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Juho Nyholm
- 10 March 2025
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 27Details
- Abstract
- Cyberattacks pose greater risk to financial stability than ever before as they have grown in both number and magnitude. A macroprudential perspective on cyber resilience stress testing is needed because cyber incidents can have a systemic impact as their effects spread across the financial sector via confidence, operational and financial mechanisms. While broader stress-testing principles also apply to cyber stress testing, stress testers need to focus in particular on clearly defining the overall objectives, determining the institutional perimeter, identifying material risk propagation channels, focusing on tail risks, considering relevant behavioural responses and combining the outcomes of bottom-up and top-down exercises. Based on these principles, cyber resilience stress tests can be executed following a bottom-up as well as a top-down approach. Top-down models can complement bottom-up results by providing harmonised modelling of system-wide financial interlinkages, behavioural responses and second-round effects.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
C63 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Computational Techniques, Simulation Modeling
- 12 February 2015
- WORKING PAPER SERIES - No. 1758Details
- Abstract
- This paper investigates leading indicators of systemic banking crises in a panel of 11 EU countries, with a particular focus on Finland. We use quarterly data from 1980Q1 to 2013Q2, in order to create a large number of macro-financial indicators, as well as their various transformations. We make use of univariate signal extraction and multivariate logit analysis to assess what factors lead the occurrence of a crisis and with what horizon the indicators lead a crisis. We find that loans-to-deposits and house price growth are the best leading indicators. Growth rates and trend deviations of loan stock variables also yield useful signals of impending crises. While the optimal lead horizon is three years, indicators generally perform well with lead times ranging from one to four years. We also tap into unique long time-series of the Finnish economy to perform historical explorations into macro-financial vulnerabilities.
- JEL Code
- E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F30 : International Economics→International Finance→General
G01 : Financial Economics→General→Financial Crises
G15 : Financial Economics→General Financial Markets→International Financial Markets
C43 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Index Numbers and Aggregation - Network
- Macroprudential Research Network