Gábor Fukker
- 17 September 2025
- WORKING PAPER SERIES - No. 3114Details
- Abstract
- This paper investigates the effects of monetary policy on banks and non-bank financial institutions (NBFIs), with particular attention to the role of financial stress. We use high-frequency identified monetary policy shocks and state-dependent local projections to capture non-linear responses across financial sectors. Drawing on aggregated balance sheet data, including total assets, debt securities, and loans, we find that monetary tightening leads to broad-based contractions in total assets and debt holdings, with particularly pronounced effects for banks and investment funds. Loan responses are more heterogeneous, but money market funds and pension funds exhibit notable declines in loan exposures, especially under high-stress conditions. Importantly, we find that financial stress significantly amplifies the contractionary effects of monetary policy across all sectors and asset classes. Our results highlight the differentiated roles and vulnerabilities of financial intermediaries in the transmission of monetary policy and underline the importance of financial conditions in determining its overall effectiveness.
- JEL Code
- E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors - Network
- Challenges for Monetary Policy Transmission in a Changing World Network (ChaMP)
- 14 November 2024
- WORKING PAPER SERIES - No. 3000Details
- Abstract
- This paper documents the extension of the system-wide stress testing framework of the ECB with the insurance sector for a more thorough assessment of risks to financial stability. The special nature of insurers is captured by the modelling of the liability side and its loss absorbing capacity of technical provisions as the main novel feature of the model. Leveraging on highly granular data and information on bilateral exposures, we assess the impact of liquidity and solvency shocks and demonstrate how a combined endogenous reactions of banks, investment funds and insurance companies can further amplify losses in the financial system. The chosen hypothetical scenario and subsequent simulation results show that insurers’ ability to transfer losses to policyholders reduces losses for the entire financial sector. Furthermore, beyond a certain threshold, insurance companies play a crucial role in mitigating both direct and indirect contagion.
- JEL Code
- D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
- 1 August 2022
- WORKING PAPER SERIES - No. 2692Details
- Abstract
- Overlapping portfolios constitute a well-recognised source of risk, providing a channel for financial contagion induced by the market price impact of asset deleveraging. We introduce a novel method to assess the market price impact on a security-by-security basis from historical daily traded volumes and price returns. Systemic risk within the euro area financial system of banks and investment funds is then assessed by considering contagion between individual institutions’ portfolio holdings under a severe stress scenario. As a result, we show how the bias of more homogeneous estimation techniques, commonly employed for market impact, might lead to loss estimates that are more than twice as large as losses estimated with heterogeneous price impact parameters. Another new feature in this work is the application of a price-at-risk measure instead of the average market price impact to evaluate the tail risk of possible market price movements in scenarios of different severity. Our results also show that system-level losses at the tail can be three times higher than average losses using the same scenario.
- JEL Code
- G01 : Financial Economics→General→Financial Crises
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
- 13 June 2022
- MACROPRUDENTIAL BULLETIN - ARTICLE - No. 17Details
- Abstract
- A system-wide stress testing framework allows for a comprehensive assessment of the financial impact of severe climate risk scenarios. The combined reactions of banks, investment funds and insurers to climate stress amplify losses in the financial system.
- JEL Code
- D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
- 6 August 2021
- WORKING PAPER SERIES - No. 2581Details
- Abstract
- This paper shows how the combined endogenous reaction of banks and investment funds to an exogenous shock can amplify or dampen losses to the financial system compared to results from single-sector stress testing models. We build a new model of contagion propagation using a very large and granular data set for the euro area. Based on the economic shock caused by the Covid-19 outbreak, we model three sources of exogenous shocks: a default shock, a market shock and a redemption shock. Our contagion mechanism operates through a dual channel of liquidity and solvency risk. The joint modelling of banks and funds provides new insights for the assessment of financial stability risks. Our analysis reveals that adding the fund sector to our model for banks leads to additional losses through fire sales and a further depletion of banks’ capital ratios by around one percentage point.
- JEL Code
- D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks
- 19 May 2021
- WORKING PAPER SERIES - No. 2554Details
- Abstract
- In this paper we present a methodology of model-based calibration of additional capital needed in an interconnected financial system to minimize potential contagion losses. Building on ideas from combinatorial optimization tailored to controlling contagion in case of complete information about an interbank network, we augment the model with three plausible types of fire sale mechanisms. We then demonstrate the power of the methodology on the euro area banking system based on a network of 373 banks. On the basis of an exogenous shock leading to defaults of some banks in the network, we find that the contagion losses and the policy authority's ability to control them depend on the assumed fire sale mechanism and the fiscal budget constraint that may or may not restrain the policy authorities from infusing money to halt the contagion. The modelling framework could be used both as a crisis management tool to help inform decisions on capital/liquidity infusions in the context of resolutions and precautionary recapitalisations or as a crisis prevention tool to help calibrate capital buffer requirements to address systemic risks due to interconnectedness.
- JEL Code
- C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
G01 : Financial Economics→General→Financial Crises
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
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
L14 : Industrial Organization→Market Structure, Firm Strategy, and Market Performance→Transactional Relationships, Contracts and Reputation, Networks