Mathematical Research Data Initiative
Main page
Recent changes
Random page
SPARQL
MaRDI@GitHub
Special pages
In other projects
MaRDI portal item
Discussion
View source
View history
Purge
English
Log in

Forecasting gold price with the XGBoost algorithm and SHAP interaction values

From MaRDI portal
Publication:6547070
Jump to:navigation, search

DOI10.1007/S10479-021-04187-WzbMATH Open1537.91337MaRDI QIDQ6547070

Jean-Laurent Viviani, Sami Ben Jabeur, Salma Mefteh-Wali

Publication date: 30 May 2024

Published in: Annals of Operations Research (Search for Journal in Brave)




zbMATH Keywords

gold priceXGBoostCatBoostShapley additive explanations


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Interest rates, asset pricing, etc. (stochastic models) (91G30)


Cites Work

  • Title not available (Why is that?)
  • Title not available (Why is that?)
  • A prediction-driven mixture cure model and its application in credit scoring
  • Credit spread approximation and improvement using random forest regression
  • Deep neural networks, gradient-boosted trees, random forests: statistical arbitrage on the S\&P 500
  • Large data sets and machine learning: applications to statistical arbitrage
  • Can Exchange Rates Forecast Commodity Prices?*
  • Random forests


Related Items (1)

Forecasting duty-free shopping demand with multisource data: a deep learning approach






This page was built for publication: Forecasting gold price with the XGBoost algorithm and SHAP interaction values

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6547070)

Retrieved from "https://portal.mardi4nfdi.de/w/index.php?title=Publication:6547070&oldid=40073556"
Tools
What links here
Related changes
Printable version
Permanent link
Page information
This page was last edited on 13 February 2025, at 17:32.
Privacy policy
About MaRDI portal
Disclaimers
Imprint
Powered by MediaWiki