Information Shares in Stationary Time Series and Global Volatility Discovery

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Standard price discovery measures, particularly information shares, rely on the concept of co-integration for non-stationary time series. For the definition of information shares, the existence of a permanent impact of innovations is crucial, as these shares measure the relative contribution of different markets to this permanent impact. For stationary time series such as interest rates, CDS prices, or volatilities, permanent impacts do not occur and thus the concept fails. In this paper, we extend the concept of information shares
to the case of stationary time series. We suggest a price discovery metric based on the well-known variance decomposition for stationary time series, aiming to be equivalent to Hasbrouck's (1995) information share. This new price discovery measure converges to the standard information share in the limiting case of non-stationarity. As an application, we use the new measure to gain insight into the behavior of major implied volatility indices in Japan, Germany, and the US. We find that the US market has lost its dominant role for global volatility discovery with the emergence of the European debt crisis. In recent periods, the German volatility index exhibits the largest information shares. The Japanese market had a higher importance before the global financial crisis, which has
almost vanished within recent periods.

Author(s):

Rainer Baule    
FernUniversität in Hagen
Germany

Bart Frijns    
Auckland University of Technology
New Zealand

Milena Tieves    
FernUniversität in Hagen
Germany