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Record W2184131131

Pricing Interest Rate Derivatives under Multi-Factor GARCH

2012· article· en· W2184131131 on OpenAlexaff
Xiaofei Li, Nabil Tahani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Risk and Volatility Modeling
Canadian institutionsYork University
Fundersnot available
KeywordsCouponBondMonte Carlo methodEconometricsInterest rateShort rateRange (aeronautics)Zero-coupon bondMathematicsComputationYield curveYield (engineering)EconomicsFourier transformBond valuationVariance (accounting)StatisticsFinanceAlgorithmMathematical analysisEngineeringPhysics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents semi-closed-form solutions to a wide range of interest rate derivatives, such as options on discount bonds and on coupon bonds, options on the short rate, options on yield spreads and on a basket of yields. A multi-factor GARCH framework of the short rate and its variance components is considered. We define a generalized zero-coupon bond and derive the moment generating function (MGF) of the discount bond log-price. The solution method relies on Fourier-inverting the MGF to compute the cumulative probabilities. The solution is found very accurate and offers considerable savings in computation time when compared to Monte Carlo simulation.

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)0.003
metaresearch head score (Gemma)0.011
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.206
GPT teacher head0.299
Teacher spread0.093 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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