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Record W3143864647 · doi:10.1002/fut.22191

Smile‐implied hedging with volatility risk

2021· article· en· W3143864647 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 Futures Markets · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicStochastic processes and financial applications
Canadian institutionsWestern UniversityHEC Montréal
Fundersnot available
KeywordsImplied volatilityVolatility smileStochastic volatilityGreeksVolatility (finance)Variance swapEconometricsVolatility riskVolatility swapSABR volatility modelForward volatilityEconomicsRisk managementFinancial economicsFinance

Abstract

fetched live from OpenAlex

Abstract Options can be dynamically replicated using model‐free Greeks extracted from the volatility smile. However, smile‐implied delta and delta–gamma hedging do not achieve minimum variance in the presence of price–volatility correlation, and these strategies have shown poor performance relative to the Black–Scholes (BS) benchmark. We propose a way to extend smile‐implied option replication with volatility risk management. Large‐scale evidence on S&P 500 index options indicates that smile‐implied delta–gamma–vega hedging strategies outperform the BS approach as well as more sophisticated option hedging frameworks, including stochastic volatility and jumps.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.707
Threshold uncertainty score0.357

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.011
GPT teacher head0.200
Teacher spread0.189 · 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