Persistent liquidity shocks and interbank funding

Interbank funding, bank risk exposure and performance in the UK: A three-stage network DEA approach

“…Out of the 93 banks examined, a total of eight banks comprising three domestic and five international banks are efficient overall. Though earlier evidence that adopts the augmented structure of the network representation of production processes contends that increased structure may add discriminatory power (Galagedera et al, 2016;2018), this is not the case here. Of the eight banks that are overall efficient, two are efficient under the allied stage and performance stage, hence suggesting that a bank should be efficient if it is able to effectively manage its interbank exposure through effective risk management.…”

“…The interbank literature suggests that aggregate market information and market frictions are the primary causes of poor market functioning. These include information asymmetry (Heider et al, 2015), market power (Acharya et al, 2012), inefficient risk-sharing (Freixas et al, 2011), information contagion (Acharya and Yorulmazer, 2008), bank risk concentration (Lucchetta, 2015), aggregate liquidity shocks (Bluhm, 2018) and malfunctioning secondary markets (Diamond and Rajan, 2005). Further, the interbank network and systemic importance literature points to the complex web of exposures linking banks' balance sheets (Liu et al, 2013;Benoit et al, 2017), business models (Hryckiewicz and Kozłowski, 2017) and unequal liquidity distribution among banks (Hryckiewicz and Kozłowski, 2018) as key causes of the market failure 2 .…”

Systemic risk prevention policies targeting systemically important banks: Does clustering pattern matter?

“…Network models have been widely used to study the role of network structure in generating systemic risk and assess the risk transmission in the financial system [e.g., 7 , 27 – 32 ]. Among them, the micro-founded network model of Bluhm [ 7 ] describes the formation of financial networks, the propagation of shocks, and the emergence of systemic risk. Based on Bluhm’s [ 7 ] framework, we further embed a network optimization procedure in the network formation process.…”

“…Our work includes three steps. First, based on Bluhm [ 7 ] and Diem et al [ 8 ], this paper builds a banking network model embedded with a network optimization procedure to describe the network formulation process and risk contagion mechanism using the annual asset and liability data of four types of commercial banks in the Chinese market from 2010–2019. Second, the influences of SIBs’ connection tendency on systemic risk are analyzed.…”

A novel intelligent system for securing cash levels using Markov random fields

“…This section is specifically related to the LCR since it is intended for controlling whether the bank branches have sufficiently safe liquidity levels. In fact, the LCR was devised to be able to check if banks hold a sufficient reserve of high‐quality liquid assets that allow them to survive in conditions of significant liquidity stress lasting for 30 calendar days, see Reference [20]. Such tests are periodically performed not only to meet the external regulatory standards but also for internal security reasons to avoid dormant money at branches, since liquidity comes at a cost: keeping liquid assets in cash involves the corresponding opportunity costs of not investing in other alternative products which bring clear benefits, see Reference [7].…”