Unveiling Hidden Market Manifolds: Transformer-Powered TDA with Bayesian Edge
| Thesis title: | Unveiling Hidden Market Manifolds: Transformer-Powered TDA with Bayesian Edge |
|---|---|
| Author: | Sheredeko, Oleksandr |
| Thesis type: | Diploma thesis |
| Supervisor: | Tomanová, Petra |
| Opponents: | Fičura, Milan |
| Thesis language: | English |
| Abstract: | This paper presents a high-frequency trading (HFT) framework designed to exploit short-term market trends. A key concept is the processing approach that employs topological data analysis to exploit volatility regimes. These refined signals are passed into a Bayesian inference model that quantifies uncertainty. |
| Keywords: | High Frequency Trading; Machine Learning; Modelling |
| Thesis title: | Unveiling Hidden Market Manifolds: Transformer-Powered TDA with Bayesian Edge |
|---|---|
| Author: | Sheredeko, Oleksandr |
| Thesis type: | Diplomová práce |
| Supervisor: | Tomanová, Petra |
| Opponents: | Fičura, Milan |
| Thesis language: | English |
| Abstract: | This paper presents a high-frequency trading (HFT) framework designed to exploit short-term market trends. A key concept is the processing approach that employs topological data analysis to exploit volatility regimes. These refined signals are passed into a Bayesian inference model that quantifies uncertainty. |
| Keywords: | High Frequency Trading; Machine Learning; Modelling |
Information about study
| Study programme: | Economic Data Analysis/Data Analysis and Modeling |
|---|---|
| Type of study programme: | Magisterský studijní program |
| Assigned degree: | Ing. |
| Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
| Faculty: | Faculty of Informatics and Statistics |
| Department: | Department of Econometrics |
Information on submission and defense
| Date of assignment: | 16. 12. 2024 |
|---|---|
| Date of submission: | 5. 5. 2025 |
| Date of defense: | 2. 6. 2025 |
| Identifier in the InSIS system: | https://insis.vse.cz/zp/90798/podrobnosti |