NEW DIRECTION FOR MARKET RISK: ISSUES AND CHALLENGES

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1 NEW DIRECTION FOR MARKET RISK: ISSUES AND CHALLENGES 3 rd Annual RISK AMERICAS, May 12-13, Marriott Downtown, New York City Presenter: Anshuman Prasad, Director, Risk and Analytics 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 Regulatory Issues Reliability of various measures of risk Validation and back-testing of models to reduce model risk Trading vs. banking book boundaries Regulatory stress tests Modeling Challenges Valuation of illiquid products Correlation under stressed environment Model calibration Tradeoffs: speed vs. accuracy System and Data Issues Incomplete and/or inaccurate data Lack of unified data processing model Limited involvement of business Real-time computation, lack of integrated systems Organizational Culture Silo approach to risk management Limited role of risk managers in decision making Narrow, compliance-focused approach 3

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

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

6 Stressed: Macro variables 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 Credit Spreads Unemployment Equity Market Index House Price Index Econometric Modeling IR Term Structures IV Term Structures/Skews Correlations Valuation Models Market Risk Modelling CCP Exposure Modelling 6

7 Modeling Challenges: Model Calibration 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! Technique Description Type of Products Discounting PDE-based Lattice-based MC Simulation By discounting cashflows at future dates Closed-form pricing for low factor/low dimension models; path independent Closed-form pricing for low factor/low dimension models; path dependent Simulation pricing for high factor/high dimension models; path dependent IRS, Bonds, Floaters First generation structures Caps/Floors, CBs, TS models Highly complex structures 7

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 Bid-ask Spread Adjustment Adjustment of bid-ask spread for specific market risk parameters Bounding Approach Determine lower and upper limit price by relying on reasonable limits to trade performance 8

9 Computational Trade-offs 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 AGILITY Sensitivity Based Approaches Ease of implementation Approximations (Taylor expansion/grids) Full Revaluation Approach Robust Computationally intense CONTROL Newer technology (GPUs, multi-core processors) helping reduce computation times and trade-offs 9

10 Data Management Issues Increased regulatory focus on providing granular and frequent analysis of real time data Typical Data Management Processes Trade Data Market Data Extract Validate Enrich Transform Reports Ad hoc Queries Load Traditional Extract-Transform-Load (ETL) processes not amenable to realtime 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 10

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

12 Organizational Culture Organizational structure and incentives are getting better aligned to market risk management objectives 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 Market risk management will need to be more tightly integrated with strategic objectives, diversity of business and level of complexity 12

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