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TRANSCRIPT
Managing Capital and Stress Testing for
Traded Book Assets
Abinash Arulanandam, Alexis Hamar and Roshni Patel Thursday 4 October 2018
Managing Capital and Stress Testing for Traded Book Assets 2
AgendaKey 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 4
Market trends
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
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
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
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 5
What is the market saying?Comments in 2018
1Quantification soundnessCurrent 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.
2GovernanceThe 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.
3Greater need for Validation / AuditRevisions 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.
4Global / LocalThe 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 6
The financial crisis and the regulatory evolution
on Trading Book
Financial Crisis
2007 - Subprime
Crisis
2008 - Default Lehman Brothers
2010 - EuropeanSovereign debtcrisis
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)
Arbitrage between
Banking and Trading
Book
Capital Volatility for
Trading Assets
Market VaR RWA
Model Validation for
Complex and
Structured Instruments
Comprehensive
Risk Coverage
Managing Capital and Stress Testing for Traded Book Assets 7
Banking & Trading Books Funds T
ransfe
r Pri
ce
Commercial Margin
Concentration Premium
Option Spread
Funding Liquidity Spread
Credit Spread Residual
Reference Rate
Spread Risk Premium
Commercial Margin
Capital Value Adjustment
Margin Value Adjustment
Funding Value
Adjustment
Credit Value Adjustment
Reference Rate
Collateral Value
Adjustment
INTERSECTIONS
» New Accounting standards to
impact both Pricing and Regulatory
Capital landscapes
» CET 1 increases due to IFRS rules
will reduce upcoming FRTB
required ones
» Common Components - Spread
Risk across Trading and Banking
Books
COMMON
COMPONENTS
Common Components and Intersections
Managing Capital and Stress Testing for Traded Book Assets 9
Risk factor identification
BB & TB segregation for instruments
Intraday limit monitoring
P&L reports
Inventory ageing reports
Disclosures
Strategy/profitability Investments GovernanceSenior Management
Front office
Desk1
Desk2
Desk n Trading BookDe
sk
re
org
an
isa
tio
n
(elig
ible
de
sk
s)
Banking Book
IRT
desk
Well defined
boundary
Internal Model Approach (IMA) Standardized Approach
Expected
ShortfallNMRF
DEFAULT RISK
CHARGE
Sensitivity based
charge
Default risk
charge
Residual risk add-
on
Front office
Middle office/data
management
Monte Carlo Farms
Distributed Computing
Data Warehousing
Technology
FRTB Implementation
Managing Capital and Stress Testing for Traded Book Assets 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 12
IRC Principles
IRC
PRINCIPLES
01
0205
06
04 03
Concentration Risk» Issuer and Market (Country/Industry)
concentration
Correlations» Correlation between default& migrations
» Capture Listed, Unlisted, Emerging Markets
& Sovereign correlations
Migration» Spread and Ratings
Risk Mitigation and
Diversification» Long/Short Positions
» Hedging Strategies
Optionality» Non Linear relationships
Coverage» Debt Instruments
» Sovereigns
» Corporates/Financials
» Credit & IR Derivatives
Managing Capital and Stress Testing for Traded Book Assets 13
Proposed Architecture (Example for DRC)
Integration Services Risk Management
Default Risk Charge and
Scenario AnalysisClient
deal/static
Data
Reference
Data
Market Data
1
2
3
4
6
Distributed Simulation
Correlation Model Stress Testing Model
Staging and NormalizedDatabase
Reference Portfolios
Near Real Time
What-if (Incremental Risk, PnL)
Security
Coordinator
Full SimulationAggregated Portfolio
ViewTheoritical PnL
Front Office Desk Users
Data Integration Services
Front Office
7
8
5
Shared Temp
Hypothetical PnLSensitivies
Reference PortfolioStage
Managing Capital and Stress Testing for Traded Book Assets 14
FRTB, DRC – Correlation pain point
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
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
Managing Capital and Stress Testing for Traded Book Assets 15
IRC vs DRC SummaryTopics IRC DRC
Scope IR Instruments (Bonds, Sovereigns,
CDS) Equities (optional)
IR Instruments + Equities
Modeling Approach VaR 1 year @99.9% VaR 1 year @99.9%
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 17
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
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
Modeling Considerations
Managing Capital and Stress Testing for Traded Book Assets 18
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 19
» 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:
Wrong Way Risk and correlations
Case 1 Case 2Correlation (Counterparty and underling asset) Positive NegativeBank A position on the underling asset will receive will deliver will receive will deliverRisk (wrong way risk/ right way risk) RWR WWR WWR RWR
Managing Capital and Stress Testing for Traded Book Assets 20
» 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.
» 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.
Settlement Risk
Firm B No-default Default
Price of Apple Share $ (settlement date) 95 105 95 105
Profit 0 0 5 -5
Managing Capital and Stress Testing for Traded Book Assets 22
What Regulators say about Reverse Stress Testing ?
