In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to estimate the contribution and the vulnerability to systemic risk of volatility risk premia for five European stock markets: France, Germany, UK, Switzerland and the Netherlands. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. Therefore, we estimate and invert a Fractionally Integrated VAR model to compute the cross forecast error variance shares necessary to obtain the index of total and directional connectedness
