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Record W3134155837 · doi:10.1017/s1748499521000051

Evaluation of equity-linked products in the presence of policyholder surrender option using risk-control strategies

2021· article· en· W3134155837 on OpenAlex
Patrice Gaillardetz, Saeb Hachem, Mehran Moghtadai

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

VenueAnnals of Actuarial Science · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicStochastic processes and financial applications
Canadian institutionsTD Bank GroupConcordia University
Fundersnot available
KeywordsSurrenderEquity (law)EconomicsMoneynessActuarial scienceControl (management)Product (mathematics)Financial economicsBusinessMicroeconomicsManagementPolitical scienceMathematics

Abstract

fetched live from OpenAlex

Abstract Throughout the past couple of decades, the surge in the sale of equity-linked products has led to many discussions on the evaluation and risk management of surrender options embedded in these products. However, most studies treat such options as American/Bermudian style options. In this article, a different approach is presented where only a portion of the policyholders react optimally due to the belief that not all policyholders are rational. Through this method, a probability of surrender is obtained based on the option moneyness and the product is partially hedged using local risk-control strategies. This partial hedging approach is versatile since few assumptions are required for the financial framework. To compare the different surrender assumptions, the initial capital requirement for an equity-linked product is obtained under a regime-switching equity model. Numerical examples illustrate the dynamics and efficiency of this hedging approach.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.387

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.293
GPT teacher head0.397
Teacher spread0.104 · 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