C4 - Econometric and Statistical Methods: Special Topics

• Seasonal Adjustment of Weekly Data

  Staff Discussion Paper 2024-17 Jeffrey Mollins, Rachit Lumb

  The industry standard for seasonally adjusting data, X-13ARIMA-SEATS, is not suitable for high-frequency data. We summarize and assess several of the most popular seasonal adjustment methods for weekly data given the increased availability and promise of non-traditional data at higher frequencies.

  Content Type(s): Staff research, Staff discussion papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C4, C5, C52, C8, E, E0, E01, E2, E21

• Finding a Needle in a Haystack: A Machine Learning Framework for Anomaly Detection in Payment Systems

  Staff Working Paper 2024-15 Ajit Desai, Anneke Kosse, Jacob Sharples

  Our layered machine learning framework can enhance real-time transaction monitoring in high-value payment systems, which are a central piece of a country’s financial infrastructure. When tested on data from Canadian payment systems, it demonstrated potential for accurately identifying anomalous transactions. This framework could help improve cyber and operational resilience of payment systems.

  Content Type(s): Staff research, Staff working papers Topic(s): Digital currencies and fintech, Financial institutions, Financial services, Financial system regulation and policies, Payment clearing and settlement systems JEL Code(s): C, C4, C45, C5, C55, D, D8, D83, E, E4, E42