State Street Research Risk Management Workshop Risk Management Workshop Ron D'Vari, Ph.D., CFA Sr. Vice President, Portfolio Manager, and Director of Quantitative Research State Street Research & Management Boston Security Analyst Society October 20, 2000
Risk Management Workshop. Ron D'Vari, Ph.D., CFA Sr. Vice President, Portfolio Manager, and Director of Quantitative Research State Street Research & Management Boston Security Analyst Society October 20, 2000. Morning Session A: Introduction to Risk Management and Value-at-Risk (VaR) - PowerPoint PPT Presentation
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State Street Research
Risk Management WorkshopRisk Management Workshop
Ron D'Vari, Ph.D., CFASr. Vice President, Portfolio Manager, and Director of Quantitative Research
State Street Research & Management
Boston Security Analyst Society
October 20, 2000
AgendaAgenda
• Morning Session A: Introduction to Risk Management and Value-at-Risk (VaR)
• Morning Session B: Portfolio VaR and Different Approaches to Measuring VaR
• Afternoon Session A: Risk Management for Derivatives and Using Derivatives
– Access: Sourcing names and maturities not available through cash instrument market
– Flexibility: Uncoupling of interest and credit exposure
• Diversification
• Yield Enhancement
– Exposure to short maturities with low price sensitivity
• Relative Value and Replication
– Cheaper synthetic cash positions
• Hedging
• Leverage or Financing
Buyside ChallengesBuyside Challenges• Internal and External EducationInternal and External Education
• Accurate Portfolio Analytics and Risk ModelsAccurate Portfolio Analytics and Risk Models
• Consistent Framework for Use In Portfolio ContextConsistent Framework for Use In Portfolio Context
• Infrastructure: Compliance, Trading, and Accounting Infrastructure: Compliance, Trading, and Accounting SystemsSystems
• Signing ISDA AgreementsSigning ISDA Agreements
– Several hundred plan sponsors and separate accountsSeveral hundred plan sponsors and separate accounts
– Multiple dealers and banks Multiple dealers and banks
– A dozen custodiansA dozen custodians
– Legal resourcesLegal resources
• Shortcomings of the Standard Representations in ISDAShortcomings of the Standard Representations in ISDA
– Not developed for investment managers acting as agentNot developed for investment managers acting as agent
– Often impossible for managers to makeOften impossible for managers to make
– Requires involvement of plan sponsors and custodiansRequires involvement of plan sponsors and custodiansState Street Research & Management, Ron D’Vari, Ph.D., CFA 16
Portfolio Level Considerations of Credit Portfolio Level Considerations of Credit DerivativesDerivatives
• Besides fundamental analysis of reference credit and counterparty overall portfolio suitability has to be established.
• Optimal allotment of risk budget to credit derivatives– Portfolio’s total risk is budgeted to key active exposures
Level and shape of term structure of interest ratesVolatilitySector/Credit exposures (by sector by credit by
maturity)
• Risk Analysis and Its Transparency – Accurate accounting of credit derivatives in daily and
intraday portfolios’ multi-factor absolute and relative risk reports
– Measure credit, spread change, and structural risks
• Quantitative Relative Value Framework– W.r.t. cash instruments or other forms of risk
• Liquidity and Pricing
• Infrastructure
State Street Research & Management, Ron D’Vari, Ph.D., CFA 17
• Avoid paying bid-ask spread for a short dated trade
• Get financing (leverage)
SSRM Counter Party
Index Sector Total Return
Libor + Spreador
Total Return of Another Sector
SSRM Holdingsin a Sector
Holdings Total Return
Market
Price
State Street Research & Management, Ron D’Vari, Ph.D., CFA 23
Single Reference-Entity Credit Default Single Reference-Entity Credit Default SwapSwap
• Transfer the credit risk of an issuer (reference entity) from one entity (buyer) to another (seller)
• Seller of protection agrees to buy “obligations” of the reference entity at par in the event of a public notice
• Default event is defined a “publicly available notice” to:
– A payment failure larger or equal than “Payment Requirement” on
– an obligation equal or larger than “Default Requirement”
• Settlement can be “Physical” or “Cash”
