Ruben Hipp - Latest

• Understanding Systemic Risks in the Canadian Financial System

  Staff analytical paper 2026-28 Gabriel Bruneau, Sascha Clazie-Thomson, Thibaut Duprey, Ruben Hipp, Javier Ojea Ferreiro, Kerem Tuzcuoglu

  This paper reviews recent efforts to monitor and assess systemic risk in the Canadian financial system and outlines a framework for future system-wide stress testing.

  Content Type(s): Staff research, Staff analytical paper JEL Code(s): G, G0, G01, G1, G17, G18, G2, G21, G23, G28 Research Theme(s): Financial system, Financial stability and systemic risk

• Decomposing Systemic Risk: The Roles of Contagion and Common Exposures

  Staff working paper 2024-19 Grzegorz Halaj, Ruben Hipp

  We examine systemic risks within the Canadian banking sector, decomposing them into three contribution channels: contagion, common exposures, and idiosyncratic risk. Through a structural model, we dissect how interbank relationships and market conditions contribute to systemic risk, providing new insights for financial stability.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C3, C32, C5, C51, G, G2, G21, L, L1, L14 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods, Economic models

• Forecasting Banks’ Corporate Loan Losses Under Stress: A New Corporate Default Model

  Technical report No. 122 Gabriel Bruneau, Thibaut Duprey, Ruben Hipp

  We present a new corporate default model, one of the building blocks of the Bank of Canada’s bank stress-testing infrastructure. The model is used to forecast corporate loan losses of the Canadian banking sector under stress.

  Content Type(s): Staff research, Technical reports JEL Code(s): C, C2, C22, C5, C52, C53, G, G1, G17, G2, G21, G28 Research Theme(s): Financial system, Financial stability and systemic risk, Household and business credit, Models and tools, Economic models

• Estimating Large-Dimensional Connectedness Tables: The Great Moderation Through the Lens of Sectoral Spillovers

  Staff working paper 2021-37 Felix Brunner, Ruben Hipp

  Understanding the size of sectoral links is crucial to predicting the impact of a crisis on the whole economy. We show that statistical learning techniques substantially outperform traditional estimation techniques when measuring large networks of these links.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C2, C22, C5, C52, E, E2, E23, E27 Research Theme(s): Models and tools, Econometric, statistical and computational methods, Monetary policy, Real economy and forecasting

• On Causal Networks of Financial Firms: Structural Identification via Non-parametric Heteroskedasticity

  Staff working paper 2020-42 Ruben Hipp

  Banks’ business interactions create a network of relationships that are hidden in the correlations of bank stock returns. But for policy interventions, we need causality to understand how the network changes. Thus, this paper looks for the causal network anticipated by investors.

  Content Type(s): Staff research, Staff working papers JEL Code(s): C, C1, C3, C32, C5, C58, L, L1, L14 Research Theme(s): Financial system, Financial stability and systemic risk, Models and tools, Econometric, statistical and computational methods