First, I would like to congratulate the new editor-in-chief of The Journal of Network Theory in Finance, Professor Tiziana Di Matteo from King’s College London. Di Matteo has been coediting the journal for the past year and is in an excellent position to ensure the success and expansion of the journal in the future. I will remain an active member of the editorial board and focus on applying the very methods and approaches presented in The Journal of Network Theory in Finance in practice. Before 2017 draws to a close, my company, FNA, will be launching a service at www.fnalab.com, where – for free – researchers can replicate, test and build new methods in network theory in finance, including those presented in the journal.
At the same time, we would like to give a warm welcome to Sarah Campbell, the new journals manager. She will be taking over from Carolyn Moclair, who we thank and wish all the best in her new endeavors.
We are very glad to see that this third issue for 2017 is macro-focused. The first paper investigates global financial and trade networks, the second paper looks at systemic risk in the interbank market, and the third paper considers the interconnectedness of global financial markets.
“Ranking the economic importance of countries and industries” by Wei Li, Dror Y. Kenett, Kazuko Yamasaki, H. Eugene Stanley and Shlomo Havlin is the first paper in this issue. In it, the authors develop a world economic network based on a world input–output table (WIOT) on the supply and purchase relationships within and across national economies. The authors begin by mapping these relationships and then develop a cascading failure model in order to measure how stress on selected countries and industries propagates throughout the network. This allows the authors to draw conclusions about the importance of countries and industries in the world economy as well as identify possible sources of global vulnerabilities. This paper will be of particular interest to policymakers and professionals applying “global macro” investment strategies.
The issue’s second paper, “Systemic risk management in financial networks with credit default swaps” by Matt V. Leduc, Sebastian Poledna and Stefan Thurner, evaluates how credit default swaps (CDSs) could be used to reduce systemic risk in the interbank market by shifting exposures into a more stable network topology. As a way of doing this, the authors evaluate the effects of a systemic insurance surcharge, which is added to the CDS spread of contracts that increase systemic risk. By means of an agent-based model, they demonstrate that such a system is more resilient to failures than a system without the systemic risk-based surcharges on CDS contracts. This paper will also be of interest to policymakers, as it looks to answer a key question: how do we shape financial networks to be more resilient toward systemic risk?
Leonidas Sandoval Junior’s “Networks of log returns and volatilities of international stock market indexes”, the third paper in this issue, measures interdependence in global financial markets and draws links with the literature on similarity-based net- works. The author uses the correlation of log returns and volatility as well as transfers entropy, both on a contemporaneous and a lagged basis, as his basis of measurement. This paper finds that many markets became highly interdependent during the financial crisis in 2007–8, the European sovereign debt crisis in 2010 and more recently in 2015, and that the interdependencies have become subdued since. Monitoring the evolution of correlations is important, as in the recent past investors have sought diversification through global markets. Also, many derivatives instruments (such as asset-backed securities) are based on assumptions of low correlations that may not continue to hold, changing the risk profile of the assets.
Kimmo Soramäki and Tiziana Di Matteo
Financial Network Analytics Ltd. and King’s College London
The authors present a methodological framework for quantifying interdependencies in the global market and for evaluating risk levels in the worldwide financial network.
In this paper the authors study insolvency cascades in an interbank system, in which banks are permitted to insure their loans with credit default swaps sold by other banks.
In this paper, the author builds dynamic networks based on correlation and transfer entropy, using both the log returns and the volatilities of 97 stock market indexes from various parts of the world between 2000 and 2016