Financial data resampling for machine learning based trading application to cryptocurrency markets / [electronic resource] :

• 作者： Borges, Tome Almeida.
• 其他作者：
  • Neves, Rui.
  • SpringerLink (Online service)
• 其他題名：
  • SpringerBriefs in applied sciences and technology.
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： SpringerBriefs in applied sciences and technology, Computational intelligence
• 主題： Cryptocurrencies--Statistical methods. , Investments--Statistical methods. , Resampling (Statistics) , Computational Mathematics and Numerical Analysis.
• ISBN： 9783030683795 (electronic bk.) 、 9783030683788 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• More
• 摘要註: 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.
• 讀者標籤：

  需登入
• 引用連結：

  Copy Link
• 目前引用數
• Share: