Ronald Heijmans
De Nederlandsche Bank
Ronald received his PhD from the University of Groningen in the field of Economics. His thesis was on large value payment systems. Prior to that he obtained an MSc in astrophysics from Leiden University. He worked for DNB over 14 years in the Payments and Financial Market Infrastructure Division as researcher and policy advisor. In 2018 and 2019 he was also connected to Payments Canada as a research advisor. In June 2020 he joined the data science hub within DNB as a senior data scientist. Ronald has contributed to the literature of payment systems and financial market infrastructure on topics like machine learning, artificial intelligence, risk indicators, bank’s liquidity, network topology and game theory. In this capacity he is associate editor of the Journal of financial market infrastructures. Lately, the main focus of his research is related to artificial intelligence and big data analysis in the field of financial market infrastructures. He also teaches “R for data science” for Tridata. Besides, he gives guest lectures at universities.
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Articles by Ronald Heijmans
Are cryptocurrencies cryptic or a source of arbitrage? A genetic algorithm approach
The authors identify triangular arbitrage trading opportunities through genetic algorithms in order to find insights into the volatility of cryptocurrencies and stablecoins with the largest market cap.
How much liquidity would a liquidity-saving mechanism save if a liquidity-saving mechanism could save liquidity? A simulation approach for Canada’s large-value payment system
This paper investigates how much liquidity requirements can be reduced with the implementation of different LSMs in the Financial Network Analytics simulation engine using LVTS transaction data from 2018.
Is there anybody out there? Detecting operational outages from Large Value Transfer System transaction data
This paper develops a method to identify operational outages of participants in the Canadian Large Value Transfer System (LVTS).
Near-real-time monitoring in real-time gross settlement systems: a traffic light approach
This paper develops a method to identify quantitative risks in financial market infrastructures (FMIs) that is inspired by the Principles for Financial Market Infrastructures.
FMIC 2 special issue introduction: a policy view on developments in the field of financial market infrastructures
This introductory article positions these papers and speeches within the context of the wider conference proceedings of the Financial Market Infrastructure Conference II: New Thinking in a New Era, including insights from the panel sessions and…
Granularity, a blessing in disguise: transaction cycles within real-time gross settlement systems
The authors of this paper take us into the world of granular time series data.
Dynamic visualization of large financial networks
This paper presents animated visualizations of transaction flows in the Dutch TARGET2 payment system.