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Financial data resampling for machin...

Borges, Tome Almeida.

Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Financial data resampling for machine learning based tradingby Tome Almeida Borges, Rui Neves.
其他題名:	application to cryptocurrency markets /
作者:	Borges, Tome Almeida.
其他作者:	Neves, Rui.
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xv, 93 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	CryptocurrenciesStatistical methods.
電子資源:	https://doi.org/10.1007/978-3-030-68379-5
ISBN:	9783030683795$q(electronic bk.)

Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /
Borges, Tome Almeida.

Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /[electronic resource] :by Tome Almeida Borges, Rui Neves. - Cham :Springer International Publishing :2021. - xv, 93 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology, Computational intelligence. - SpringerBriefs in applied sciences and technology.Computational intelligence..

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.

ISBN: 9783030683795$q(electronic bk.)

Standard No.: 10.1007/978-3-030-68379-5doiSubjects--Topical Terms:

895268
Cryptocurrencies
--Statistical methods.

LC Class. No.: HG1710.3

Dewey Class. No.: 332.63

Financial data resampling for machine learning based tradingapplication to cryptocurrency markets /
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