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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.
Über die Autorin bzw. den Autor:
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 evolutionof the financial markets.
Titel: Financial Data Resampling for Machine ...
Verlag: Springer
Erscheinungsdatum: 2021
Einband: Softcover
Zustand: New
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide. Artikel-Nr. ABNR-279923
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Artikel-Nr. 394199647
Anzahl: 1 verfügbar
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 112 pp. Englisch. Artikel-Nr. 9783030683788
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Artikel-Nr. 9783030683788
Anzahl: 1 verfügbar
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Paperback. Zustand: Brand New. 112 pages. 9.25x6.10x0.27 inches. In Stock. Artikel-Nr. x-3030683788
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