A Jump-HMM-driven modified Heston model generates synthetic implied volatility surfaces and American option prices directly from simulated equity return paths, breaking the circular dependency on market-derived volatility.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4representative citing papers
PPAT residualizes losses via a prediction-powered control variate inside LURE, yielding lower-variance unbiased risk estimates, tailored acquisition, and asymptotic CIs that cover with fewer labels.
Framework combining Wiener Chaos Expansion, Malliavin Calculus, and adaptive importance sampling achieves 839-2516x variance reduction for fade duration CCDF estimation in Rayleigh/Rician/Nakagami channels with relative errors below 0.5%.
Using common random numbers in rollout simulations provably reduces variance in relative utility estimates when a rollout policy is invoked beyond some depth.
citing papers explorer
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Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility
A Jump-HMM-driven modified Heston model generates synthetic implied volatility surfaces and American option prices directly from simulated equity return paths, breaking the circular dependency on market-derived volatility.
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Prediction-Powered Active Testing
PPAT residualizes losses via a prediction-powered control variate inside LURE, yielding lower-variance unbiased risk estimates, tailored acquisition, and asymptotic CIs that cover with fewer labels.
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Stochastic Analysis of Fade Duration Using Wiener Chaos Expansion and Malliavin Calculus: Optimal Importance Sampling via Adaptive SGD
Framework combining Wiener Chaos Expansion, Malliavin Calculus, and adaptive importance sampling achieves 839-2516x variance reduction for fade duration CCDF estimation in Rayleigh/Rician/Nakagami channels with relative errors below 0.5%.
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Using Common Random Numbers for Simulation-based Planning with Rollouts
Using common random numbers in rollout simulations provably reduces variance in relative utility estimates when a rollout policy is invoked beyond some depth.