Check out Anshuman Prasad’s 'New Direction For Market Risk: Issues & Challenges' at 3rd Annual Risk Americas presentation

1. 3rd Annual RISK AMERICAS, May 12-13, Marriott Downtown, New York City
Presenter: Anshuman Prasad, Director, Risk and Analytics
NEW DIRECTION FOR MARKET RISK:
ISSUES AND CHALLENGES
May 12-13, 2014

2. Agenda
 Market Risk Management: Outstanding Issues
 Impact of Regulations
– Measures of Market Risk
– Regulatory Stress Tests
 Modeling Challenges
– Valuation of Illiquid Instruments
– Illiquidity Discount
– Computational Trade-offs
 Data Management Issues
 Trends in Market Risk Systems
 Organizational Culture
2

3. Market Risk Management: Outstanding Issues
3
 Reliability of various measures of risk
 Validation and back-testing of models
to reduce model risk
 Trading vs. banking book boundaries
 Regulatory stress tests
Regulatory Issues
 Silo approach to risk management
 Limited role of risk managers in
decision making
 Narrow, compliance-focused
approach
Organizational Culture
 Valuation of illiquid products
 Correlation under stressed
environment
 Model calibration
 Tradeoffs: speed vs. accuracy
 Incomplete and/or inaccurate data
 Lack of unified data processing
model
 Limited involvement of business
 Real-time computation, lack of
integrated systems
System and Data Issues
Modeling Challenges

4. Impact of Regulations
4
Newer regulations impacting market risk management frameworks
 Fundamental Review
of the Trading Book
(BCBS 219)
Regulation
 Stress Testing
(Dodd-Frank, CCAR)
 Model Risk
Management
(OCC SR-11/7)
 Difficult to move assets between the trading and banking
books
 Shift to Expected Shortfall from VaR
 Varying liquidity horizons
Impact
 Handling granular market shocks
 Requires calculation of various parameters under stress
 Widened the definition a “model”
 Enhanced model validation and model governance framework
 Emphasis on rigorous testing, model documentation and
quantifying model uncertainty
 Data aggregation and
Reporting
(BCBS 239)
 Early warning systems
 Comprehensive and granular reporting
 Overhaul of systems and processes

5. Measures of Market Risk
5
There is no single measure of risk that can provide a consistent view of risk
across market participants and regulators
 Simple, established
 Single view of risk
Pros
 Conservative
 Size and likelihood
of losses
 Reduces cyclicality
 Easy to interpret
 Simple modeling
procedure
 Lacks coherence
 Extreme tails
 Inconsistencies
Cons
 Difficult to back-test
 Prone to
optimization errors
 Can be misleading
 Cannot be
aggregated
 Regulatory reporting
 Setting risk limits
Key Use
 Regulatory reporting
 Economic risk
capital
 Key measure used
for hedging risk
 Setting risk limits
Value at
Risk (VaR)
Measure
Expected
Shortfall
(ES)
Sensitivities

6. Regulatory Stress Tests (CCAR, EBA)
 Regulators provide a varying degree of granularity in their market shock
variables
 Some of the key requirements in dealing with these stress tests from a
market risk perspective include
– Comprehensive understanding of risk drivers
– Customized scenario expansion models to expand regulatory scenarios
– Robust input-output templates to ensure quick turnarounds
– Organizational focus and coordination across functions
Real GDP Growth
Unemployment
Equity Market
Index
House Price Index
Stressed:Macrovariables
Econometric
Modeling
Credit Spreads
IR Term Structures
IV Term
Structures/Skews
Correlations
Valuation Models
Market Risk
Modelling
CCP Exposure
Modelling
6

7.  By discounting cashflows at
future dates
Description
 Closed-form pricing for low
factor/low dimension
models; path independent
 Closed-form pricing for low
factor/low dimension
models; path dependent
 IRS, Bonds, Floaters
Type of Products
 First generation structures
 Caps/Floors, CBs, TS
models
 Simulation pricing for high
factor/high dimension
models; path dependent
 Highly complex structures
Modeling Challenges: Model Calibration
7
Discounting
Technique
PDE-based
Lattice-based
MC Simulation
 FASB valuation categories are based on complexity – Level 1/2/3
 Level 3 assets are priced using in-house valuation models
 Models built can only be as good as the underlying data !

8. Modeling Challenges: Illiquidity Discount
 Driven by stress testing requirements, initial steps are being taken towards
better management of the market impact of illiquidity; measures include
– Checking for variability in liquidation times for illiquid positions
– Setting up processes for measuring impact of trade volumes on market prices
– Monitoring widening bid-ask spreads, specially in times of adverse market conditions
 CCPs started for most liquid OTC derivatives; liquidity adjustment
challenges seen in more exotic products
 Methods for incorporating the illiquidity discounts in OTC valuation models
8
 Adjustment of bid-ask spread for specific market risk
parameters
 Determine lower and upper limit price by relying on
reasonable limits to trade performance
Bid-ask
Spread
Adjustment
Bounding
Approach

9. Computational Trade-offs
9
 Choice between delta-based methods and the full revaluation method
 Most banks still use sensitivity-based approaches due to computational
challenges associated with the full-revaluation approach
Newer technology (GPUs, multi-core processors) helping reduce
computation times and trade-offs
Sensitivity Based
Approaches
 Ease of implementation
 Approximations (Taylor
expansion/grids)
Full Revaluation Approach
 Robust
 Computationally intense
CONTROL
AGILITY

10. Data Management Issues
10
Increased regulatory focus on providing granular and frequent analysis of
real time data
 Traditional Extract-Transform-Load (ETL) processes not amenable to real-
time computation of risk. Alternatives may include:
– ELT: Data transformation after the data load, includes data virtualization
– Data Federation: Single virtual view without actually moving the data
Typical Data Management Processes
 Trade Data
 Market Data
Extract
 Validate
 Enrich
Transform
 Reports
 Ad hoc Queries
Load

11. Trends in Market Risk Systems
11
Increase ‘risk velocity’ and ‘risk management’ clock-speed
 Automation of stress testing and reporting framework
 GPU-based farms enabling move to full revaluation
approach
Measure
 Cloud Computing, a natural solution for higher data
capacity needed for granular regulatory reporting
 Service-based architecture with detailed data captured at
trade level
 Flexible data capture and storage solutions
Timeliness and
Accuracy
Data/Reporting
Attribute
Comprehensive
ness
Adaptability

12. Organizational Culture
12
 Front office alignment
– Financial incentives being aligned with risk-informed performance indicators
– RWA consumption by trade becoming an important statistic
 Model validation and model development functions being strengthened
– Investments in internal/external resourcing
 Robust middle office and IT processes becoming a differentiator
– Cost of funding (CVA, FVA etc) getting incorporated
– Granularity/Speed/Flexibility in risk calculations and reporting
Organizational structure and incentives are getting better aligned to market
risk management objectives
Market risk management will need to be more tightly integrated with strategic
objectives, diversity of business and level of complexity

13. www.crisil.com/gra