Financial volatility forecasting using novel deep learning models
dc.contributor | Aalto University | en |
dc.contributor | Aalto-yliopisto | fi |
dc.contributor.advisor | Pekka, Malo | |
dc.contributor.author | Ha, Vy | |
dc.contributor.department | Tieto- ja palvelujohtamisen laitos | fi |
dc.contributor.school | Kauppakorkeakoulu | fi |
dc.contributor.school | School of Business | en |
dc.date.accessioned | 2023-12-02T16:13:34Z | |
dc.date.available | 2023-12-02T16:13:34Z | |
dc.date.issued | 2023 | |
dc.format.extent | 90 | |
dc.identifier.uri | https://aaltodoc.aalto.fi/handle/123456789/124691 | |
dc.identifier.urn | URN:NBN:fi:aalto-202312027021 | |
dc.language.iso | en | en |
dc.location | P1 I | fi |
dc.programme | Information and Service Management (ISM) | en |
dc.subject.keyword | deep learning | en |
dc.subject.keyword | LSTM | en |
dc.subject.keyword | transformer-based model | en |
dc.subject.keyword | hybrid model | en |
dc.subject.keyword | volatility | en |
dc.subject.keyword | risk management | en |
dc.title | Financial volatility forecasting using novel deep learning models | en |
dc.type | G2 Pro gradu, diplomityö | fi |
dc.type.ontasot | Master's thesis | en |
dc.type.ontasot | Maisterin opinnäyte | fi |
local.aalto.electroniconly | yes | |
local.aalto.openaccess | no |