Journal of Network Theory in Finance
Editor-in-chief: Ron Berndsen
Volume 4, Number 3 (September 2018)
Welcome to the third issue of Volume 4 of The Journal of Network Theory in Finance.
We start this volume with the paper “Computational analysis of structural properties of economic and financial networks” by Frank Emmert-Streib, Aliyu Musa, Kestutis Baltakys, Juho Kanniainen, Shailesh Tripathi, Olli Yli-Harja, Herbert Jodlbauer and Matthias Dehmer. This is a nice review on the use of networks and network-based methods to study economic problems. It highlights the usefulness of network-type instruments in understanding financial and economic systems, with the aim of making the study of economic networks more popular and accessible in the economics and finance literature. The paper discusses interesting applications in economics, including network games, labor markets, international trade and social networks, as well as applications in finance with an emphasis on systemic risk. I agree with the authors that complex systems and networks offer the potential for better analysis and monitoring of research on topics such as systemic risk in financial systems, and that it is important for the development of such topics to have journals publishing truly multidisciplinary papers. I am proud that The Journal of Network Theory in Finance is a part of this. Indeed, our past volumes contain several papers discussing a variety of interesting topics from both empirical and theoretical perspectives.
Our second paper offers another excellent contribution to the understanding of how distress can propagate over financial networks. This is by Sadamori Kojaku, Giulio Cimini, Guido Caldarelli and Naoki Masuda and is titled “Structural changes in the interbank market across the financial crisis from multiple core–periphery analysis”. It offers a study on the electronic market for interbank deposits (eMID) and uses a novel core–periphery detection method to show that the network is characterized by multiple core–periphery pairs. The authors’ results show that the market features a main core–periphery pair that is mostly composed of Italian banks, a second, smaller core–periphery pair of foreign banks, and many other smaller core–periphery pairs. The method also detects bipartite patterns for long (quarterly and monthly) and short (weekly and daily) data aggregation periods as well as the transition from core– periphery to bipartite structures that occurs by shortening the temporal scale of data aggregation.
“Networks of common asset holdings: aggregation and measures of vulnerability” by Anton Braverman and Andreea Minca, our third and final paper, also contributes nicely to the growing literature on financial networks and quantifies the interrelations induced by common asset holdings among financial institutions. A network representation emerges, where nodes represent portfolios and edge weights aggregate the common asset holdings and the liquidity of these holdings. The network construction has some important side implications for asset pricing. The ability to quantify these links is a keystone in understanding the systemic risk due to common asset holdings. In particular, this paper introduces a simple model of order imbalance that estimates price impacts due to liquidity shocks. In this model, asset prices are set by a competitive risk-neutral market maker, and the arrival rates for the buyers and sellers depend on the common asset holdings. No exogenous parameters such as asset correlations are required, and the network of common asset holdings can be thought of as a partial dependence structure among portfolio returns. The main focus of this paper is on vulnerabilities, and the use of mutual fund data helps to show that the vulnerability index is useful in predicting returns in periods of mass liquidation. In such periods, authors are able to identify vulnerable funds based on asset holdings and the liquidity characteristics of the stocks.
Let me end this editorial letter by thanking the authors of this volume for their valuable contributions, and by reminding our readers and potential authors that The Journal of Network Theory in Finance is included in a number of scholarly indexes. In addition to appearing in the Clarivate Analytics Emerging Sources Citation Index, we are listed in EconLit, EconBiz and Cabell’s Directory. We are working toward increasing our journal’s impact by including high-quality, peer-reviewed papers, and we are seeing good growth in our citations.
Let me also congratulate the following winners, who were awarded these prizes during the NetSci 2018 conference (www.netsci2018.com).
(1) “The Journal of Network Theory in Finance Best Poster Award”, awarded to Samuel Unicomb, Gerardo Iniguez, Janos Kertesz, Diana Knipl and Marton Karsaiand for “Threshold driven contagion on multiplex networks”, presented by Samuel Unicomb.
(2) “The Journal of Network Theory in Finance Best Paper Award”, awarded to Andrea Zaccaria, Lorenzo Napolitano, Luciano Pietronero and Emanuele Pugliese for “Firms’ complexity: technological scope, coherence and perfor- mance”, presented by Andrea Zaccaria.
(3) An iPad mini, our raffle prize (contestants submitted a business card for a chance to win an iPad mini), awarded to Federico Musciotto.
Tiziana Di Matteo
King’s College London
Papers in this issue
Computational analysis of structural properties of economic and financial networks
This paper surveys the use of networks and network-based methods to study economy- related questions.
Structural changes in the interbank market across the financial crisis from multiple core–periphery analysis
In this work, the authors employ the KM–ER algorithm to characterize the internal organization of eMID.
Networks of common asset holdings: aggregation and measures of vulnerability
This paper quantifies the interrelations induced among financial institutions by common asset holdings.