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.
Journal of Political Economy , volume=
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The Time-Geometric model combines GNNs for geometric patterns with temporal models and reports statistically significant accuracy gains in financial time series forecasting.
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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The Statistical Significance of the Inclusion of Graph Neural Networks in the Financial Time Series Forecasting Problem
The Time-Geometric model combines GNNs for geometric patterns with temporal models and reports statistically significant accuracy gains in financial time series forecasting.