Delivery included to the United States

Financial Data Resampling for Machine Learning Based Trading SpringerBriefs in Computational Intelligence

Financial Data Resampling for Machine Learning Based Trading SpringerBriefs in Computational Intelligence Application to Cryptocurrency Markets - SpringerBriefs in Applied Sciences and Technology

1st Edition 2021

Paperback (23 Feb 2021)

Save $33.75

  • RRP $74.63
  • $40.88
Add to basket

Includes delivery to the United States

10+ copies available online - Usually dispatched within 7 days

Publisher's Synopsis

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.

Book information

ISBN: 9783030683788
Publisher: Springer International Publishing
Imprint: Springer
Pub date:
Edition: 1st Edition 2021
Language: English
Number of pages: 93
Weight: 168g
Height: 235mm
Width: 155mm
Spine width: 6mm