Payment systems constitute a critical aspect of modern economic infrastructure; yet understanding the payment system mechanisms remains elusive in the face of rapidly evolving financial markets and intricate institutional linkages. Computer simulations of payment systems have proven useful in determining optimal balances of risk, efficiency, and liquidity usage. Constructs such as gridlock-resolution algorithms and liquidity-saving mechanisms are now routinely applied in such areas as optimization of liquidity and payment delay, but can also be used to assess potential impacts of changes in policy or system setups. In addition, simulations can be extended to incorporate behavioral elements of participants by modeling their behavior with Agent-Based Modeling (ABM). The 2008 global financial crisis has increased interest in simulations to identify and quantify risk, particularly where new channels of contagion and complex interlinkages of markets and payment systems are involved. Payment system simulations offer central bank authorities broad possibilities to improve their risk monitoring and should be incorporated as a standard part of financial stability analysis.
The paper reports the outcome of the stress-testing of liquidity risk in the TARGET2 payment system, with the study having been conducted by an ad-hoc group composed of operators and overseers of TARGET2. The study aims to assess the resilience of the system, defined as the network of its participants, and the appropriateness of liquidity levels under tightened liquidity conditions. The scenarios analysed are based on extreme shocks to the value of collateral of different levels and types that lead to a decrease in the intraday credit lines available in TARGET2 and, as a result, the payment capacity of TARGET2 participants. The tool used to perform these stress tests is the TARGET2 simulator, which provides access to real transaction level data and allows simulations to be run by changing parameters, in this case the credit lines. The period under analysis is one maintenance period for the years 2008 to 2013. In general, the stress-testing indicates that the system is resilient under the stress scenarios; liquidity levels seem to be appropriate and supported by the efficient liquidity management features of TARGET2. Even in the worst simulated event of a 70% drop in all collateral value, 80-90% of TARGET2 turnover would have been settled. The scenario results take also into account that the period under analysis was characterised by unconventional monetary policy measures.
The large amount of data and the need to perform large numbers of simulations of payment systems are a challenge and a starting point for this paper. Parallel and distributed simulation systems are widely used in many applications such as in military applications and entertainment. Parallel computing has been applied in other econometric areas such as VAR models but not in payment system simulations. In this empirical paper, a reduction in total execution times of payment system simulations is studied by exploiting computational parallelization in a one multicore PC environment. The preliminary results of parallel simulations are reported and the possible benefits of analyzing financial market infrastructures using this technique are discussed. This information can be very useful for choosing a parallelization strategy and designing the next generation platforms for parallel processing of payment and securities settlement system simulations. This is the first time parallel computing techniques have been applied to payment system simulations.
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