coverage and news flow have therefore the highest levels of volatility asymmetry (e.g.,
the USA, UK, and Japan).
Given that, it is no surprise that globally volatility asymmetry increases over time, as
more and more private investors enter markets and the news flow increases.
The model is supported by two further pieces of evidence: first, the number of Google
searches for certain keywords related to the macroeconomy like ‘‘recession’’ is a pre-
dictor for high volatility. This demonstrates directly that private investors (who are most
likely the majority among Google users) influence volatility, and also shows the pro-
posed causality. Second, investigating a full sample of stock market trades of a country
(Estonia) we could see that times with high volatility coincide with times where many
investors trade on the market. The new investors that enter in these times are usually less
professional investors. Our model suggests that their trading increases volatility.
11.5 Acknowledgments
We thank Thorsten Hens and Sven Christian Steude for interesting discussions on the
topic of this chapter. Support by the National Centre of Competence in Research
‘‘Financial Valuation and Risk Management’’ (NCCR FINRISK); Project A1, ‘‘Be-
havioural and Evolutionary Finance’’; the University Priority Program ‘‘Finance and
Financial Markets’’ of the University of Zu ̈rich; and by ‘‘LGT and Science’’ is gratefully
acknowledged.
11.6 References
Andersen T.G.; Bollerslev T.; Diebold F.X. (2003)Some Like it Smooth, and Some Like it Rough:
Untangling Continuous and Jump Components in Measuring, Modeling, and Forecasting Asset
Return Volatility, SSRN eLibrary.
Volatility asymmetry, news, and private investors 269Figure 11.7.Functional sketch explaining how the news reaction of private investors can lead to
asymmetric volatility.