Managing Risk in Multi-Asset Class,
Multimarket Central Counterparties:
The CORE Approach
Luis Antonio Barron G. Vicente
Risk Management Officer
May/2013
CLASSIFICATION OF INFORMATION (CHECK WITH AN “X”):
CONFIDENTIAL AND RESTRICTED
CONFIDENTIAL
INTERNAL USE
X PUBLIC
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
RISK MODELING IN MULTI-ASSET CLASS CLEARINGHOUSES
DEFINING A ROBUST & EFFICIENT RISK MODEL
MULTI-ASSET CLASS AND MULTIMARKET
CLEARINGHOUSES
OPPORTUNITY TO INCREASE EFFICIENCY VIA
RISK-OFFSETTING
BUT HOW TO ENSURE THAT EFFICIENCY GAINS
ARE ROBUST?
Efficiency gains are not considered robust
when the assumptions employed by the riskoffsetting model have a low level of
adherence to reality, resulting in insufficient
resources for the clearinghouse to fulfill its
obligations
NEED TO BUILD A RISK MODEL THAT REFLECTS, IN A REALISTIC WAY, THE RISK
MANAGEMENT PROBLEM FACED BY A CLEARINGHOUSE
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RISK MODELING IN MULTI-ASSET CLASS CLEARINGHOUSES
THE RISK MANAGEMENT PROBLEM FACED BY A CLEARINGHOUSE
IN THE EVENT OF A PARTICIPANT DEFAULT, THE RISK MANAGEMENT PROBLEM OF FACED BY A CLEARINGHOUSE IS TO HAVE
THE RESOURCES AND LIQUIDITY NEEDED TO PROVIDE AN ORDERLY CLOSEOUT FOR THE SET OF POSITIONS HELD BY THE
PARTICIPANT, UNDER CURRENT MARKET CONDITIONS, CONSIDERING A MINIMUM HOLDING PERIOD
PORTFOLIO CLOSEOUT
PROCESS
T+0
T+1
T+2
T+3
T+4
...
T+N
MAJOR ASPECTS THAT SHOULD BE TAKEN INTO ACCOUNT BY THE MODEL
EVOLUTION (INTERTEMPORAL DYNAMICS) OF THE RISK FACTORS THAT
DEFINE THE VALUE OF THE ASSETS AND CONTRACTS INCLUDED IN THE
PORTFOLIO, AS WELL AS OF THE PORTFOLIO COMPOSITION ITSELF
FRICTIONS, RESTRICTIONS AND OPERATIONAL FEATURES ASSOCIATED
WITH EACH ASSET INCLUDED IN THE PORTFOLIO
TRADING MODEL – ELECTRONIC VS OTC
SETTLEMENT MODEL – RTGS VS DNS
LIQUIDITY/MARKET DEPTH
CASH FLOW STRUCTURE OF THE ASSET
POSSIBILITY OF A FRACTIONAL SETTLEMENT
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RISK MODELING IN MULTI-ASSET CLASS CLEARINGHOUSES
A MORE COMPLEX APPROACH THAN THAT OF MODELS BASED ON VAR
WHEN MODELLING THE RISK MANAGEMENT PROBLEM FACED BY A CLEARINGHOUSE, ONE MUST CONSIDER, IN A
JOINT FASHION, THE EVOLUTION OF THE MARKET VARIABLES (PRICES & RATES) AND THAT OF THE PORTFOLIO
COMPOSITION, RESPECTING A SET OF SIGNIFICANT RESTRICTIONS IMPOSED BY THE CHARACTERISTICS OF EACH
ASSET UNDER CONSIDERATION
PORTFOLIO
CLOSEOUT RISK
P&L CALCULATION
T+0
T+1
T+2
T+3
T+4
...
T+N
DYNAMIC PROCESS WITH FRICTIONS
THIS TYPE OF MODELLING REQUIRES CONCEPTS AND TOOLS MORE COMPLEX THAN THOSE TYPICALLY EMPLOYED
BY THE FINANCIAL INDUSTRY (I.E. MODELS BASED ON VAR). IN FACT, THESE MODELS OFTEN FOCUS ON
MEASURING THE POTENTIAL VALUE OF A STATIC PORTFOLIO, WITHOUT TAKING INTO ACCOUNT A DYNAMIC
CLOSEOUT PROCESS WITH FRICTIONS
VARIATION RISK OF
THE PORTFOLIO
VALUE
P&L CALCULATION
T+0
T+N
STATIC PROCESS WITHOUT FRICTIONS
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RISK MODELING IN MULTI-ASSET CLASS CLEARINGHOUSES
A MORE COMPLEX APPROACH THAN THAT OF MODELS BASED ON VAR (CONT’D)
ALTHOUGH THE MODELS BASED ON VAR MAY BE ADAPTED TO ESTIMATE THE CLOSEOUT RISK, THEIR
PLAUSIBILITY IS COMPROMISED WHEN MULTI-ASSET AND MULTIMARKET PORTFOLIOS (I.E. HIGHLY
HETEROGENEOUS) ARE CONSIDERED
UNDERLYING HYPOTHESIS: ALL ASSETS & CONTRACTS ARE TO BE SETTLED AT THE
SAME TIME WITHOUT ANY FRICTIONS, WITH FULLY COINCIDING CASH FLOWS
IMPLICIT CLOSEOUT
MODEL
T+0
T+N
AN ALTERNATIVE APPROACH CONSISTS IN THE USE OF A MODEL BASED ON MULTIPLE SILOS, WHERE EACH SILO
CONTAINS ONLY ASSETS AND/OR CONTRACTS WITH COMMON FEATURES (I.E. HOMOGENEOUS). IN THIS CASE,
THE TOTAL PORTFOLIO RISK IS GIVEN BY THE ALGEBRAIC SUM OF EACH SILO.