EIOPA study on market and
credit risk
Quantification elements for
inclusion
Solvency 2 Go Live including
some requirements on
Reverse Stress Testing
PRA provides more explicit
statements on Reverse Stress
Testing
Update on ICAAP and SREP
EIOPA – ORSA reinforces
Reverse Stress Testing
inclusion
2009 2015 2017
2014 2016 2018
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
Further to the AQR and EBA
stress tests, SREP reverse stress
testing requirements are published
Managing Capital and Stress Testing for Traded Book Assets 23
Reverse Stress Testing: Trends
1Reverse 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
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)
2
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?
Managing Capital and Stress Testing for Traded Book Assets 26
Joining the Building Blocks
CONSOLIDATED RISK
CREDIT RISK
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
BANKING BOOK
RISK DUE TO DEFAULT RISK DUE TO CREDIT MIGRATION
TRADING BOOK
RISK DUE TO MARKET RISK RISK DUE TO CCR
RISK DUE TO SPREAD RISKRISK DUE TO SPREAD
RISK
Managing Capital and Stress Testing for Traded Book Assets 27
Advantage of an Integrated Solution
A SINGLE CREDIT RISK SYSTEM
RISK DUE TO DEFAULT
RISK DUE TO CREDIT MIGRATION
INTEGRATED RISK
from an Integrated Model
of Risk Factors
» Ability to set more accurate and granular risk correlation parameters
» Straightforward risk decomposition
» Avoids double counting
» Improved operational efficiency
Better captures diversification – more accurate capital numbers
RISK DUE TO SPREAD RISK
RISK DUE TO MARKET RISK
RISK DUE TO CCR
Managing Capital and Stress Testing for Traded Book Assets 28
Credit Risk Framework
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 = 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] + 0.5 x Min [DRCb,0],0]
Standardized ApproachDRC – 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 PD @3bps
» 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.
Managing Capital and Stress Testing for Traded Book Assets 29
Modeling Credit Correlations Using Macroeconomic Variables is also Core to Understand Portfolio-Specific Tail Risk under Stress
Σ curent covariance matrix
φ
?
??
MVs
φM
Vs
The parameters to be estimated are the entries of the correlations matrix linking macroeconomic variables and systematic creditrisk factors, as well as correlations among macroeconomic variables
Define metrics and
target survival valuesPerform tail risk factor
analysis
Identify
macroeconomic
variables
Enterprise –wide
sensitivity analysis
Take actions and
create contingency
plans
Identify unviable
scenarios & hidden
vulnerabilities
Correlations of systematic factors and macroeconomic variables (MVs):
Managing Capital and Stress Testing for Traded Book Assets 30
Counterparty Credit RiskRiskFrontier 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 φMV
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 31
Expanded GCorrTM and Macro Variables Covariance Matrix:
Modeling Overview
*For further information: “Modeling Credit Correlations using Macro Economic Variables”, Nihil Patel, RPC 2012
TrialSimulated macroeconomic
factorsSimulated GCorrTM systematic
credit risk factors Portfolio Loss
1 φMV1, φMV2, … φ1, φ2, … L
2 φMV1, φMV2, … φ1, φ2, … L
Economic scenario
Losses Economic scenarios
Specified loss level
Inputs
Outputs
Analysis
Expanded Cov. Matrix Mapping MV and MV Factors
MV MC Trial-by-Trial File
Scenario Analysis: Impact MV
on LossesStress Testing Reverse Stress Testing
RiskFrontier TM
MC Simulation
Engine
Managing Capital and Stress Testing for Traded Book Assets 32
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 33
Workflow: Set the starting macro environment
Managing Capital and Stress Testing for Traded Book Assets 34
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 35
Scenarios that Generate a Loss Level
» The key to this approach is an approximation of the
portfolio loss function 𝐿𝐻 𝑟 as a linear function of asset
returns.
» The linearization is done around the asset returns ҧ𝑟 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 ҧ𝑟.
Managing Capital and Stress Testing for Traded Book Assets 36
Scenarios that Generate a Loss LevelExample
» 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 37
Scenarios that Generate a Loss LevelExample: Focus on the scenario with a 6% loss level
Macroeconomic VariableAnalysis Date
Q3-2016
Average Scenario Q3-2017
US Unemployment 4.9% 10%
US Equity 100 25
US VIX 13.34 39.87
US BBB Spread 1.85% 9.36%
Canada Equity 100 33
Canada Unemployment 7% 20.51%
Oil Price 100 41
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 38
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.
Interest Rate Risk in the Banking Book, Sep 2017 39
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obligation will not qualify for certain types of treatment under U.S. laws. MJKK and MSFJ are credit rating agencies registered with the
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MJKK or MSFJ (as applicable) hereby disclose that most issuers of debt securities (including corporate and municipal bonds, debentures, notes and
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