The third issue of The Journal of Network Theory in Finance again shows the topical nature and wide applicability of network models. The issue features three papers covering topics related to financial stability, group lending and financial markets stress.
The first paper, "Too interconnected to fail: a survey of the interbank networks literature" by Anne-Caroline Hüser, reviews the literature on interbank networks with a focus on theoretical work. A substantial body of this literature has been developed since the financial crisis of 2007-8, and it has become clear that understanding interlinkages among financial institutions is critical for financial stability analysis. This review surveys the literature and identifies gaps in analysis. These gaps include the need to better combine theoretical models with empirical findings on real topologies in order to better understand indirect linkages or channels of contagion that manifest themselves through fire sales or credit risk transfers, and to establish better links to the more established macrofinance literature that is tackling similar problems. The review highlights the advances made in recent years and will be of great interest to policy makers. However, I would mention one more gap in current research. It is critical to develop insights into how modeling results are translated into effective policy decisions if this research is to find wide application.
Our second paper, "Group lending to a borrower network: a partial joint liability model" by Usha Sridhar and Sridhar Mandyam, opens up a brand new avenue of research by using network theory to develop models for credit decisions in group lending schemes. The proposed mathematical model is based on borrowers' bilateral trust relationships and is combined with incentive payments for the group to collectively perform on the loans. The scheme taps into the social idea of the community acting as borrowers, which is likely to strengthen performance of the loans compared with monetary incentives alone. This paper tackles the important topic of the provision of finance to people and ventures that are not currently served by traditional credit institutions, and it provides a real and novel solution to the problem. I can very well see approaches like these being adopted both in developing economies and also by the rapidly evolving financial technology sector in mature economies, where much innovation is currently taking place.
The issue's third paper, "Network-based measures as leading indicators of market instability: the case of the Spanish stock market" by Gustavo Peralta, identifies links between time series data of stock returns for the purpose of understanding the structure of the market and for identifying early-warning signals of forthcoming market stress. For this purpose the proposed model uses partial correlations that are filtered with a graphical lasso algorithm. Several different methodologies for identifying links among assets in financial markets have been proposed in recent literature. The litmus test for each of these is how useful they are for the task at hand - be that managing risks, asset allocation and trading strategies, or early warning of financial stress on a macro level. The paper finds compelling evidence that properties of the Spanish stock market could be used as leading indicators of market distress, and will surely be of interest to macro fund managers and financial regulators, among others.
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This paper uses network theory to develop models for credit decisions in group lending schemes.
This paper systematically reviews the theoretical literature on interbank networks.
Network-based measures as leading indicators of market instability: the case of the Spanish stock market
This paper identifies links between time series data of stock returns for the purpose of understanding the structure of the market and for identifying early-warning signals of forthcoming market stress.