Systems and methods for callable options values determination using deep machine learning
US11100586B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 9, 2019 |
| Grant date | Aug 24, 2021 |
| Priority date | — |
| Expiry date | Oct 14, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30252
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Systems, apparatuses, methods, and computer program products are disclosed for pricing a callable instrument. A plurality of corresponding pairs of Brownian motion paths and index value paths are determined corresponding to a set of dates. A deep neural network (DNN) of a backward DNN solver is trained until a convergence requirement is satisfied by for each pair of corresponding Brownian motion path and index value path, using the backward DNN solver to determine by iterating in reverse time order from a final discounted option payoff to an initial value. A statistical measure of spread of a set of initial values is determined and parameters of the DNN are modified based on the statistical measures of spread. Pricing information is determined by the backward DNN solver and provided such that a representation thereof is provided via an interactive user interface of a user computing device.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.