Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility¶
Bibliographic record. Follow the original-source link for the publication.
| Field | Value |
|---|---|
| Primary domain | Volatility |
| Other domains | — |
| Methods | Financial Ml, Research Methods |
| Facets | — |
| Authors | Julia Sun, Zheyu Jin, Jiawei Zhang, Jeffrey D. Varner |
| Published | 2026-05-13 |
| Source | arXiv Quantitative Finance History |
| Identifiers | arxiv:2605.13998 |
| URL | Open original source |
Editorial synthesis¶
Why it matters¶
This work addresses the circular dependency between implied-volatility and option prices by generating implied volatility from a structural return model, which is relevant for synthetic data quality and coherent risk-testing pipelines. (abstract:S1, abstract:S2, abstract:S3, abstract:S4, abstract:S5, abstract:S6, abstract:S7, abstract:S8)
Main author claims¶
- The authors claim synthetic data generation breaks circularity by deriving implied-vol paths from Jump-HMM return paths through a modified Heston process and pricing American options with a recombining binomial lattice. (
abstract:S1,abstract:S2,abstract:S3) - They claim smile, skew, and term structure emerge without external calibration, with a hierarchical parametric+shared+sector neural surrogate for multi-sector ladders and event-driven generalization in temporal holdout. (
abstract:S4,abstract:S5,abstract:S6,abstract:S7) - The authors report joint simulation of path-conditional implied volatility, finite-difference American Greeks, and terminal short-premium PnL on real near-the-money options, followed by a second-underlying robustness run; the implementation is released as an open-source Julia package. (
abstract:S7,abstract:S8)
Data, method, or discussion scope¶
Scope includes the broken-circularity claim, Jump-HMM and modified Heston pipeline, hierarchical calibration (parametric + neural surrogates), temporal holdout findings, and the open-source Julia package statement. (abstract:S1, abstract:S2, abstract:S3, abstract:S4, abstract:S5, abstract:S6, abstract:S7, abstract:S8)
Main limitations¶
The pipeline depends on state, mood and surrogate design assumptions with limited reproducible specification, making risk diagnostics and failure-mode tracing harder. (abstract:S3, abstract:S5, abstract:S7)
Relationships¶
- None recorded.