%

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Individual Tontine Accounts

2019

JAF

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An individual tontine account (ITA) is similar to a conventional investment brokerage account, but with the added feature of mortality pooling through participation in an open-ended fair tontine. In showing them to be fair to all participants, we envision ITAs as complementary to individual retirement accounts (IRAs), allowing retirees to derive extra income from savings without taking additional investment risk and to obtain lifetime income at a lower cost than with insurance products. ITAs represent an efficient new solution in addressing retirement needs and may help address the "annuity puzzle" by providing a more transparent, lower-cost alternative to insurance-based products.

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Section: Simulation Insightsmentioning

confidence: 91%

Section: Forfeiture Allocationmentioning

confidence: 99%

Section: Forfeiture Allocationmentioning

confidence: 99%

Section: The Effect Of Systematic Mortality Riskmentioning

confidence: 99%

“…The standard deviation of the group gain is largely unchanged, having decreased only slightly. See Sabin and Forman (2016) for a more thorough discussion of these statistics.…”

Section: Figure 12 Group Gain When Mortality Evolves According To Iarmentioning

confidence: 99%

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Individual Tontine Accounts

2019

JAF

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On the unfairness of actuarial fair annuities

Chen¹,

Vanduffel

2023

Decisions Econ Finan

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Actuarial fairness pertains to the situation in which the price of an insurance contract is equal to its expected outcome. We show that actuarial fairness leads to “unfairness” in that annuitants with higher survival rates can choose a better payoff in the sense of second-order stochastic dominance than those with lower survival rates. To deal with this issue, we propose equal utility pricing, i.e., we determine prices such that all contracts have the same (nonlinear) utility from the viewpoint of a third party (e.g., a social planner). This approach is of particular relevance with respect to the design of group self-annuitization schemes.

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