• Deliverable obligations can be
– Reference obligation
– Any of Deliverable obligations • According to ISDA it could be any borrowed money: loans,cp, bond, and
bond and loan
• Must be specified in long confirm
State Street Research & Management, Ron D’Vari, Ph.D., CFA 24
Advantages of Default Swap over Short Advantages of Default Swap over Short CorporatesCorporates
• In general they tend to be cheaper than similar cash bond because:In general they tend to be cheaper than similar cash bond because:
– buyers inability to hedge their risk in any other marketbuyers inability to hedge their risk in any other market
(shorting public debt can be quite risky and subject to adverse technicals)(shorting public debt can be quite risky and subject to adverse technicals)
– expensive risk capital charges required against credit riskexpensive risk capital charges required against credit risk
• Increases yield with minimal increase in spread durationIncreases yield with minimal increase in spread duration
– Very attractive break-even cushion against spread wideningVery attractive break-even cushion against spread widening
• Ability to do default swap opens up unique opportunities to tailor credit Ability to do default swap opens up unique opportunities to tailor credit exposure of the portfolio - i.e. take advantage of credit curve steepness (buy exposure of the portfolio - i.e. take advantage of credit curve steepness (buy longer dated cash bonds and roll over short dated credit protection)longer dated cash bonds and roll over short dated credit protection)
• More flexibility - Default swap does not tie up cash to earn spread More flexibility - Default swap does not tie up cash to earn spread
• Allows creating higher information ratio strategies that may be leveraged for Allows creating higher information ratio strategies that may be leveraged for higher returns than similar risk strategieshigher returns than similar risk strategies
• Access to names and maturities that otherwise may not be availableAccess to names and maturities that otherwise may not be available
State Street Research & Management, Ron D’Vari, Ph.D., CFA 25
Pricing MethodologyPricing Methodology
State Street Research & Management, Ron D’Vari, Ph.D., CFA 26
• Method 1: Basis - Asset Swap vs. Default Swap (works only for single name)
• Method 2: Model Loss Distribution
Market Implied Default Probabilities
Credit Spreads Recovery Rates
Asset Correlations
Default Correlations
Simulator
Loss Distribution
Pricing Single-entity Default SwapPricing Single-entity Default Swap• Compare Libor spread of cash bond of the issuer of similar Compare Libor spread of cash bond of the issuer of similar
maturity with the default swap ratematurity with the default swap rate
• Compare all-in yield of a synthetic bond of “Default Compare all-in yield of a synthetic bond of “Default Swap+AAA ABS” with the cash bond Swap+AAA ABS” with the cash bond
• Compare a given spread with valuation based on long-term Compare a given spread with valuation based on long-term default probability and recovery rates based on transition default probability and recovery rates based on transition probability matrix and recovery valueprobability matrix and recovery value
ACCOUNT
Default Option on $10mm TCI
7 ¼ 6/99
COUNTER-PARTY
40BP/Annum
AAA Asset Back Maturing
6/15/99(+20 to 25bp over
Treasury)
Bond $10mm
State Street Research & Management, Ron D’Vari, Ph.D., CFA 27
Transition Probability (S&P Transition Probability (S&P CreditWeekCreditWeek 15 15 April 96)April 96)
IntialRating
Rating At Year-End (% )
AAA AA A BBB BB B CCC D
AAA 90.81 8.33 0.68 0.06 0.12 0.00 0.00 0.00
AA 0.70 90.65 7.79 0.64 0.06 0.14 0.02 0.00
A 0.09 2.27 91.05 5.52 0.74 0.26 0.01 0.06
BBB 0.02 0.33 5.95 86.93 5.30 1.17 0.12 0.18
BB 0.03 0.14 0.67 7.73 80.53 8.84 1.00 1.06
B 0.00 0.11 0.24 0.43 6.48 83.46 4.07 5.20
CCC 0.22 0.0 0.22 1.30 2.38 11.24 64.86 19.79
• Four sources of transition probability matrices: S&P, Moody, CreditMetrix, KMV
•Over 15 years of data with more than 25,000 firm/years of observations, adjusted for “no-longer rated” entities
State Street Research & Management, Ron D’Vari, Ph.D., CFA 28
•Recovery rates (CreditMetrix using several studies)Recovery rates (CreditMetrix using several studies)Seniority Class Mean(% ) Std. Dev. (% )