Generally, news sentiment indexes try to capture the prevailing sentiment trend for a particular market or sector based on news information. In order to capture such trends, it seems reasonable to consider an aggregation of news sentiment over well-defined moving time intervals to capture the general “mood” of the market. News sentiment indexes have been useful when constructing simple investment strategies that consistently outperform similar strategies based on price momentum (Hafez, 2009a). Previous results have shown to be resistant to different sentiment aggregation windows, investment horizons, and different investment timing.

5.2.1 Data and news analytics

In order to measure sentiment for a particular equity index, I use news analytics data from RavenPack going back to 2005. The dataset includes tens of thousands of records per day, each representing a company reference in a financial news story. Currently, RavenPack tracks around 27,000 companies globally, which represent more than 98% of the investable global market. Each record comes with a millisecond timestamp and data for sentiment, novelty, relevance, event categories, among other news analytics. One of the advantages of RavenPack's news analytics is that the data are free of survivorship bias. That is, each company is identified systematically using its respective point-in-time ticker symbols and/or other company identifiers or aliases, and both “dead” and “survivor” companies are included ...

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