Joint Implied Willow Tree: An Approach for Joint S&P 500/VIX Calibration
Bibliographic record
Abstract
ABSTRACT Since the inception of Volatility Index (VIX) options trading, academic literature has persistently sought accurate methods for jointly calibrating the prices of the S&P 500 index (SPX) and VIX options. This study introduces a novel nonparametric approach, called the joint implied willow tree (JIWT) method, aimed at resolving this joint calibration challenge. The resulting willow tree adheres to the martingale constraint for the SPX and ensures that the VIX is derived as the implied volatility of a 30‐day log contract on the SPX. A notable advantage of our method is its ability to recover not only the unconditional probabilities for a fixed maturity but also the conditional probabilities across different maturities. Consequently, we reconstruct the entire term structure of the SPX, aligning it with market information from both SPX and VIX options. Numerical and empirical analyses demonstrate that the JIWT method excels in accurately capturing the volatility smile of SPX and VIX across various maturities.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".