Near real-time monitoring in real-time gross settlement systems: A traffic light approach

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This paper develops a method to identify quantitative risks in financial market infrastructures (FMIs), which are inspired by the Principles for Financial Market Infrastructures. We convert transaction level data into indicators that provide information on operational risk, concentration risk and liquidity dependencies. As a proof of concept we use TARGET2 data. The indicators are based on legislation, guidelines and their own history. Indicators that are based on their own history are corrected for cyclical patterns. Our method includes a setup of the signaling threshold of relevant changes. For the signaling, we opt for a traffic light approach: a green, amber or red light for a small, moderate or substantial change in the indicator, respectively. The indicators developed in this paper can be used by overseers/regulators, operators of FMIs and by financial stability experts.
Original languageEnglish
JournalThe Journal of Risk
Publication statusAccepted/In press - 2019

Fingerprint

Monitoring
Financial markets
Financial stability
Liquidity
Operational risk
Operator
Legislation

Cite this

@article{662390bd851e4011ad7ddf0cad9be9fd,
title = "Near real-time monitoring in real-time gross settlement systems: A traffic light approach",
abstract = "This paper develops a method to identify quantitative risks in financial market infrastructures (FMIs), which are inspired by the Principles for Financial Market Infrastructures. We convert transaction level data into indicators that provide information on operational risk, concentration risk and liquidity dependencies. As a proof of concept we use TARGET2 data. The indicators are based on legislation, guidelines and their own history. Indicators that are based on their own history are corrected for cyclical patterns. Our method includes a setup of the signaling threshold of relevant changes. For the signaling, we opt for a traffic light approach: a green, amber or red light for a small, moderate or substantial change in the indicator, respectively. The indicators developed in this paper can be used by overseers/regulators, operators of FMIs and by financial stability experts.",
author = "Ron Berndsen and Ronald Heijmans",
year = "2019",
language = "English",
journal = "The Journal of Risk",
issn = "1465-1211",
publisher = "Incisive Media Ltd.",

}

Near real-time monitoring in real-time gross settlement systems : A traffic light approach. / Berndsen, Ron; Heijmans, Ronald.

In: The Journal of Risk, 2019.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Near real-time monitoring in real-time gross settlement systems

T2 - A traffic light approach

AU - Berndsen, Ron

AU - Heijmans, Ronald

PY - 2019

Y1 - 2019

N2 - This paper develops a method to identify quantitative risks in financial market infrastructures (FMIs), which are inspired by the Principles for Financial Market Infrastructures. We convert transaction level data into indicators that provide information on operational risk, concentration risk and liquidity dependencies. As a proof of concept we use TARGET2 data. The indicators are based on legislation, guidelines and their own history. Indicators that are based on their own history are corrected for cyclical patterns. Our method includes a setup of the signaling threshold of relevant changes. For the signaling, we opt for a traffic light approach: a green, amber or red light for a small, moderate or substantial change in the indicator, respectively. The indicators developed in this paper can be used by overseers/regulators, operators of FMIs and by financial stability experts.

AB - This paper develops a method to identify quantitative risks in financial market infrastructures (FMIs), which are inspired by the Principles for Financial Market Infrastructures. We convert transaction level data into indicators that provide information on operational risk, concentration risk and liquidity dependencies. As a proof of concept we use TARGET2 data. The indicators are based on legislation, guidelines and their own history. Indicators that are based on their own history are corrected for cyclical patterns. Our method includes a setup of the signaling threshold of relevant changes. For the signaling, we opt for a traffic light approach: a green, amber or red light for a small, moderate or substantial change in the indicator, respectively. The indicators developed in this paper can be used by overseers/regulators, operators of FMIs and by financial stability experts.

M3 - Article

JO - The Journal of Risk

JF - The Journal of Risk

SN - 1465-1211

ER -