Generative Models for Stochastic Processes Using Convolutional Neural Networks

Fernando Fernandes Neto

Papers from arXiv.org

Abstract: The present paper aims to demonstrate the usage of Convolutional Neural Networks as a generative model for stochastic processes, enabling researchers from a wide range of fields (such as quantitative finance and physics) to develop a general tool for forecasts and simulations without the need to identify/assume a specific system structure or estimate its parameters.

Date: 2018-01
New Economics Papers: this item is included in nep-cmp and nep-ets
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1801.03523

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