Financial Data Resampling For Machine Learning Based Trading - Borges Tomé Almeida; Neves Rui | Libro Springer 02/2021 - HOEPLI.it


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Financial Data Resampling for Machine Learning Based Trading Application to Cryptocurrency Markets

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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 02/2021
Edizione: 1st ed. 2021





Trama

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.





Sommario

Chapter 1 - Introduction       

Chapter 2 - Related work     

Chapter 3 - Implementation               

Chapter 4 - Results  

Chapter 5 - Conclusions and future work 





Autore

Tomé Almeida Borges is a data scientist at Santander Portugal since December 2019. He received the master’s degree in Electrical and Computer Engineering from Instituto Superior Técnico, Technical University of Lisbon, Portugal, in 2019. His research activity is focused on pattern recognition and data resampling methods of financial markets.

Rui Ferreira Neves is a professor at Instituto Superior Técnico since 2005. He received the Diploma in Engineering and the Ph.D. degrees in Electrical and Computer Engineering from the Instituto Superior Técnico, Technical University of Lisbon, Portugal, in 1993 and 2001, respectively. In 2006, he joined Instituto de Telecomunicações (IT) as a research associate. His research activity deals with evolutionary computation and pattern matching applied to the financial markets, sensor networks, embedded systems and mixed signal integrated circuits. He uses both fundamental, technical and pattern matching indicators to find the evolution of the financial markets.








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Altre Informazioni

ISBN:

9783030683788

Condizione: Nuovo
Collana: SpringerBriefs in Applied Sciences and Technology
Dimensioni: 235 x 155 mm Ø 185 gr
Formato: Brossura
Illustration Notes:2 Illustrations, black and white
Pagine Arabe: 93
Pagine Romane: xv






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