Financial news is known to move stock prices, for instance through company specific news events ("simple events") such as product recalls, earnings announcements, or mergers and acquisitions. In addition, further effects may be explained by the market sentiment trend extracted from the news. Due to the complexity of financial markets, it seems reasonable to assume that not all companies are equally responsive to such sentiment trends and that such responsiveness may change over time. To address this issue, I introduce the concept of News Beta. Similar to the beta in the CAPM, News Beta measures the responsiveness of a company's stock price to a market benchmark, but instead of considering market returns, it considers changes to a market sentiment index. Applying News Beta in trading applications, it is possible not only to use it as a stock selection tool, but also as input in the process moving from simple to complex events.

Peter Hafez, Director of Quantitative Research at RavenPack

A graduate and researcher from Sir John Cass Business School, Peter has held various positions in the portfolio management and alternative investment industry both in London and in Copenhagen, Denmark with companies such as Standard & Poor's, Credit Suisse First Boston, and Saxo Bank where he was a Chief Quantitative Analyst and Head of CHARM. Most recently, Peter has acted as an advisor and consultant to businesses within the quantitative trading and investment industry focusing on applications of news analytics. Peter is a recognized speaker at conferences on behavioral finance and algorithmic trading across the globe.

Peter joined RavenPack in 2008 as a Director of Quantitative Research responsible for enhancing existing data products as well as designing new ones based on RavenPack's linguistic analysis.