Managing Capital and Stress Testing for Traded Book Assets. Abinash Arulanandam, Alexis Hamar and Roshni Patel Thursday 4 October 2018

Transcription

1 Managing Capital and Stress Testing for Traded Book Assets Abinash Arulanandam, Alexis Hamar and Roshni Patel Thursday 4 October 2018

2 Agenda Key elements for discussion 1. Overview and the current market demands 2. Impacts for trading book assets a. Fundamental Review of Trading Book - Linkage to Incremental Risk Charge (IRC) and Default Risk Charge (DRC) b. Risk coverage 3. Focus on Reverse Stress Testing 4. Q&A Managing Capital and Stress Testing for Traded Book Assets 2

3 1 Overview and the current market demands

4 Market trends Traditionally, analysis of trading book and banking book is viewed as distinct from the analysis of the different nature and dynamics of risks. However, some joint dynamics are required to capture the emergence of collateral risk NEW PARADIGM FOR TRADED ASSETS More Regulatory emphasis on economic risks of traded assets treated Risk and Emergence of Collateral Risk Spread Risk - Settlement Risk Wrong Way Risk Stress Testing reinforcement in context of ICAAP and future FRTB rules CONSOLIDATED VIEW Group structures require a strong coordination of activities aimed to: Set rules for estimation of traded assets and banking books at group level. Have a consolidated and consistent view of the Group risk profile Increase the efficiency of risk-capital allocation over the entire Group perimeter Risk Appetite and Hedging Strategies Implementation Exploring both Regulatory and Internal Risk Capital Concentration and correlation affects for concentration risk Capital allocation across both measures Trend to enhance and integrate measures Managing Capital and Stress Testing for Traded Book Assets 4

5 What is the market saying? Comments in Quantification soundness Current approaches adopted by clients are viewed to not be quantitative, and are more expert or qualitatively based/driven. This is predominantly led by ICAAP findings and internal committee reviews. Governance The banking book, its models have known to have strong governance frameworks but the trading book needs to have consistent and common governance structures, enhancing controls for models. Greater need for Validation / Audit Revisions to regulation, models and feedback on prior regulatory submissions has meant greater interactions for internal / external validation and providing Auditors with proof on the submissions. Global / Local The need for global consistency but accounting for local nuisances and how to manage branches, subsidiaries and group level consolidations. Common reporting and model framework. Managing Capital and Stress Testing for Traded Book Assets 5

6 The financial crisis and the regulatory evolution on Trading Book Capital Volatility for Trading Assets Financial Crisis Subprime Crisis Default Lehman Brothers European Sovereign debt crisis Issues posed by regulators Advantage of Internal Models vs Standard VaR and credit risk in the Trading Book Low sensitivity to extreme events Banking Book vs Trading Book Arbitrage Basel 2.5 Stressed VaR IRC/CRM Hypo vs Actual Backtesting Impact of Basel 2.5 Capital charge for wider asset classes (i.e Sovereign Increase of capital requirement for Internal Model Banking Book vs Trading Book Next evolution: FRTB Basel 4 Expected Shorftall / Liquidity Horizon Regulator imposed correlations Market dynamics representation News for Model Validation PnL Attribution Backtesting Validation of IMM at Desk level Floor Standard Method / Reduction of gap Internal Model vs Std Default Risk Charge (DRC) Market VaR RWA Arbitrage between Banking and Trading Book Comprehensive Risk Coverage Model Validation for Complex and Structured Instruments Managing Capital and Stress Testing for Traded Book Assets 6

7 Funds Transfer Price Banking & Trading Books Common Components and Intersections INTERSECTIONS Commercial Margin Spread Risk Premium COMMON COMPONENTS Commercial Margin Collateral Value Adjustment Concentration Premium Option Spread» New Accounting standards to impact both Pricing and Regulatory Capital landscapes Capital Value Adjustment Margin Value Adjustment Funding Liquidity Spread Credit Spread Residual Reference Rate» CET 1 increases due to IFRS rules will reduce upcoming FRTB required ones» Common Components - Spread Risk across Trading and Banking Books Funding Value Adjustment Credit Value Adjustment Reference Rate Managing Capital and Stress Testing for Traded Book Assets 7

8 2 Fundamental Review of Trading Book Linkage to DRC and IRC

9 Desk reorganisation (eligible desks) FRTB Implementation Senior Management Strategy/profitability Investments Governance Desk1 Banking Book Front office Desk2 IRT desk Well defined boundary Desk n Trading Book Internal Model Approach (IMA) Standardized Approach Front office Expected Shortfall NMRF DEFAULT RISK CHARGE Sensitivity based charge Default risk charge Residual risk addon Middle office/data management Risk factor identification BB & TB segregation for instruments Intraday limit monitoring P&L reports Inventory ageing reports Disclosures Monte Carlo Farms Technology Distributed Computing Data Warehousing Managing Capital and Stress Testing for Traded Book Assets 9

10 Stress Testing Emphasis in FRTB» Stress Testing is a transversal imposed practice Stressed calibration period (period of significant financial stress) for Expected Shortfall Liquidity Horizon : no price movement for instrument hedging in stressed period Curvature in Standardized approach is estimated through 2 stress scenarios per risk factors Non Modellable Risk factors where there is a stress capital charge Default Risk Charge : Based on a 1 year period of stress taken from a 10 year historical data using a 250 Liquidity Horizon Stressed period means: 12 months period of stress over the observation horizon in which the portfolio experiences the largest loss Span at least back to 2007 Observation equally weighted At least an update once a month And updates done as soon as there is a significant move in the market Managing Capital and Stress Testing for Traded Book Assets 10

11 IRC Principles Risk Mitigation and Diversification» Long/Short Positions» Hedging Strategies Coverage» Debt Instruments» Sovereigns» Corporates/Financials» Credit & IR Derivatives Optionality» Non Linear relationships 05 IRC PRINCIPLES 02 Concentration Risk» Issuer and Market (Country/Industry) concentration Migration» Spread and Ratings Correlations» Correlation between default& migrations» Capture Listed, Unlisted, Emerging Markets & Sovereign correlations Managing Capital and Stress Testing for Traded Book Assets 12

12 Proposed Architecture (Example for DRC) Integration Services Risk Management Front Office Data Integration Services Reference Data Correlation Model Stress Testing Model Reference Portfolios Coordinator Hypothetical PnL Sensitivies 1 4 Shared Temp Security 8 Client deal/static Data Default Risk Charge and Scenario Analysis Distributed Simulation 6 Front Office Desk Users Staging and Normalized Database 3 Full Simulation Aggregated Portfolio View Theoritical PnL 5 7 Market Data 2 Reference Portfolio Stage Near Real Time What-if (Incremental Risk, PnL) Managing Capital and Stress Testing for Traded Book Assets 13

13 FRTB, DRC Correlation pain point Correlation is one of the pain points due to modelling complexity, data requirements and inclusion of equities in FRTB FRTB REQUIREMENTS MODEL Correlation model is a requirement Correlation needs to be measured over a liquidity horizon of one year Validation of correlation model must be in place Choice & weights of systematic risk factors must be well documented and validated DATA Calibration to at least 10 years of data Equity data must be included Must include periods of stress Objective and transparent data What banks are looking for Granular level that allows client to better understand risk in their portfolios Multi-factor model allows to capture different aspects of firms, economy and the relevant relations +10 years of data satisfying FRTB requirements and providing robust estimates Partner with external vendor or create a combined external and internal data model Sovereigns included with state of the art methodology due to scarce data Corporate correlations included in model ensuring maximum completeness Extensive research in model development for different sectors Data cleaning not needed on the client s side, painless bind with system Recognized vendor ensuring quality, standards and support if needed Managing Capital and Stress Testing for Traded Book Assets 14

14 IRC vs DRC Summary Topics IRC DRC Scope IR Instruments (Bonds, Sovereigns, CDS) Equities (optional) IR Instruments + Equities Modeling Approach VaR 1 VaR 1 Default Risk Multi-Factor approach 2 types of Factor Approach Correlations horizon 3 years 10 years including a 12 months of stress Correlations source Any (asset returns, equity returns, cds spreads) Based on CDS spreads and equity returns Migration Risk Included Excluded. Included in Spread Risk Liquidity Horizons 3 month or 1 year horizon 1 year and 60 day for Equity PD No floor 3 bps floor LGD Deterministic, stochastic (optional) Stochastic and correlated to systematic factors Managing Capital and Stress Testing for Traded Book Assets 15

15 2b Other risk types

16 Counterparty Credit Risk considerations Multi-period Valuation Portfolio Models Correlation» Valuation (optionality and pricing proxies etc)» Credit Migration and Spread Risk Effects» Liquidity Value adjustments/ funding liquidity adjustments» Wrong way risk (specific)» Monte Carlo simulation approximations» CVA VaR and allocation» Re/calibration» Benchmarking» Back-testing» Risk Factor Analysis (multi factor asset correlation models)» Cross asset correlation (IR, Credit, FX etc)» Wrong way risk (general)» Stress testing and scenario construction Modeling Considerations Strategy and Business Considerations» Best practices processes» Data, System infrastructure and reporting requirements» Front office (FO) vs CCR model reconciliation» CVA Hedging» Capital Optimisation» Integration of loan and trading portfolios Managing Capital and Stress Testing for Traded Book Assets 17

17 Wrong Way Risk» Wrong-Way Risk An unfavourable dependence between exposure and counterparty credit quality: the exposure is high when the counterparty is more likely to default and vice versa.» General Wrong-Way Risk Arises when the probability of default of counterparties is positively correlated with general market risk factors.» Specific Wrong-Way Risk Arises when the exposure to a particular counterpart is positively correlated with the probability of default of the counterparty due to the nature of the transactions with the counterparty.» Wrong Way Risk includes the following ingredients: Joint simulation of Market-Credit factors Utilizes Economic Portfolio Models as it is designed by nature with correlations effects Migration, Default and to some extent Recovery for systematic LGD Conditional scenarios Funding Spread in FVA Managing Capital and Stress Testing for Traded Book Assets 18

18 Wrong Way Risk and correlations» There are two types of correlation to consider: The correlation between the underlying asset and the counterparty of the trade. The correlation between the trades.» A firm has to typically take into account both types of correlation.» The correlation between the instrument and trade counterparty can increase (WWR/wrong way risk) or decrease (RWR/right way risk) the capital requirements.» Example of an use cases (other use cases also available: Case 1 Case 2 Correlation (Counterparty and underling asset) Positive Negative Bank A position on the underling asset will receive will deliver will receive will deliver Risk (wrong way risk/ right way risk) RWR WWR WWR RWR Managing Capital and Stress Testing for Traded Book Assets 19

19 Settlement Risk» Settlement risk is the risk that one party will fail to deliver the terms of a contract with another party at the time of settlement.» In Europe, there is a growing trend to see more quantification of the settlement risk capital and its impact considering netting, correlations and at different distributions.» Regulators want to explore all the other traditional risk types» Settlement risk can create a loss if the underlying asset value moves against the agreed price. In Delivery vs Payment (DvP) contracts: the loss is the replacement cost. Example» Firm A buys 1 Apple share at $100 from Firm B. Firm B No-default Default Price of Apple Share $ (settlement date) Profit » To measure settlement risk it is key to capture the joint likelihood of counterparty default and the change in the value of the underlying reference asset. Managing Capital and Stress Testing for Traded Book Assets 20

20 3 Focus on Reverse Stress Testing

21 What Regulators say about Reverse Stress Testing? The Basel committee paper on principles for sound stress testing practices and supervision promoted a comprehensive stress testing approach in banks, the concept of Reverse Stress Testing. EIOPA -Solvency Pilar 2 ORSA Introduction Reverse Stress Testing PRA provides more explicit statements on Reverse Stress Testing Update on ICAAP and SREP EIOPA ORSA reinforces Reverse Stress Testing inclusion Further to the AQR and EBA stress tests, SREP reverse stress testing requirements are published Solvency 2 Go Live including some requirements on Reverse Stress Testing EIOPA study on market and credit risk Quantification elements for inclusion Managing Capital and Stress Testing for Traded Book Assets 22

22 Reverse Stress Testing: Trends 1 2 Reverse Stress Testing Nothing new In the UK, this has been around for a number of years, Europe has become more advanced and developed, a new re-focus Require firm to assess scenarios and circumstances that would render its business model unviable More understanding for the ICAAP submission as per regulatory requirements Core elements Determining scenarios Be able to macroeconomic variable related terms for loss points defined Explore idiosyncratic weaknesses Uncover which risks contribute the most to expected loss and capital and use that information to design plausible stress scenarios For instance By how much does GDP have to fall for my portfolio to lose 10% in value? 3 Example approach Range of qualitative and quantitative approaches to determine those weaknesses Explore correlations between credit risk factors and macroeconomic variables to help draw impacts Different risk types will also have different triggers, look at asset class specific influences Leverage macro-scenario approach, which is key input for the firm to explore cause of trigger points. Estimating conditional mean of the risk factors and macro variables conditional on portfolio loss exceeding a given loss level Reducing dimension of risk and macro factors by ranking the most influential risk/macro factors that determine losses Solving for the inversion problem to find the set of risk/macro factors values with regards to the hypothetical scenario (the most likely scenario) Managing Capital and Stress Testing for Traded Book Assets 23

23 Q&A

24 Appendix

25 Joining the Building Blocks BANKING BOOK RISK DUE TO DEFAULT RISK DUE TO CREDIT MIGRATION CREDIT RISK RISK DUE TO SPREAD RISK RISK DUE TO SPREAD RISK RISK DUE TO MARKET RISK TRADING BOOK RISK DUE TO CCR COUNTERPARTY CREDIT RISK» Challenges in setting the correlation between credit risk, market risk, spread risk and CCR» Spread Risk presence in both trading and banking books and unique counting Margin Period of Risk Settlement Risk Migration Risk - Spread CONSOLIDATED RISK Managing Capital and Stress Testing for Traded Book Assets 26

26 Advantage of an Integrated Solution Better captures diversification more accurate capital numbers A SINGLE CREDIT RISK SYSTEM RISK DUE TO DEFAULT RISK DUE TO CREDIT MIGRATION INTEGRATED RISK from an Integrated Model of Risk Factors RISK DUE TO SPREAD RISK RISK DUE TO MARKET RISK RISK DUE TO CCR» Ability to set more accurate and granular risk correlation parameters» Straightforward risk decomposition» Avoids double counting» Improved operational efficiency Managing Capital and Stress Testing for Traded Book Assets 27

27 Credit Risk Framework DRC Internal Model Approach Credit VaR based approach :» Stochastic LGD and 0% recovery for equities» Dependance of recovery rates and systematic risk factors» 2 types of systematic factors for simulating defaults» Correlations based on equity prices or CDS spreads» Floored One year liquidity horizon and 60 day for Equities The new default risk charge should capture the risk arising from long/short positions from the timing of defaults within a one-year capital horizon :» For example a long 1-year bond position hedged with a 3month CDS should take into account loss scenarios generated by the issuer defaulting between months four and twelve months. 3 sub-portfolio to be considered:» Non Securitization» Securitization-Non CTP incl. its hedges» Securitization-CTP incl. its hedges Modeling of the Default Risk by Jump-to-default (JTD)» LGD equity, non senior debt = 100%; LGD senior debt = 75%, LGD covered bonds = 25%» Limitation in terms of seniority for offsetting positions (long/short) : Netting is allowed only if short position has the same seniority of the long one» JTD (long) = Max {LGD X Notional +PnL; 0}» JTD (short) = Max {LGD X Notional + PnL; 0}» RW = default risk weight * JTD Wts = Standardized Approach σ JTD long σ JTD long+σ JTD short DRC Charge Non Securitization (by bucket) = Max [ RWlong net JTD - WtS * RWshort net JTD, 0] DRC Charge Securitization CTP (by bucketed DRCb) = Max [ [Max[DRCb,0] x Min [DRCb,0],0] Managing Capital and Stress Testing for Traded Book Assets 28

28 MVs φ Modeling Credit Correlations Using Macroeconomic Variables is also Core to Understand Portfolio-Specific Tail Risk under Stress The parameters to be estimated are the entries of the correlations matrix linking macroeconomic variables and systematic credit risk factors, as well as correlations among macroeconomic variables Correlations of systematic factors and macroeconomic variables (MVs): φ Σ curent covariance matrix MVs??? Define metrics and target survival values Perform tail risk factor analysis Identify macroeconomic variables Identify unviable scenarios & hidden vulnerabilities Enterprise wide sensitivity analysis Take actions and create contingency plans Managing Capital and Stress Testing for Traded Book Assets 29

29 Counterparty Credit Risk RiskFrontier in conjunction with GCorr Macro and a market risk system can be used to construct Wrong Way Exposure, along with the portfolio referent risk of each particular counterparty. 1)Run RiskFrontier with GCorr Macro and the Expected Exposure Profile (from market system that accounts for netting) 2)Using the MC Output (which provides trial-by-trial detailed distributions on exposure and factor level) one can calculate the expected WW PD and expected WW market factor realizations conditional on the portfolio realizing losses in the region of the capital threshold 3)Compute WW Exposure using the market risk system along with the expected WW market factor from step (2) 4)Calculate portfolio referent risk of each counterparty using WW Exposure from (3) 5)In some cases the WW Exposure is substantial and may impact the capital threshold to the point where steps (1)-(4) need to be iterated, with the WW Exposure replacing Expected exposure in step (1) Expected shock φ MV conditional on portfolio loss Market Risk System Calculates Wrong Way Exposure Wrong Way Exposure analyzed in RiskFrontier Managing Capital and Stress Testing for Traded Book Assets 30

30 Expanded GCorr TM and Macro Variables Covariance Matrix: Modeling Overview Expanded Cov. Matrix Mapping MV and MV Factors Inputs Outputs Trial Simulated macroeconomic factors MV MC Trial-by-Trial File Simulated GCorrT M systematic credit risk factors Portfolio Loss 1 φ MV1, φ MV2, φ 1, φ 2, L RiskFrontier TM MC Simulation Engine 2 φ MV1, φ MV2, φ 1, φ 2, L Scenario Analysis: Impact MV on Losses Stress Testing Reverse Stress Testing Analysis Economic scenario Losses Specified loss level Economic scenarios *For further information: Modeling Credit Correlations using Macro Economic Variables, Nihil Patel, RPC 2012 Managing Capital and Stress Testing for Traded Book Assets 31

31 Workflow : Easy Upload and Selection of Trials Upload RF Outputs: generated the loss distribution correlated factor file Define the tail trial windows entering probability levels or a single probability and a window size. Managing Capital and Stress Testing for Traded Book Assets 32

32 Workflow: Set the starting macro environment Managing Capital and Stress Testing for Traded Book Assets 33

33 Workflow: Factor and MV Tail Mean Analysis 4. Trials Sorting in R or Excel 5. Attribution Reports Outputs Factor Means Macro and Financial Variable Means Macro and Financial Variable Density» Conditional Systematic Factor Ranking Tail Mean» Conditional Macro and Financial Variables Tail Mean» Macro and Financial Variable Density Probability Managing Capital and Stress Testing for Traded Book Assets 34

34 Scenarios that Generate a Loss Level» The key to this approach is an approximation of the portfolio loss function L H r as a linear function of asset returns.» The linearization is done around the asset returns rҧ that generate the pre-defined loss level തL.» We can then analytically search for the scenarios that give that level of loss» We need the Monte Carlo output around the pre-defined loss level to identify the asset returns r. ҧ Managing Capital and Stress Testing for Traded Book Assets 35

35 Scenarios that Generate a Loss Level Example» Consider a well-diversified portfolio made of US and Canadian exposures.» We want macroeconomic scenarios that lead to a loss of 6% of mark-to-model value in this portfolio at a 1-year horizon. This loss level corresponds to the 47bp percentile of the loss distribution. Analysis date: 30/09/2016.» We focus only on scenarios with the following macroeconomic variables: US Unemployment, US Equity, US VIX, US BBB Spread, Canada Equity, Canada Unemployment, Oil Price. Managing Capital and Stress Testing for Traded Book Assets 36

36 Scenarios that Generate a Loss Level Example: Focus on the scenario with a 6% loss level Macroeconomic Variable Analysis Date Q Average Scenario Q US Unemployment 4.9% 10% US Equity US VIX US BBB Spread 1.85% 9.36% Canada Equity Canada Unemployment 7% 20.51% Oil Price The scenarios should lead to a conditional loss distribution whose expected loss is close to the desired level of loss Percentiles Target Expected Conditional Loss 672 bp 2% 4% 154 bp 4% 6.33% 46 bp 6% 8.19% Managing Capital and Stress Testing for Traded Book Assets 37

37 Reverse Stress Testing Utility Automation The utility automates and streamlines the reverse stress testing process from RF Outputs to Tail Factor Analysis. Factor and Macro Variable Sensitivity Approach Systematic and Macro/financial Macro Variables detailed Tail Mean Analysis Transparency Validation and Audit Analysis including Tail Trials, MV Returns, GCorr Factor Mapping Governance Frequency of Updates wrt GCorr Models, Macro Levels update and Quality Checks Fast Calculation Uses R code and Excel Macros for Trial Sorting that can be performed in few minutes. Managing Capital and Stress Testing for Traded Book Assets 38

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