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Record W3172456216 · doi:10.1111/jori.12345

High‐water mark fee structure in variable annuities

2021· article· en· W3172456216 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Risk & Insurance · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicClimate Change Policy and Economics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnnuityVariable (mathematics)Actuarial scienceEconomicsWelfareEconometricsLife annuityVariablesFinancePensionStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract This paper proposes a novel high‐water mark fee structure and investigates its impact on the marketability of variable annuities. To evaluate the welfare effects of holding a variable annuity, we adopt mean‐variance analysis. By also examining the welfare effects of holding two alternative investments, we introduce a quantitative measure, namely a compatible set of risk aversions, to assess the marketability of the variable annuity under a certain fee structure. Comparing the compatible sets and the welfare effects of holding the variable annuity under the high‐water mark fee structure with those under a constant and a state‐dependent fee structure, we find that the high‐water mark fee structure improves the variable annuity's marketability in two aspects: First, it makes the variable annuity preferable to the alternative investments for a broader range of policyholders. Second, when the variable annuity is preferred over the alternative investments, it produces the highest welfare for the policyholder.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.208
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it