We present a novel approach that incorporates individual entity stress testing and losses from systemic risk effects (SE losses) into macroprudential stress testing. SE losses are measured using a reduced-form model to value financial entity assets, conditional on macroeconomic stress and the distress of other entities in the system. This valuation is made possible by a multivariate density which characterizes the asset values of the financial entities making up the system. In this paper this density is estimated using CIMDO, a statistical approach, which infers densities that are consistent with entities’ probabilities of default, which in this case are estimated using market-based data. Hence, SE losses capture the effects of interconnectedness structures that are consistent with markets’ perceptions of risk. We then show how SE losses can be decomposed into the likelihood of distress and the magnitude of losses, thereby quantifying the contribution of specific entities to systemic contagion. To illustrate the approach, we quantify SE losses due to Lehman Brothers’ default.
This paper presents the Systemic Risk and Interconnectedness (SyRIN) tool. SyRIN allows a comprehensive assessment of systemic risk via quantification of the impact of risk amplification mechanisms, due to interconnectedness structures across banks and other financial intermediaries—insurance, pension fund, hedge fund and investment fund sectors, which cannot be captured when analyzing sectors independently. The tool produces various metrics to evaluate systemic risk from complementary perspectives, including tail risk, cross-entity interconnectedness and the contribution to systemic risk by different entities and sectors. SyRIN is easily implementable with publicly available data and can be adapted to cater to different degrees of institutional granularity and data availability. The framework is designed to be a tool to identify vulnerabilities from a top-down perspective that can lead to deeper analysis in specific sectors for policy formulation.
Macroprudential stress testing (MaPST) is becoming firmly embedded in the post-crisis policy-frameworks of financial-sectors around the world. MaPSTs can offer quantitative, forward-looking assessments of the resilience of financial systems as a whole, to particularly adverse shocks. Therefore, they are well suited to support the surveillance of macrofinancial vulnerabilities and to inform the use of macroprudential policy-instruments. This report summarizes the findings of a joint-research effort by MCM and the Systemic-Risk-Centre, which aimed at (i) presenting state-of-the-art approaches on MaPST, including modeling and implementation-challenges; (ii) providing a roadmap for future-research, and; (iii) discussing the potential uses of MaPST to support policy.
We propose an original method to estimate the market price of risk under stress, which is needed to correct for risk aversion the CDS-implied probabilities of distress. The method is based, for simplicity, on a one-factor asset pricing model. The market price of risk under stress (the expectation of the market price of risk, conditional on it exceeding a certain threshold) is computed from the price of risk (which is the variance of the market price of risk) and the discount factor (which is the inverse of the expected market price of risk). The threshold is endogenously determined so that the probability of the price of risk exceeding it is also the probability of distress of the asset. The price of risk can be estimated via different methods, for instance derived from the VIX or from the factors in a Fama-MacBeth regression.
Over the past year, euro area sovereign spreads have exhibited an unprecedented degree of volatility. This paper explores how much of these large movements reflected shifts in (i) global risk aversion (ii) country-specific risks, directly from worsening fundamentals, or indirectly from spillovers originating in other sovereigns. The analysis shows that earlier in the crisis, the surge in global risk aversion was a significant factor influencing sovereign spreads, while recently country-specific factors have started playing a more important role. The perceived source of contagion itself has changed: previously, it could be found among those sovereigns hit hard by the financial crisis, such as Austria, the Netherlands, and Ireland, whereas lately the countries putting pressure on euro area government bonds have been primarily Greece, Portugal, and Spain, as the emphasis has shifted towards short-term refinancing risk and long-term fiscal sustainability. The paper concludes that debt sustainability and appropriate management of sovereign balance sheets are necessary conditions for preventing sovereign risk from feeding back into broader financial stability concerns.
We propose a framework to link empirical models of systemic risk to theoretical network/ general equilibrium models used to understand the channels of transmission of systemic risk. The theoretical model allows for systemic risk due to interbank counterparty risk, common asset exposures/fire sales, and a “Minsky" cycle of optimism. The empirical model uses stock market and CDS spreads data to estimate a multivariate density of equity returns and to compute the expected equity return for each bank, conditional on a bad macro-outcome. Theses “cross-sectional" moments are used to re-calibrate the theoretical model and estimate the importance of the Minsky cycle of optimism in driving systemic risk.
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