Pricing vulnerable options with constant elasticity of variance versus stochastic elasticity of variance
Why this work is in the frame
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Bibliographic record
Abstract
In order to handle option writer’s credit risk, a different underlying price model is required beyond the well-known Black-Scholes model. This paper adopts a recently developed model, which characterizes the 2007-2009 global financial crisis in a unique way, to determine the no-arbitrage price of European options vulnerable to writer’s default possibility. The underlying model is based on the randomization of the elasticity of variance parameter capturing the leverage or inverse leverage effect. We obtain an analytic formula explicitly for the stochastic elasticity of variance correction to the Black-Scholes price of vulnerable options and show how the correction effect is compared with the one given by the constant elasticity of variance model. The result can help to design a dynamic investment strategy reducing option writer’s credit risk more effectively.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it