The Wiley Finance Series : Handbook of News Analytics in Finance

(Chris Devlin) #1

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 program-
ming required. Specific components (tagged with numbers in circles in Figure 6.12) of
the Event Study Explorer include:


1.Long-term event study view The one-quarter excess return of the current subset of
positive and negative events.
2.Short-term event study view The one-week excess return of the current subset of
positive and negative events.
3.The event filter This allows the researcher to dynamically choose for which events
she would like to see subsequent excess return calculations.
4.Details on demand When the user selects a subset of events (e.g., by clicking on the
positive or negative event line in one of the event study views), the details for these
event days are displayed here.
5.Signals within each period This display shows that the subset of events is consistent
across time.
6.Signals within each sector This display shows that the subset of events is consistent
across sectors.


Relating news analytics to stock returns 159

Figure 6.9.Full S&P index results. Using Linked count 5¼0 includes only news items without
predecessor items. The table insert illustrates the expected effects of adjusting filter settings—
requiring a larger threshold reduces the number of signals, but the ones that remain are associated
with larger excess returns.

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