We use high frequency intra-day data to investigate the influence of unscheduled currency
and Bitcoin news on the returns, volume and volatility of the cryptocurrency Bitcoin and …

The authors used a dataset of more than 900,000 news stories to test whether news can
predict stock returns. They measured sentiment with a proprietary Thomson Reuters neural …

This study presents a methodology for identifying a broad range of real‐world news events
based on microblogging messages. Applying computational linguistics to a unique dataset …

This article utilises commodity specific news sentiment data provided by Thomson Reuters
News Analytics to examine the relationship between news sentiment and returns in the gold …

News on corporate information can enhance clarity or add to confusion for market
participants, especially investors. We explore how two diverse types of information …

Analysts often update their recommendations following corporate news. Questions have
been raised regarding analysts' ability to generate new information beyond recent corporate …

We analyze the effects of positive and negative news on the liquidity of 100 largest
cryptocurrencies in an event study context. We find that the liquidity of cryptocurrencies …

In contrast to most developed countries that use registration systems, China has
implemented an approval system for initial public offering (IPO) applications. As this IPO …

This paper examines the dynamic relationship between firm-level return volatility and public
news sentiment. By using the new RavenPack News Analytics⿿ Dow Jones Edition …

This paper utilises commodity-specific news sentiment data on the Organisation of
Petroleum Exporting Countries (OPEC) collected from Thomson Reuters News Analytics in …