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Record W3166297865 · doi:10.1002/fut.22214

Valuation of bitcoin options

2021· article· en· W3166297865 on OpenAlexaff
Melanie Cao, Batur Celik

Bibliographic record

VenueJournal of Futures Markets · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicStochastic processes and financial applications
Canadian institutionsYork University
Fundersnot available
KeywordsValuation (finance)EconomicsCurrencyMoneynessValuation of optionsAsian optionOption valueDividendBlack–Scholes modelMonetary economicsFinancial economicsMicroeconomicsFinance

Abstract

fetched live from OpenAlex

Abstract We propose an equilibrium valuation model for bitcoin options by extending Cao. Bitcoin is interpreted as a foreign currency in a small open economy where money supply and aggregate dividend are exogenous. The equilibrium bitcoin prices increase with diffusive and jump risks of these two exogenous factors. Analytical option pricing formulas are obtained with Merton's model as a special case. Static analysis reveals that a bitcoin call (put) option value increases (decreases) with the money supply growth rate. Numerical analysis shows that all risks lead to a positive premium in option prices relative to the Black–Scholes model.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.244
Teacher spread0.211 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2021
Admission routes1
Has abstractyes

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