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The Handbook of News Analytics in Finance by Leela Mitra, Gautam Mitra

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6.5 REFINING FILTERS USING INTERACTIVE EXPLORATORY DATA ANALYSIS AND VISUALIZATION

There are many ways to slice and dice event studies, and for advanced content-based filters the ability to drill down to individual news events is desirable. We developed an interactive exploratory data analysis and drill-down system, the Event Study Explorer, using the TIBCO Spotfire visualization tool. The sliders and selection boxes seen in Figure 6.12 illustrate this capability.

This approach to exploratory data analysis (EDA) was first suggested by John Tukey (Tukey, 1977), and refined by Tufte in Visual Display of Quantitative Information (Tufte, 2001). These ideas were greatly advanced as computational tools by Ben Schneiderman's Human Computer Interface Lab (Schneiderman and Plaisant, 2009).

The Event Study Explorer allows great flexibility in filter selection parameters, study period, sector, capitalization, and pre-event return. It provides the ability to drill down to news content as the basis for further natural language processing (NLP) or machine learning (ML) filtering.

The Event Study Explorer allows the researcher to consider the subsequent cumulative return for specific subsets of events. Events are keyed by date and RIC (security identifier) and can be subset by time period, sector, market capitalization, or attributes of the RNSE news that occurred on that day. Given news aggregations and return calculations, the Event Study Explorer is easily configured in Spotfire with no programming ...

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