A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?

Financial companies from all around the world have started to focus their investments in quantitative and algorithmic funds. Those methods run in server applications that execute automatic trades. It is important to distinguish high frequency trading from machine learning trading. The latter is...

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Detalles Bibliográficos
Autor principal: Alba Chicar, Agustín
Otros Autores: Roccatagliata, Pablo
Formato: Tesis de maestría acceptedVersion
Lenguaje:Español
Publicado: 2023
Materias:
Algoritmos
Inversiones
inversiones financieras
Análisis de datos
Gestión Financiera
Algorithms
Financial investments
data
Bitcoins
Compraventa de bitcoins
Aprendizaje automático
Machine Learning
Bitcoins Trading
Acceso en línea:https://repositorio.utdt.edu/handle/20.500.13098/11558
Aporte de:
Repositorio Digital Universidad Torcuato Di Tella de Universidad Torcuato Di Tella
id I57-R163-20.500.13098-11558
record_format dspace
institution Universidad Torcuato Di Tella
institution_str I-57
repository_str R-163
collection Repositorio Digital Universidad Torcuato Di Tella
language Español
orig_language_str_mv spa
topic Algoritmos
Inversiones
inversiones financieras
Análisis de datos
Gestión Financiera
Algorithms
Financial investments
data
Bitcoins
Compraventa de bitcoins
Aprendizaje automático
Machine Learning
Bitcoins Trading
spellingShingle Algoritmos
Inversiones
inversiones financieras
Análisis de datos
Gestión Financiera
Algorithms
Financial investments
data
Bitcoins
Compraventa de bitcoins
Aprendizaje automático
Machine Learning
Bitcoins Trading
Alba Chicar, Agustín
A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
topic_facet Algoritmos
Inversiones
inversiones financieras
Análisis de datos
Gestión Financiera
Algorithms
Financial investments
data
Bitcoins
Compraventa de bitcoins
Aprendizaje automático
Machine Learning
Bitcoins Trading
description Financial companies from all around the world have started to focus their investments in quantitative and algorithmic funds. Those methods run in server applications that execute automatic trades. It is important to distinguish high frequency trading from machine learning trading. The latter is used and analyzed in detail in the present work. This project explains the development of a trading strategy on Bitcoins based on machine learning techniques. A pipeline proposal is shown which is based on Lopez de Prado's book ([Pra18]). Some modi cations are introduced in the book's pipeline to adjust a momentum primary model on Bitcoins, and to incorporate and study features that would let estimate the size of the primary model bets (secondary model to be trained on top of the rst model). The range of features to analyze goes from nancial metrics derived from Bitcoin prices and volumes, to Bitcoin and blockchain related features and nally social indexes which incorporate interest and animosity towards Bitcoin itself. The pipeline proposed in [Pra18] and implemented in this thesis rigorously handles the dataset, the involved models and nally the posterior backtesting strategies. Details about statistical foundation of the involved methods, algorithm complexity and implementation and domain explanations (such as those related to cryptocurrencies) can be found. The pipeline allows to gather enough information to compare and decide whether a propose strategy is good enough to be implemented. We will use this to compare models that introduce microstructure indexes such as SADF (Supremum Augmented Dickey Fuller) in comparison and conjunction with social indexes.
author2 Roccatagliata, Pablo
author_facet Roccatagliata, Pablo
Alba Chicar, Agustín
format Tesis de maestría
acceptedVersion
author Alba Chicar, Agustín
author_sort Alba Chicar, Agustín
title A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
title_short A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
title_full A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
title_fullStr A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
title_full_unstemmed A Quantamental approach to Bitcoin trading: Are we swinging for the Fences?
title_sort quantamental approach to bitcoin trading: are we swinging for the fences?
publishDate 2023
url https://repositorio.utdt.edu/handle/20.500.13098/11558
work_keys_str_mv AT albachicaragustin aquantamentalapproachtobitcointradingareweswingingforthefences
AT albachicaragustin quantamentalapproachtobitcointradingareweswingingforthefences
bdutipo_str Repositorios
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