Extends rough fractional stochastic volatility to a multivariate fOU model with GMM estimation, simulation validation, and empirical analysis of realized volatility series showing correlations and spillover effects.
Stochastic automatic differentiation: automatic differentiation for Monte-Carlo simulations
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Bayesian neural SDE calibration produces posterior mixtures that deliver robust bounds on implied volatility by jointly using historical and option data, learning the historical-to-risk-neutral measure change, and sampling via Langevin dynamics.
Discounting sensitivities align liquidity forecasting with self-financing replication, while a liquidity valuation adjustment captures settlement lags.
citing papers explorer
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Multivariate Rough Volatility
Extends rough fractional stochastic volatility to a multivariate fOU model with GMM estimation, simulation validation, and empirical analysis of realized volatility series showing correlations and spillover effects.
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Robust financial calibration: a Bayesian approach for neural SDEs
Bayesian neural SDE calibration produces posterior mixtures that deliver robust bounds on implied volatility by jointly using historical and option data, learning the historical-to-risk-neutral measure change, and sampling via Langevin dynamics.
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Replication-Consistent Liquidity Forecasting for Derivatives -- Forward Funding Sensitivities and a Liquidity Valuation Adjustment for Settlement Lags
Discounting sensitivities align liquidity forecasting with self-financing replication, while a liquidity valuation adjustment captures settlement lags.