Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10362/142106
Título: | Automated AI trading system |
Autor: | Baltazar, Diogo Miguel Fontes Raposo |
Orientador: | Zejnilovic, Leid |
Palavras-chave: | Machine learning Python Cryptocurrency Cloud Algorithms Sql |
Data de Defesa: | 20-Jan-2022 |
Resumo: | This Work Project is an empirical investigation and a prototype development of an automated AI trading system. The framework system is a fully automated pipeline of data processing, data analytics, and signals interpretation that ends with an action to buy, hold, or sell an asset. The data analytics segment represents a deployment of state-of-the-art AI models developed to predict future cryptocurrency prices while accounting for risk and order management. The framework proposed predicted the next 15-minuteclose price of Bitcoin achieving an RMSE value of 167during the period of 11th-15thDecember. After accounting for fees and commissions, the system would have yielded a return of (1.11%) with a Sharpe Ratio of (0.04)against a B&H strategy with (3.92%)and (0.09)Sharpe. |
URI: | http://hdl.handle.net/10362/142106 |
Designação: | A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics |
Aparece nas colecções: | NSBE: Nova SBE - MA Dissertations |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
---|---|---|---|---|
2021-22_fall_29134_diogo-baltazar.pdf | 730,79 kB | Adobe PDF | Ver/Abrir |
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