Generative Models for Stochastic Processes Using Convolutional Neural Networks
Autor: | Neto, Fernando Fernandes |
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Rok vydání: | 2018 |
Předmět: | |
Druh dokumentu: | Working Paper |
Popis: | 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. |
Databáze: | arXiv |
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