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Financial Data Resampling for Machine Learning Based Trading
Application to Cryptocurrency Markets
Tomé Almeida Borges, Rui Neves
Livre broché | Anglais | SpringerBriefs in Applied Sciences and Technology | SpringerBriefs in Computational Intelligence
68,95 €
+ 137 points
Description
This book presents a system that combines the expertise of four algorithms, namely Gradient Tree Boosting, Logistic Regression, Random Forest and Support Vector Classifier to trade with several cryptocurrencies. A new method for resampling financial data is presented as alternative to the classical time sampled data commonly used in financial market trading. The new resampling method uses a closing value threshold to resample the data creating a signal better suited for financial trading, thus achieving higher returns without increased risk. The performance of the algorithm with the new resampling method and the classical time sampled data are compared and the advantages of using the system developed in this work are highlighted.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 93
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9783030683788
- Date de parution :
- 23-02-21
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 156 mm x 234 mm
- Poids :
- 167 g
