Information Shares in Stationary Time Series and Global Volatility Discovery

58 Pages Posted: 16 Feb 2016 Last revised: 25 Jul 2017

See all articles by Rainer Baule

Rainer Baule

University of Hagen

Bart Frijns

Auckland University of Technology - Faculty of Business & Law

Milena Tieves

University of Hagen

Date Written: July 24, 2017

Abstract

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.

Keywords: information share, stationarity, co-integration, variance decomposition, volatility spillover

JEL Classification: G14, C32, C10, C51

Suggested Citation

Baule, Rainer and Frijns, Bart and Tieves, Milena, Information Shares in Stationary Time Series and Global Volatility Discovery (July 24, 2017). Available at SSRN: https://ssrn.com/abstract=2733068 or http://dx.doi.org/10.2139/ssrn.2733068

Rainer Baule

University of Hagen ( email )

Universitaetsstrasse 41
Hagen, 58097
Germany

Bart Frijns

Auckland University of Technology - Faculty of Business & Law ( email )

3 Wakefield Street
Private Bag 92006
Auckland Central 1020
New Zealand

Milena Tieves (Contact Author)

University of Hagen ( email )

Universitätsstrasse 41
Hagen, 58084
Germany

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