Stress Tests: Top-Down Vs Bottom-up A CCP view Panel session at 8 th Financial Risks International Forum 31 st of March 2015.

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Presentation transcript:

Stress Tests: Top-Down Vs Bottom-up A CCP view Panel session at 8 th Financial Risks International Forum 31 st of March 2015

2 Overview Systemic importance of CCPs and Regulatory implications 1/2  CCPs are at the heart of financial systems  CCPs tend to concentrate liquidity&flows (e.g. dependence to Exchanges, semi-monopolies on given asset classes, etc.)  Systemic institutions (LCH.C, Eurex…)  CCPs call financial ressources to cover potential exposures resulting from the default of a Clearing Member  Loss allocation upon a predefined Waterfall process  Initial Margin (« normal market conditions »)  Skin-in-the-game  Mutualised Default Fund (tail risk / Stress test losses) What is a CCP?  A Central Counterparty (CCP) is a financial institution providing two post-trading services: 1.Insurance on counterparty credit risk 2.Central trade & settlement facility (Back Office efficiencies, Netting benefits) Financial ressources

3 Overview Systemic importance of CCPs and Regulatory implications 2/2  Lack of homogeneity of Regulatory Technical Standards (RTS)  Across different jurisdiction (Dodd Franck vs EMIR)  Across different rules (Market Infrastructure vs Bank) Example: Liquidity ratios  Lack of clarity of controversial articles (Lobbying effects?) EMIR article 27: « W here portfolio margining covers multiple instruments, the amount of margin reductions shall be no greater than 80% of the difference between the sum of the margins for each product calculated on an individual basis and the margin calculated based on a combined estimation of the exposure for the combined portfolio. Where the CCP is not exposed to any potential risk from the margin reduction, it may apply a reduction of up to 100% of this difference. » Regulatory environment  Multiple jurisdiction & rules  EMIR  Basel III (LCH Clearnet SA is a Bank, only CCP included in the ECB Stress testing review)  CRD IV  Dodd Frank / CPSS-IOSCO, etc. Main operational issues

4 The Stress Testing case Context, Challenges  Regulation is not prescriptive (room for interpretation)  Need to stress all portfolios equally (no discrimination)  Need to define a stable measure (avoid procyclical effects)  Lack of consistent datasets / Granularity of risk factors  Stability of distributions (is an historical event still valid today?)  Plausibility measure: Univariate vs Multivariate Regulatory Context  Stress Testing is linked to Default Fund and shall cover  Historical and theoretical scenarios  Under « extreme but plausible » market conditions  Extreme but plausible is measured  Including periods of extreme market movements observed over the past 30 years  Via a range of potential future scenarios, drawing on both quantitative and qualitative assessments of potential market conditions Risk Management challenges

5 The Stress Testing case Practice: Historical Scenarios Dates for extreme Negative Variations Description 15/10/1987 Black Monday 19th of October /10/20086th of October 2008 Black Monday & Subprime Crisis 01/08/2011Eurozone crisis 28/11/20086th of October 2008 Black Monday & Subprime Crisis 29/04/2003 Wheat crisis Dates for extreme Positive Variations Description 12/03/2003 Rise after historically lowest prices on main Indexes - Beginning of the second Iraqi war 28/10/2008 6th of October 2008 Black Monday & Subprime Crisis 08/10/2002 European market decline & high increase after black July 30/07/1999 Rapeseed Crisis DatesDescription 01/05/1998Decorrelation scenario CaC vs AEX 13/03/2000Decorrelation scenario 4 main indices Historical scenarios (subsample)  Replay historical events: well recognized stress periods  Worst historical moves for major pairs of risk factors

6 The Stress Testing case Practice: Theoretical approach Plausibility measure  How to define Extreme but plausible?  Qualitative / Event-driven scenarios (for instance apply historical returns to other risk factors)  Quantitative approach relying on: 1.Elliptical distribution 2.Convex optimization framework: Where:P is the predefined portfolio direction S is the vector of risk factor returns: ‘the stress scenario’ Sigma is the risk factor correlation matrix q is the predefined desired quantile of the portfolio loss (plausibility threshold)

7 Conclusion Top Down: Existing regulatory issues (Learnt the hard way!)  Regulation should be as simple and clear as possible to create a level playing field  Current environment leaves room for interpretation  Risk of a race to the bottom  Good risk management practice not rewarded  Need of comparison / transparency among CCPs  Need of a standardized CCP stress testing framework Bottom Up: Industry trend  Inner knowledge of real risk  Positions  Risk factors  Ability to react  Need of a standardized CCP stress testing framework (comparison & floor)  Going Further - LCH Clearnet position: