High-frequency news analytics can increase market efficiency by allowing traders to react faster to new information. One concern about such services is that they might provide a competitive advantage to their users with potential distortionary price effects. This column looks at how high frequency news analytics affect the stock market, net of the informational content that they provide. News analytics improve price efficiency, but at the cost of reducing liquidity and with potentially distortionary price effects.
Bastian von Beschwitz, Donald B. Keim, Massimo Massa, Thursday, July 2, 2015
Dora L. Costa, Matthew E. Kahn, Monday, April 27, 2015
Newspapers report good and bad news, but the reporting doesn’t always match reality. This column presents evidence from turn-of-the-century America that news reports of typhoid tracked mortality patterns, but the reporting was biased. Spikes in death rates led to bigger jumps in media coverage when death rates were low. This could be due to the idea that deviations from Kahneman and Tversky’s ‘reference points’ are more newsworthy, or due to the possibility that bad news is more valuable to readers when things seem to be going well.
Alessandro Beber, Michael W Brandt, Maurizio Luisi, Friday, April 19, 2013
Timely measurement of the state of the economy traditionally relies on low-frequency observations of a few economic aggregates referring to previous weeks, months, or even quarters. This column presents a new method of a real-time approach to timely and more accurate macroeconomic news.
Jakob de Haan, Mark Mink, Thursday, February 23, 2012
Since 2010, Eurozone countries have engaged in unprecedented rescue operations to avoid contagion from a potential Greek sovereign default. This column argues that news about Greek public finances does not affect Eurozone bank stock prices, while news about a Greek bailout does. This suggests that markets consider news about a Greek bailout to be a signal of Eurozone countries’ willingness to use public funds to combat the financial crisis.