Online detection of financial time series peaks and troughs: A probability‐based approach*

DOI10.1002/SAM.11411OpenAlexW2922448664MaRDI QIDQ4970286

Riccardo Bramante, Diego Zappa, Silvia Facchinetti

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11411

zbMATH Keywords

financial time seriestime varying parametersturning point detection

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (2)

Evaluation of recursive detection methods for turning points in financial time series ⋮ A multi-scale approach for testing and detecting peaks in time series

This page was built for publication: Online detection of financial time series peaks and troughs: A probability‐based approach*

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q4970286)