Journal Of Network Theory In Finance

On September 9, 2015, the second annual conference on Network Theory and Financial Risk, sponsored by The Journal of Network Theory in Finance, was held at the Centre for Risk Studies at Cambridge University. The program contained six keynotes by members of the journal's editorial board. The twenty-five research papers presented over two days used methods from network theory to address systemic risk, discussed market risk and asset allocation strategies, risks in payment systems and supply networks, and risks stemming from interbank exposures, and presented accounts of historical financial crises viewed through the lens of network theory. The next conference will be held in September 2016.

The first paper in the issue, "European government bond dynamics and stability policies: taming contagion risks" by Peter Schwendner, Martin Schuele, Thomas Ott and Martin Hillebrand, was presented at the journal's conference in Cambridge. It develops methodologies to measure spillover risks in European sovereign bond markets in the period 2004-15. Using partial correlations of daily changes in yields of euro area sovereign bonds as links, the authors find that different "core" and "periphery" network structures started to emerge after 2010. They also find that investors became confident in the guarantee structure of the European Financial Stability Facility (EFSF) within a year of its inception (recognizing it as a core issuer). The proposed methodology works very well as a tool to monitor the time dynamics of relationships between sovereign bond yield changes, and also more broadly to understand the structural dynamics of any complex system moving in time.

Our second paper, "Systemic risk and the sovereign-bank default nexus: a network vector autoregression approach" by Peter Claeys and Bořek Vašíček, also investigates European bond markets. In particular, the authors look at credit risk spillover effects between financial institutions and sovereigns in the euro area. The paper develops a contagion index based on Granger causality of fair-value credit default spreads. In a time-varying analysis, the authors find only a limited number of contagion episodes when controlling for common factors and taking into account implicit government support for financial institutions. These include the beginning of the 2007-8 financial crisis, the period after the failure of Lehman Brothers and the sovereign debt crisis starting in 2010. Measures like the one proposed in the paper are very welcome alternatives to the still more commonly used correlation based metrics.

The issue's third paper, "Network centrality, failure prediction and systemic risk" by Abalfazl Zareei, also addresses credit markets, by constructing networks based on correlations in credit default swap spreads. The author finds that a firm's centrality in a network can be used to increase the explanatory power of default prediction models, and that more peripheral firms have a higher likelihood of jump events and a higher bankruptcy probability. This is a promising new avenue of investigation into how information on firms' interconnectivity can improve existing credit models and a starting point for more research on this topic, especially research that also provides a theoretical underpinning for the effects found.

Last but not least, I want to mention that 2016 brings some exciting news regarding The Journal of Network Theory in Finance. The journal has been submitted for indexing in Web of Science to obtain an impact factor, and also to Scopus and EConLit. After a successful first year we are aiming to expand the reach of the journal and we hope that broader indexing will make the journal more useful for the researchers publishing in it, as well as making it more easily accessible to professionals who are interested in applications of network theory in finance.

Kimmo Soramäki
Financial Network Analytics Ltd.

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an indvidual account here: