Stock data clustering and multiscale trend detection

DOI10.1007/s11009-010-9186-7zbMath1241.62145OpenAlexW2040987808MaRDI QIDQ430849

Andreea B. Dragut

Publication date: 26 June 2012

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-010-9186-7

zbMATH Keywords

financial time serieslinear time clustering algorithmmonotonic algorithmmultiscale trend detectionspace dilating measure

Mathematics Subject Classification ID

Related Items (1)

Versatile hyper-elliptic clustering approach for streaming data based on one-pass-thrown-away learning

Uses Software

• wmtsa

Cites Work

• Unnamed Item
• Mining evolving data streams for frequent patterns
• Adaptive correlation analysis in stream time series with sliding windows
• Correlation based networks of equity returns sampled at different time horizons
• Transfer estimation of evolving class priors in data stream classification
• Unfolding preprocessing for meaningful time series clustering
• Space-conserving agglomerative algorithms
• EVOLUTION AND TIME HORIZONS IN AN AGENT-BASED STOCK MARKET
• Asset Trees and Asset Graphs in Financial Markets
• Dimensionality reduction for fast similarity search in large time series databases

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