The Stability of Banking System with Shadow Banking on Different Interbank Network Structures

With the rapid development of the financial market, the outbreak of systemic risk is affected by many factors, among which shadow banking is considered to be the essential reason to cause financial crisis and destroy the stability of the banking system. In view of the stability of the banking system, considering shadow banking, interbank lending, and complex relationships between banks, a dynamic complex interbank network model with shadow banking under different network structures is proposed. Based on the model, the effects of ROI, investment periods, average deposit, deposit interest rate, the density of shadow banks, and asset loss are studied quantitatively, and the sensitivity and difference of the banking system with shadow banking under different interbank networks are compared and analyzed. The findings indicate that the spread of systemic risks between banks is closely related to the interbank network structures. With the relatively concentrated interbank network structure, it is easier to increase the probability and degree of risk contagion. Under the random, small-world, and scale-free networks, the random network has the strongest ability to resist and absorb risks, while the small-world network is the weakest. However, once the banking network suffers a big shock, excessive risk will directly break through the protection of the banking network, detonate the systematic risk, and destroy the stability of the banking system with shadow banking. This study contributes to a future empirical research agenda on the topic. Moreover, it gives a reference for policymakers and regulatory authorities to prevent systemic risk introduced by shadow banking.

Money creation, debt, and justice

Theories of justice rely on a variety of criteria to determine what social arrangements should be considered just. For most theories, the distribution of financial resources matters. However, they take the existence of money as a given and tend to ignore the way in which the creation of money impacts distributive justice. Those with access to collateral are favoured in the creation of credit or debt, which represents the main form of money today. Appealing to the idea that access to credit confers freedom, and that inequalities in this freedom are morally arbitrary, this article shows how the advantage to those with collateral plays out in different ways in today’s economy. The article identifies several forms of bias inherent in money creation, and its subsequent destruction: loans from commercial banks to individuals and corporations, interbank lending, lending from central banks to commercial banks, and selective bail-outs by central banks. These are not mere inequalities: they are unjust since alternative designs of the financial architecture exist that would significantly reduce them. The paper focuses on one possible reform with the potential to address several of the types of bias identified, namely the separation of money creation from private bank credit.

A Dynamic Network Model of Interbank Lending—Systemic Risk and Liquidity Provisioning

We develop a dynamic model of interbank borrowing and lending activities in which banks are organized into clusters, and adjust their monetary reserve levels to meet prescribed capital requirements. Each bank has its own initial monetary reserve level and faces idiosyncratic risks characterized by an independent Brownian motion, whereas system wide, the banks form a hierarchical structure of clusters. We model the interbank transactional dynamics through a set of interacting measure-valued processes. Each individual process describes the intracluster borrowing/lending activities, and the interactions among the processes capture the intercluster financial transactions. We establish the weak limit of the interacting measure-valued processes as the number of banks in the system grows large. We then use the weak limit to develop asymptotic approximations of two proposed macromeasures (the liquidity stress index and the concentration index), both capturing the dynamics of systemic risk. We use numerical examples to illustrate the applications of the asymptotics and conduct-related sensitivity analysis with respect to various indicators of financial activity.