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Stock market events are hard to model. In recent years, one approach that has been receiving increasing attention is to analyze graphs induced by price correlations of different stock companies. By analyzing the structure of such graphs, it is possible to identify critical events, e.g., market crises. To the best of our knowledge, there are no tools available that offer comprehensive support for such analyses. This paper introduces a novel tool that offers in-depth analysis with the ability of fine tuning parameters with an intuitive user interface. With a proposed workflow to handle time series data, the tool becomes versatile and it can analyze correlation graphs of different semantics: minimum spanning tree, graphs with edge thresholds, and evolving graphs. It also provides a rich set of functions that enable users to explore easily, interactively and systematically the correlation graphs starting from a file of raw time series data. With real-world stock data, we demonstrate how straightforward yet effective it is to accomplish various analytical tasks with the proposed tool.

Correlation graph analytics for stock time series data