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Matthias Sydow
- 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
- 15 May 2024
- OCCASIONAL PAPER SERIES - No. 348Details
- Abstract
- This paper provides an overview of stress-testing methodologies in Europe, with a focus on the advancements made by the European Central Bank’s Financial Stability Committee Working Group on Stress Testing (WGST). Over a four-year period, the WGST played a pivotal role in refining stress-testing practices, promoting collaboration among central banks and supervisory authorities and addressing challenges in the evolving financial landscape. The paper discusses the development and application of various stress-testing models, including top-down models, macro-micro models and system-wide models. It highlights the integration of new datasets and model validation efforts as well as the expanded use of stress-testing methodologies in risk and policy evaluation and in communication. The collaborative efforts of the WGST have demystified stress-testing methodologies and fostered trust among stakeholders. The paper concludes by outlining the future agenda for continued improvements in stress-testing practices.
- 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
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
G01 : Financial Economics→General→Financial Crises
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
- 16 December 2022
- WORKING PAPER SERIES - No. 2757Details
- Abstract
- This paper develops a framework for the short-term modelling of market risk and shock propagation in the investment funds sector, including bi-layer contagion effects through funds’ cross-holdings and overlapping exposures. Our work tackles in particular climate risk, with a first-of-its-kind dual view of transition and physical climate risk exposures at the fund level. So far, while fund managers communicate more aggressively on their awareness of climate risk, it is still poorly assessed. Our analysis shows that the topology of the fund network matters and that both contagion channels are important in its study. A stress test on the basis of granular short-term transition shocks suggests that the differentiated integration of sustainability information by funds has made network amplification less likely, although first-round losses can be material. On the other hand, there is room for fund managers and regulators to consider physical risk better and mitigate the second round effects it induces, as they are less efficiently absorbed by investment funds. Improving transparency and setting relevant industry standards in this context would help mitigate short-term financial stability risks.
- JEL Code
- C62 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Existence and Stability Conditions of Equilibrium
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G17 : Financial Economics→General Financial Markets→Financial Forecasting and Simulation
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
- 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
- 31 October 2019
- WORKING PAPER SERIES - No. 2323Details
- Abstract
- This paper presents a model for stress testing investment funds, based on a broad worldwide sample of primary open-end equity and bond funds. First, we employ a Bayesian technique to project the impact of macro-financial scenarios on country-level portfolio flows worldwide that are constructed from fund-level asset holdings. Second, from these projected country-level flows, we model the scenarios’ repercussions on individual funds along a three year horizon. Importantly, we further decompose portfolio flows, disentangling the specific contributions of transactions, valuation and foreign exchange effects. Overall, our results indicate that the impact of a global adverse macro-financial scenario leads to a median depletion in assets under management (AUM) of 24% and 5%, for euro area-domiciled equity and bond funds respectively, largely driven by valuation effects. Scenario and results both present similarities to the global financial crisis. We use historical information on fund liquidations to estimate a threshold for a drop in AUM that signals a high likelihood of a forthcoming liquidation. Based on this, we estimate that 5.8% and 0.5% of euro area-domiciled equity and bond funds respectively could go into liquidation. Such empirical thresholds can be useful for the implementation of prudential policy tools, such as redemption gates.
- JEL Code
- F21 : International Economics→International Factor Movements and International Business→International Investment, Long-Term Capital Movements
G15 : Financial Economics→General Financial Markets→International Financial Markets
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
G28 : Financial Economics→Financial Institutions and Services→Government Policy and Regulation
- 11 October 2013
- OCCASIONAL PAPER SERIES - No. 152Details
- Abstract
- The use of macro stress tests to assess bank solvency has developed rapidly over the past few years. This development was reinforced by the financial crisis, which resulted in substantial losses for banks and created general uncertainty about the banking sector's loss-bearing capacity. Macro stress testing has proved a useful instrument to help identify potential vulnerabilities within the banking sector and to gauge its resilience to adverse developments. To support its contribution to safeguarding financial stability and its financial sector-related work in the context of EU/IMF Financial Assistance Programmes, and looking ahead to the establishment of the Single Supervisory Mechanism (SSM), the ECB has developed a top-down macro stress testing framework that is used regularly for forward-looking bank solvency assessments. This paper comprehensively presents the main features of this framework and illustrates how it can be employed for various policy analysis purposes.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
D85 : Microeconomics→Information, Knowledge, and Uncertainty→Network Formation and Analysis: Theory
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G01 : Financial Economics→General→Financial Crises
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
- 3 March 2009
- WORKING PAPER SERIES - No. 1019Details
- Abstract
- We apply a dynamic dividend-discount model to analyse unexpected housing returns in a panel of eight euro area countries which together comprise 90% of euro area GDP. The application of this model allows for a de-composition of house price movements into movements in rent (cash-flow) and expected return news components. The empirical application of the model involves the estimation of a panel vector autoregressive model (VAR) for four variables –excess return to housing, rents, the real interest rate and real disposable per capita income– using quarterly data over the period 1985-2007. This empirical investigation yields two main findings. First, the bulk of the variability of house price move-ments in the panel of countries analysed can be attributed to movements in the rental yield. Indeed, perturbations to rents appear to result in a one-to-one analogous movement in house prices over the long term once controlling for changes in expected returns. Second, evidence from the dynamic profile of shocks along with the negative co-movement between changing rental yield expectations and changing expected returns on housing assets would suggest that euro area house prices overreact to news.
- JEL Code
- R21 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Household Analysis→Housing Demand
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
- 11 February 2009
- WORKING PAPER SERIES - No. 1002Details
- Abstract
- In terms of regulatory and economic capital, credit risk is the most significant risk faced by banks. We implement a credit risk model - based on publicly available information - with the aim of developing a tool to monitor credit risk in a sample of large and complex banking groups (LCBGs) in the EU. The results indicate varying credit risk profiles across these LCBGs and over time. Furthermore, the results show that large negative shocks to real GDP have the largest impact on the credit risk profiles of banks in the sample. Notwithstanding some caveats, the results demonstrate the potential value of this approach for monitoring financial stability.
- JEL Code
- C02 : Mathematical and Quantitative Methods→General→Mathematical Methods
C19 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Other
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C61 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→Optimization Techniques, Programming Models, Dynamic Analysis
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
- 28 December 2006
- WORKING PAPER SERIES - No. 706Details
- Abstract
- We apply the Campbell-Shiller return decomposition to exchange rate returns and fundamentals in a stationary panel vector autoregression framework. The return decomposition is then used to analyse how different investor segments react to news as captured by the different return components. The results suggest that intrinsic value news are dominating for equity investors and speculative money market investors while investors in currency option markets react strongly to expected return news. The equity and speculative money market investors seem able to distinguish between transitory and permanent FX movements while options investors mainly focus on transitory movements. We also find evidence that offsetting impact on the various return components can blur the effect of macroeconomic data releases on aggregate FX excess returns.
- JEL Code
- C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
F31 : International Economics→International Finance→Foreign Exchange
F32 : International Economics→International Finance→Current Account Adjustment, Short-Term Capital Movements
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 29 September 2006
- WORKING PAPER SERIES - No. 677Details
- Abstract
- We combine the dynamic dividend-discount model with an accounting-based vector autoregression framework that allows for a decomposition of EU banks' stock returns to cash-flow and expected return news components. The main findings are that while the bulk of the variability of EU banks' stock returns is due to cash flow shocks, the expected return shocks are relatively more important for larger than for smaller banks. Moroever, variables used in the literature as cash-flow proxies explain a higher share of the cash-flow component of the total excess returns for smaller than for larger EU banks. This suggests that large banks could be more prone to market wide news and events - that in the literature are associated with the expected return news component - as opposed to the bank-specific news, typically assumed to be incorporated in the cash-flow component.
- JEL Code
- C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 9 June 2005
- OCCASIONAL PAPER SERIES - No. 30Details
- Abstract
- Chapter 1 provides an overview and assessment of the price competitiveness and export performance of the euro area and the larger euro area countries, as well as an evaluation of how standard equations have been able to explain actual export developments. Chapter 2 carries out a constant market share analysis for the euro area and thereby sheds light on the reasons for movements in aggregate export market shares by looking at the sectoral and geographical composition of euro area exports. Chapter 3 looks at the evolution of the technological competitiveness of the euro area and major competitors
- JEL Code
- E3 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles