Finding 7768Emerging EvidenceValidation V0
This paper discretizes a 4-factor path-dependent volatility model, allowing non-Gaussian innovations and practical hedging alignment, and links $P$ and $Q$ calibration. It proposes a Gaussian-mixture matched via Hellinger to Student-$t$, and a hybrid $P$--$Q$ estimation. Strong SPX/VIX fits, including joint smiles, and superior $P$-measure MLE deliver practitioner-relevant value, plus robustness.
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Supporting86% linkage confidence
This paper discretizes a 4-factor path-dependent volatility model, allowing non-Gaussian innovations and practical hedging alignment, and links $P$ and $Q$ calibration. It proposes a Gaussian-mixture matched via Hellinger to Student-$t$, and a hybrid $P$--$Q$ estimation. Strong SPX/VIX fits, including joint smiles, and superior $P$-measure MLE deliver practitioner-relevant value, plus robustness.
key_findings bullet 4 · key_findings
Inspect source: The Discrete-Time 4-Factor Path-Dependent Volatility Model: Calibration under P and Q →This Finding was extracted from the configured corpus. It is versioned, traceable, and may evolve through editorial review or new corpus evidence.