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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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3 results for “SDE-GANs”

Neural Options Pricingq-fin.MF

Neural models price financial options without assuming underlying price forms.

problem Pricing financial options under flexible price processes.

method Apply neural SDEs as universal approximators, use Wasserstein distance for training.

result Error in option prices bounded by Wasserstein distance used for training.

neural networks financial options SDEs Wasserstein distance Itô processes

2021-05-27abs ↗pdf ↗

Efficient and Accurate Gradients for Neural SDEscs.LG

We developed efficient methods to compute gradients for Neural SDEs, improving training speed and accuracy.

problem Training Neural SDEs requires accurate and efficient computation of gradients, which is challenging due to the complexity of SDEs.

method We introduced a reversible Heun method for solving backwards-in-time SDEs and a Brownian Interval for sampling and reconstructing Brownian motion.

result Our methods significantly improve training speed and accuracy for Neural SDEs, outperforming state-of-the-art techniques.

Neural SDEs Gradient Computation Reversible Heun Method Brownian Interval SDE-GANs

2021-05-27abs ↗pdf ↗

Monte Carlo Simulation of SDEs using GANscs.LG

GANs can approximate SDEs for large time steps.

problem Approximating SDEs for large time steps using GANs.

method Proposed a conditional GAN architecture to enable strong approximation of SDEs.

result Supervised GAN outperformed standard GAN and other schemes in strong error.

Monte Carlo Simulation SDEs GANs Conditional GAN Strong Approximation

2021-04-03abs ↗pdf ↗