1,677 research outputs found

    Optimizing Liquidity Usage and Settlement Speed in Payment Systems

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    The operating speed of a payment system depends on the stage of technology of the system's communication and information processing environment. Frequent intraday processing cycles and real-time processing have introduced new means of speeding up the processing and settlement of payments. In a real-time environment banks face new challenges in liquidity management. They need to plan for intraday as well as interday fluctuations in liquidity. By employing various types of hybrid settlement structures, banks may be able to even out intraday fluctuations in liquidity demand. The aim of this study is to develop a framework for analysing fluctuations in liquidity demand and assessing the efficiency of different settlement systems in terms of speed and liquidity needs. In this study we quantify the relationship between liquidity usage and settlement delay in net settlement systems, real-time gross settlement systems and hybrid systems, as well as the combined costs of liquidity and delay in these systems. We analyse ways of reducing costs via optimization features such as netting of queues, offsetting of payments and splitting of payments. We employ a payment system simulator developed at the Bank of Finland, which enables us to evaluate the impact of changes in system parameters and thus to compare the effects of alternative settlement schemes with given payment flows. The data used covers 100 days of actual payments processed in the Finnish BoF-RTGS system. Our major findings relate to risk reduction via real-time settlement, effects of optimization routines in hybrid systems, and the effects of liquidity costs on banks' choice of settlement speed. A system where settlement takes place continuously in real-time and with queuing features is more efficient from the perspective of liquidity and risks than a net settlement system with batch processing. Real-time processing enables a reduction in payment delay and risks without necessarily increasing liquidity needs. Participants will operate under immediate payment/settlement if liquidity costs are low enough relative to delay costs and if the liquidity arrangements are sufficiently flexible. The central bank can therefore support risk reduction and payment speed objectives by providing low cost intraday liquidity as well as more flexible ways for participants to add or withdraw liquidity from the system. Optimizing and gridlock solving features were found to be effective at very low levels of liquidity. The efficiency of the different optimization methods for settlement systems are affected by the actual flow of payments processed. Gains from netting schemes with multiple daily netting cycles were found to be somewhat more limited.payment systems; clearing/settlement; liquidity; efficiency; gridlock

    'Datafication': Making sense of (big) data in a complex world

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    This is a pre-print of an article published in European Journal of Information Systems. The definitive publisher-authenticated version is available at the link below. Copyright @ 2013 Operational Research Society Ltd.No abstract available (Editorial

    Operational Disruption and the Hungarian Real Time Gross Settlement System (VIBER)

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    Central bankers wish to ensure worldwide that large-value transfer systems, as a component of the key market infrastructure, exhibit sufficiently robust levels of operational resilience. We focus on the operational resilience of the Hungarian real time gross settlement system, known as VIBER. The goal of the research is the quantitative assessment of the ability of the system to withstand certain types of operational shocks. Systemically important participants are identified and it is argued that they overlap with endangered participants. An indicative list of participants who might be endangered by a liquidity shock is compiled by analysing proxies for liquidity risk. We shed light on the capacity of the system to function smoothly in the event of operational problems by simulating the technical default of one or two systemically important participants in VIBER. Altogether six plausible scenarios were formed, three entire-day incidents and three incidents involving less time (part-time incidents). The impact of behavioural reactions of technically non-defaulted participants and the application of existing backup procedures are also considered. The disturbance in the payment system was measured by the value of initially not submitted payments, the value of rejected payments, the total value of queued payments, the maximum queue value, the average queue length and the settlement delay. By means of gross and net liquidity deficit indicators, liquidity assistance required to settle all previously rejected transactions is calculated. By comparing the value of unsettled payments with the value of eligible collaterals in the banks’ balance sheet, we can gain insight into whether the liquidity deficit can be financed through normal monetary policy operations.real-time gross settlement, large-value transfer system, operational risk, shock-absorbing capacity.

    Designing large value payment systems: An agent-based approach

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    The purpose of this paper is to show how agent-based simulations of payment systems can be used to aid central bankers and payment system operators in thinking about the appropriate design of payment settlement systems to minimise risk and increase their efficiency. Banks, which we model as the �agents�, are capable of a degree of autonomy with which to respond to payment system rules and adopt a strategy that determines how much collateral to post with the central bank at the start of the day (equivalently how much liquidity to borrow intraday from the central bank) and when to send payment orders to the central processor. An interbank payment system with costly liquidity requires banks to solve an intraday cash management problem, minimising their liquidity and delay costs subject to their beliefs about what the other banks are doing. Some preliminary results are given on how banks learn to endogenously determine how much liquidity to post in the interbank liquidity management game.

    Smooth heaps and a dual view of self-adjusting data structures

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    We present a new connection between self-adjusting binary search trees (BSTs) and heaps, two fundamental, extensively studied, and practically relevant families of data structures. Roughly speaking, we map an arbitrary heap algorithm within a natural model, to a corresponding BST algorithm with the same cost on a dual sequence of operations (i.e. the same sequence with the roles of time and key-space switched). This is the first general transformation between the two families of data structures. There is a rich theory of dynamic optimality for BSTs (i.e. the theory of competitiveness between BST algorithms). The lack of an analogous theory for heaps has been noted in the literature. Through our connection, we transfer all instance-specific lower bounds known for BSTs to a general model of heaps, initiating a theory of dynamic optimality for heaps. On the algorithmic side, we obtain a new, simple and efficient heap algorithm, which we call the smooth heap. We show the smooth heap to be the heap-counterpart of Greedy, the BST algorithm with the strongest proven and conjectured properties from the literature, widely believed to be instance-optimal. Assuming the optimality of Greedy, the smooth heap is also optimal within our model of heap algorithms. As corollaries of results known for Greedy, we obtain instance-specific upper bounds for the smooth heap, with applications in adaptive sorting. Intriguingly, the smooth heap, although derived from a non-practical BST algorithm, is simple and easy to implement (e.g. it stores no auxiliary data besides the keys and tree pointers). It can be seen as a variation on the popular pairing heap data structure, extending it with a "power-of-two-choices" type of heuristic.Comment: Presented at STOC 2018, light revision, additional figure
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