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Multi-Asset Spot and Option Market Simulation

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arxiv 2112.06823 v1 pith:6JNDGJSW submitted 2021-12-13 q-fin.CP cs.LGq-fin.MFq-fin.STstat.ML

classification q-fin.CPcs.LGq-fin.MFq-fin.STstat.ML
keywords marketsimulatorsflowsmulti-assetnormalizingoptionpricesspot
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We construct realistic spot and equity option market simulators for a single underlying on the basis of normalizing flows. We address the high-dimensionality of market observed call prices through an arbitrage-free autoencoder that approximates efficient low-dimensional representations of the prices while maintaining no static arbitrage in the reconstructed surface. Given a multi-asset universe, we leverage the conditional invertibility property of normalizing flows and introduce a scalable method to calibrate the joint distribution of a set of independent simulators while preserving the dynamics of each simulator. Empirical results highlight the goodness of the calibrated simulators and their fidelity.

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Cited by 1 Pith paper

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    Policies trained under stationary latent ambiguity, implemented by refreshing the latent parameter, preserve robustness to regime shifts better than policies trained under a fixed latent draw.

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