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John Theal

29 August 2012
Severe financial turbulences are driven by high impact and low probability events that are the characteristic hallmarks of systemic financial stress. These unlikely adverse events arise from the extreme tail of a probability distribution and are therefore very poorly captured by traditional econometric models that rely on the assumption of normality. In order to address the problem of extreme tail events, we adopt a mixture vector autoregressive (MVAR) model framework that allows for a multi-modal distribution of the residuals. A comparison between the respective results of a VAR and MVAR approach suggests that the mixture of distributions allows for a better assessment of the effect that adverse shocks have on counterparty credit risk, the real economy and banks' capital requirements. Consequently, we argue that the MVAR provides a more accurate assessment of risk since it captures the fat tail events often observed in time series of default probabilities.
JEL Code
C15 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Statistical Simulation Methods: General
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
Macroprudential Research Network
23 September 2014
Securities financing transaction (SFT) markets and the management and usage of collateral are elements of the financial system which are of systemic relevance. As such, there is a clear need for enhanced transparency and regulatory oversight. The European Systemic Risk board (ESRB) mandated a task force to identify the potential risks related to SFTs in Europe and to develop policy proposals to better monitor any vulnerabilities identified by the analysis. This report presents the results of two data collection exercises that were conducted to gain some initial insights into the structure of the SFT market and the correlated practices adopted by market participants concerning the re-investment or the re-use of the collateral sourced through SFTs or via equivalent transactions. A description of this landscape is, in fact, crucial as a first step in assessing the risks emanating from the cash and securities collateral markets and their potential implications for macro-prudential policy in Europe. By providing a description of the SFT landscape, the data collection exercises undertaken by the ESRB have a macro-prudential dimension in that they provide data at an aggregated level. The first data collection exercise encompassed a sample of 38 EU banks, representing approximately 60% of the EU banking system’s total assets. The institutions covered by this sample are the main players in the management of securities collateral. The second data collection targeted 13 agent lenders that are considered to be the largest re-investors of cash collateral in Europe. The sample period of the data is fixed at the end of February 2013. The ESRB templates yielded a unique set of data on the sources and use of securities collateral (non-cash collateral) by banks, as well as on the re-investment of cash collateral by agent lenders. The data collections were intended to fit in the broader policy context initiated by the Financial Stability Board (FSB) and the resulting analyses ultimately address a number of theFSB’s recommendations. The first element of the analysis in this report is specifically related to the FSB’s fourth recommendation (disclosure of collateral management activities) (FSB, 2013) and, to a certain extent, to the first recommendation (authorities to collect granular information on SFTs of large international financial institutions). The second element is similarly related to the first of the FSB’s recommendations, but also the sixth, which requests better disclosure ofsecurities lending activities. The analysis contained thereafter is relevant for the European Commission’s proposal on the reporting of SFTs to trade repositories (EC, 2014), which will greatly enhance transparency and regulatory oversight of SFT activities in the European Union. Finally, the report is in line with the ESRB’s outline of a monitoring framework (ESRB, 2013).
JEL Code
G15 : Financial Economics→General Financial Markets→International Financial Markets
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation