Generative network based probabilistic portfolio management
US11386496B2 · kind B2 · utility
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14Claims
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Key dates
| Filing date | Jul 26, 2019 |
| Grant date | Jul 12, 2022 |
| Priority date | — |
| Expiry date | Dec 3, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/094
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A deep-learning neural network can be trained to model a probability distribution of the asset-price trends for a future time period using a training data set, which can include asset-price trends of a plurality of assets over a past time period and a latent vector sampled from a prior distribution associated with the asset-price trends of a plurality of assets. The training data set can represent a time series data. A portfolio optimization can be executed on the modeled probability distribution to estimate expected risks and returns for different portfolio diversification options.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.