Investment Symposium March I3: Challenges in Implementing and Managing a Derivatives Program. Moderator Stephen Stone

Transcription

1 Investment Symposium March 2008 I3: Challenges in Implementing and Managing a Derivatives Program Jason Steigman Frank Zhang Ernie Tang Moderator Stephen Stone

2 Challenges in Implementing and Managing a Derivatives Program Investment Symposium, Session I3 March 25, 2008 Jason Steigman, CFA, FSA Mason Street Advisors, LLC (A Northwestern Mutual Company) Managing Director - Public Fixed Income Challenges in Implementing and Managing a Derivatives Program Organizational Challenges Operational Challenges Risk Management Challenges Portfolio Management Challenges Regulatory/Accounting/Tax Challenges Audit Management Challenges

3 Organizational Challenges Upper Management Education and Sponsorship Continuous communication with the Board Coordination of functional and professional areas: virtual organization approach Derivatives Policy and Procedures: Effectiveness vs. Organizational Feasibility Staffing: Attracting and retaining talented and competent individuals in each area Operational Challenges Derivatives System(s) and Data Integrity Home-Grown vs. Purchased Front-to-Back vs. Modular Integration with Trading Platform(s) Long Lead-Time/Large Resource Commitment Data Access/Data Integrity is critical...and challenging Back-Office/Middle-Office Support Booking/Settling/Reconciling Trades Pricing/Valuation of Derivatives Positions Confirmation/Novation Management CSA (collateral) Management for OTC Feedback Loop to Front Office Compliance Reporting

4 Operational Challenges (cont.) Front-Office Trade Execution (Best Execution) Market Surveillance Relative Value Assessment Risk Management Challenges Setting/Measuring/Monitoring Appropriate Risk Limits Counterparty Risk (OTC) Potential Exposure/Gap Risk Context: ALM vs. Asset-Side Methodologies: VaR type approaches; Scenarios Reliable systems/data is critical Leverage: Definition, Limits, Policy Model Risk Ever Changing Optical Risk (e.g. Headline Risk) Impact on Risk Management Domains: ALM, ERM, Compliance, Portfolio Risk Optimization

5 Portfolio Management Challenges Integration vs. centralization of derivatives on the trading desk Criteria for using derivatives do benefits outweigh costs/risks? Effective cash management - key to any derivatives strategy Impact of hedging costs on product price for liability hedgers Benchmark issues for total return managers Stability/Flexibility/Accuracy of Models Regulatory/Accounting/Tax Challenges Regulatory Adherence: SARBOX, NY DUP, State Derivatives Laws, 40 Act (for funds) Hedge Effectiveness Monitoring (GAAP, STAT) Filing RSATS (SVO) ISDA/CSA Agreements Effective Negotiation Adherence to ISDA Protocols Tax Issues: Straddle Rules; Wash Sales, Diversification Rule (for funds)

6 Audit Management Challenges Thorough Documentation is Critical Controls/Infrastructure Identifying and Closing the Gaps

7 Challenges of Implementing and Managing a Derivatives Program Frank Zhang, CFA, FRM, FSA, MSCF, PRM Head of Structured Derivatives and Assets Strategies ING Wealth Management SOA Investment Symposium March 25-26, 2008 New York City A Virtual Team for Equity Derivatives Hedging Program Investment Management Market Risk Management VA/FIA Hedging Program Other Mid- Back Office Investment Management Trade execution Broker relationship Portfolio management Market Risk Management Structured solutions and trading system Liability modeling Daily liability valuation production Middle and back offices Cash management Book keeping and accounting Financial reporting 2

8 Teams Within Market Risk Management Advanced Financial Modeling Structured Derivatives and Assets Strategies Market Risk Management Hedging Operations and Performance Management Structured Derivatives and Assets Strategies Structured solutions and back testing Trading system development Assets and stochastic process modeling Advanced Financial Modeling Hedging system development Projection system development Financial and liability modeling Hedging Operations and Performance Management Daily production of liability option values and Greeks Hedge performance attribution analysis Value-added analytics and risk reporting + Dedicated Risk IT Team Database, Software, Hardware, Grid Computing 3 A Case Study Setting Up a New FIA Hedging Program We recently established a new FIA hedging program 1 Study the derivative Strategies Set up mid/back office functions 2 Establish trading system 3 4

9 Case Study (Cont d 1) Study the derivative Strategies and obtain ALCO approval Back testing over 20 years Historical implied volatility surfaces and interest rate curves Derivatives pricing modules Nested stochastic derivatives pricing Weekly conference calls from offices cross the country Discussions with Chief Actuary & Chief Risk Officer, Chief Financial Officer, Head of Capital, Head of ALM, Head of Pricing BU ALCO and US Region ALCO approvals 5 Sample Back Testing P/L Breakdown Cost Savings (% of Notional) 4.50% 3.50% 2.50% 1.50% 0.50% -0.50% Sources of P/L Based on Historical Backtesting 25th %ile Mean Min Max 75th %ile -1.50% -2.50% Skew Vega Rho Vol Spread 6

10 Case Study (Cont d 2) Set up mid/back office functions Daily hedging production Systems/data Cash management P/L and performance attribution Risk reporting and monitoring Reconciliation between hedging and accounting 7 FIA Hedging Diagram Daily Market Data Interest rate curve Implied volatility surface Implied dividend yield curve Volatility surface calibration Admin System Database Policy Information C++ Pricing Engine Trading Model Collect market data Calculate asset/liab position mismatch Determine trading positions Produce trading instruction Store transaction history Hedge Performance Attribution Attribution due to Greeks, Actuarial Assumption, and etc. Hedge P/L Account Asset Account Daily trading P/L Receive premium pay credits IIM Atlanta Trades Execution PD Crediting Reporting Hedge Accounting 8

11 FIA Hedging Account P/L Tracking Diagram Liability Option Premium $ New/Renewal Policies Liability (FIADB) (Initial Liability + New Policies) General Account $ Hedging Account $ Interest Credits $ Daily G/L $ Hedging P/L Account $ Total liability option cost of hedged liability credited & cost of OTC options debited Investment earnings credited Adjusted with daily G/L settlement cash flows Policy option payoff credits paid Hedging Performance Attribution To be allocated at policy level linked with FIADB Daily OTC Options Buy/Sell $ Daily MTM P/L Trading Greeks are evaluated with implied volatility surface Default trading rule plus traders adjustments within limits Daily settlement of trading G/L credited or charged to P/L account Financial Reporting/Accounting Reconciliation and earnings volatility FIA Crediting Process Crediting should reflect long term average savings, but may reflect short term P/L experience, if desired sometimes. 9 Case Study (Cont d 2) Establish trading system Trading rule Historical intra-day test of trading results Daily closes vs. tick data Mock trading Live market data feeds and volatility surface calibrations Reliability, Stability, Noises Roll forward attribution Analysis Hedge performance attribution analysis 10

12 How to decide a good trading rule Liability Model (VA/FIA) Hedging projection system May be stochastic on stochastic simulations Model distributions similar to actual block 20 Years Market Data Historical data Market prices/dividends Swap curves Implied volatility surfaces Including 1987 market crash, etc. Daily Tick Data For Realistic Trading More realistic trading rule testing requires tick data during trading day, not just daily closes Actual 15-minute tick data for recent days Analytical technique for other history to match daily open/close/high/low Multiple Criteria Trade-off of the following Transaction costs Hedge effectiveness Performance in market crashes Considerations for the risks taken 11 Liability Roll Forward & Liability Attribution Processes Beginning Period Liability Option Value & Greeks Expected vs. Actual Changes In Option Values and Greeks Ending Period Liability Option Value & Greeks ING performs a detailed and extensive liability roll forward analysis to account for all changes in the option values of the block of business. Numerous drivers of option value changes are evaluated: Changes in market levels, interest rates, and volatilities New business and new premium additions Time decay, fees, asset classification Deaths, lapses, and withdrawals Transfers of assets between mutual funds Model changes, and other assumption updates, etc. It is a solid tool for ING to be completely on top of all components of the liability option value changes, to understand trends and behavior, to catch outliers, and to direct potential future improvements 12

13 Hedge Performance Attribution Process Net Gain\ (Loss) over the period Attributable To Fund vs. Index Tracking Error Actual vs. Expected Volatility/Skew Actual vs. Expected Correlation Actual vs. Expected Interest Rates Actual vs. Expected Decrements Joint Effects & Higher Order Greeks ING s proprietary Performance Attribution Process has been used to successfully track and manage the various asset and liability drivers that contribute to hedge program net gains and losses. It represents an important tool for deepening ING s understanding and gaining valuable insights into the key drivers of successful VA hedge program performance, allowing ING to quickly identify issues and take corrective action. It serves as an important feedback & control mechanism for things like fund manager performance relative to benchmarks, market parameters, the hedge process, and policyholder behavior. 13 Tracking Error Decomposition Net Gain / (Loss) due to Tracking Error Attributable To Basis risk Model risks Trading risks ING s proprietary Tracking Error Decomposition Tracking Error is the Residual Exposure to hedging P/L from the combination of the long position in funds with the short position in futures. The P/L due to tracking error from model and trading risks can be future broken down into model alpha, model error, fees, dividends, actual vs. expected trading P/L components, asset classes, etc. Breaking down the components of tracking errors allowed ING to specifically address the potential issues in fund selection, trading process, and hedging model improvements. 14

14 Challenges of Implementing and Managing a Derivatives Program: Front Office Perspective Ernie Tang ING Investment Management SOA Investment Symposium Session I3 March 25, 2008 Challenges in Implementing and Managing a Derivatives Program Front Office Perspective Supports Needed for a Front Office Roles / Responsibilities of a Front Office Challenges for an Insurance Company Derivative Desk SOA Investment Symposium Session I3, March 25,

15 Supports Needed for a Front Office To mange a derivative portfolio of a decent size, the front-office would not be able to operate efficiently without these supports: Trade Capture System Preferably with straight-through processing capabilities Any tie-in with Compliance system would be highly desirable Be able to handle rapidly-changing derivatives products Middle Office Analytics, MTM etc. Will have to tackle all aspects of the derivatives business. Back Office / Operation Hedge Accounting Payments/ Confirmations Collateral Management Legal / Tax Support A dedicated person to the desk is ideal SOA Investment Symposium Session I3, March 25, Supports Needed for a Front Office - Continued Trading tools / market data feeds Reuters/ Telerate (or other feeds depending on the markets) Electronic trading tools FIX protocol Risk Management Provide checks and balances Daily monitor of VaR or other risk measures Other down-steam systems / supports Feeds to ledger, schedule DB Compliance system IT Supports SOA Investment Symposium Session I3, March 25,

16 Roles / Responsibilities of a Front Office Best trade executions Selection of best instruments Best execution levels Timely responses Other value-added activities Derivatives product knowledge Constantly evolving derivatives products Market Color / Flow / Opportunities Strategy formulations / hedge designs Relationship management Client services / supports SOA Investment Symposium Session I3, March 25, Challenges for an Insurance Company Derivative Desk Insurance Industry is heavily regulated State insurance regulations are not friendly to derivative instruments DUP (Derivatives Use Plan) may not be flexible enough Non-stop auditing activities Special challenges for subsidiaries domiciled in different states Exposure must be managed and monitored carefully; ISDA s and CSA s ERISA concerns too Yet more challenges for international companies Rigid structure is not conducive for trading It takes a long time to get ideas implemented Centralized trading desk or not? Compliance considerations Practical market considerations Would the liquidity crunch affect insurance industries? Dealers began to raise haircut requirements and tightened eligible collateral list SOA Investment Symposium Session I3, March 25,