We propose a spatial approach for modeling risk spillovers using financial time-varying proximity matrices based on observable networks. We show how these methods could be useful in (i) isolating risk channels, risk spreaders and risk receivers, (ii) investigating the role of portfolio composition in risk transfer, and (iii) computing target exposure structures able to reduce the forecasted system variance and thus the risk of the system. Our empirical analysis builds on banks' foreign exposures provided by the Bank of International Settlements (BIS) as a proxy for Euro area cross-country holdings. We find, in the European sovereign bond markets, that Germany, Italy and, to a lesser extent, Greece are playing a central role in spreading risk, and Ireland and Spain are the most susceptible receivers of spillover effects that can be traced back to a physical claim channel: banks' foreign exposures. We additionally show that acting on these physical channels before the sovereign crisis, it would have been possible to have a clear risk mitigation outcome Keywords spatial GARCH, network, risk spillover, financial spillover. JEL Codes C58, G10 AbstractWe propose a spatial approach for modeling risk spillovers using financial time-varying proximity matrices based on observable networks. We show how these methods could be useful in (i) isolating risk channels, risk spreaders and risk receivers, (ii) investigating the role of portfolio composition in risk transfer, and (iii) computing target exposure structures able to reduce the forecasted system variance and thus the risk of the system. Our empirical analysis builds on banks' foreign exposures provided by the Bank of International Settlements (BIS) as a proxy for Euro area cross-country holdings. We find, in the European sovereign bond markets, that Germany, Italy and, to a lesser extent, Greece are playing a central role in spreading risk, and Ireland and Spain are the most susceptible receivers of spillover effects that can be traced back to a physical claim channel: banks' foreign exposures. We additionally show that acting on these physical channels before the sovereign crisis, it would have been possible to have a clear risk mitigation outcome.
We propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic normality of the quasi-maximum-likelihood estimator. We show how to isolate risk channels and we discuss how to compute target exposure able to reduce system variance. An empirical analysis on Euro-area cross-country holdings shows that Italy and Ireland are key players in spreading risk, France and Portugal are the major risk receivers, and we uncover Spain's non-trivial role as risk middleman.
In this paper, we analyze the dynamic relationships between ten stock exchanges of the euro zone using Granger causal networks. Considering returns for which we allow the variance to follow a Markov-Switching GARCH or a Changing-Point GARCH process, we …rst show that over di¤erent periods, the topology of the network is highly unstable. In particular dynamic relationships vanish over very recent years. Then, expandingon this idea, we analyze patterns of information transmission within the network. Using rolling windows to study networks' topology in terms of information clustering, we …nd that the nodes'state changes continually.Moreover, the system exhibits periods of ‡ickering in information transmission. During these periods of ‡ickering, the system also exhibits desynchronization in the information transmission process. These periods do precede tipping points or phase transitions on the market, especially before the global …nancial crisis, and can thus be used as early warnings. To our knowledge, this is the …rst time that ‡ickering in information transmission
We use a recently proposed fast test of copula radial symmetry based on multiplier bootstrap and obtain an equivalent randomization test. The literature shows the statistical superiority of the randomization approach in the bivariate case. We extend the comparison of statistical performance focusing on the high-dimensional regime in a simulation study. We document radial asymmetry in the joint distribution of the percentage changes of sectorial industrial production indices of the European Union.
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