IMPLICIT CLOSEOUT
MODEL
SUM OF RISKS
T+0
T+N
SILO 1
T+0
T+0
T+N
SILO 2
T+N
SILO 3
7
...
RISK MODELING IN MULTI-ASSET CLASS CLEARINGHOUSES
SILO MODELLING & SYSTEMIC RISK INCREASE
EVEN A MODEL BASED ON SILOS, WITH SUPERCOLLATERALIZATION VIA SUM OF RISKS, DOES NOT NECESSARILY ENSURE A
MORE ROBUST SYSTEM. IN FACT, A MODEL BASED ON SILOS MAY HIDE IMPORTANT RISKS OF LIQUIDITY FRAGMENTATION
AND REDUCE INCENTIVES TOWARDS THE ADOPTION OF A DILIGENT BEHAVIOR IN TIMES OF CRISIS.
ORIGINAL
SITUATION,
AGENTS “A” & “B”
COLLATERAL (RISK) = 100
T+0
T+N
T+0
SILO 1
T+N
SILO 2
INCREASED MARKET VOLATILITY
AGENT “A” HEDGES
SILO 2 RISK ON THE
MARKET
COLLATERAL(RISK) = 200
T+0
T+N
T+0
SILO 1
T+N
LIQUIDITY RISK INCREASES
IN THE SYSTEM
SILO 2
AGENT “B” DOES
NOT HEDGE AT ALL
COLLATERAL (RISK) = 100
T+0
T+N
SILO 1
T+0
DISINCENTIVE TOWARDS A
DILIGENT BEHAVIOR
T+N
SILO 2
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LTCM SCENARIOS (1998) &
NTN-D CRISIS (2002)
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
THE CORE MODEL FOR RISK CALCULATION
THE CORE MODEL
THE CORE MODEL WAS SPECIFICALLY DEVELOPED BY BM&FBOVESPA TO ALLOW FOR ROBUST AND EFFICIENT RISK
ESTIMATION IN A MULTI-ASSET CLASS, MULTIMARKET CLEARINGHOUSE
MAJOR FEATURES
CONSIDERS THE INTERTEMPORAL DYNAMICS OF THE PORTFOLIO CLOSEOUT PROCESS
CONTEMPLATES IMPORTANT FRICTIONS & RESTRICTIONS ASSOCIATED WITH THE SETTLEMENT
PROCESS OF ASSETS AND CONTRACTS – TRADING DYNAMICS, MARKET LIQUIDITY AND DEPTH, CASH
FLOW STRUCTURE, ETC
ESTIMATES, IN BOTH A JOINT AND A CONSISTENT MANNER, THE MARKET AND LIQUIDITY RISKS
ASSOCIATED WITH A PORTFOLIO CLOSEOUT PROCESS
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THE CORE MODEL FOR RISK CALCULATION
OVERVIEW: CLOSEOUT RISK CALCULATION IN THREE STEPS
1. DETERMINING
THE CLOSEOUT
STRATEGY
T+0
T+1
T+2
T+3
T+4
...
T+N
2. RISK EVALUATION
T+0
T+1
T+2
T+3
T+4
...
T+N
T+1
T+2
T+3
T+4
...
CLOSEOUT RISK
PERMANENT LOSS
TRANSIENT LOSS
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Defines the (stress) scenarios associated with
the dynamics of each risk factor relevant to
the portfolio. All assets and contracts are
reevaluated considering the scenarios
defined in this step (full valuation).
Calculates and aggregates intertemporally
P&L associated with each scenario,
considering the defined closeout strategy
3. POTENTIAL P&L
CALCULATION
T+0
Defines the portfolio closeout strategy which,
respecting the settlement restrictions of the
portfolio of assets/markets, should minimize
the risk of a loss associated with the closeout
process, preserving existing hedge strategies
T+N
Result: Two risk measures—market and
liquidity—that are estimated both jointly and
consistently
THE CORE MODEL FOR RISK CALCULATION
OVERVIEW: PERMANENT & TRANSIENT LOSS
3. POTENTIAL P&L
DETERMINATION
T+0
+
V1
+
V2
+
V3
+
T+3
V4
+ ...
T+4
VN
V0
...
T+N
CASH NEED ON T+N
EQUALS
PERMANENT
LOSS
CASH NEED BY T+0
V0
+
V1
V0
+
V1
+
V2
V0
+
V1
+
V2
+
V3
V0
+
V1
+
V2
+
V3
+
V4
V0
+
V1
+
V2
+
V3
+
V4
CASH NEED BY T+1
CASH NEED BY T+2
CASH NEED BY T+3
CASH NEED BY T+4
+ ...
VN
12
CASH NEED BY T+N
MAXIMUM BETWEEN
CASH FLOW AMOUNTS
V0
T+2
T+1
TRANSIENT LOSS
THE CORE MODEL FOR RISK CALCULATION
DETAIL: CLOSEOUT STRATEGY DEFINITION
T+0
T+1
T+2
T+3
T+4
T+5
CLOSEOUT
PORTFOLIO
FUTURES, BUY, IMMEDIATE SETTLEMENT
OPTIONS, SELL, SETTLEMENT ON T+3 ONLY
1
NAIVE STRATEGY
2
OPTIMAL STRATEGY DEFINITION
3
OPTIMAL STRATEGY
RISK
SWAP, SELL, SETTLEMENT ON T+5 ONLY
MINIMUM RISK
ITERATION
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THE CORE MODEL FOR RISK CALCULATION
DETAIL: PORTFOLIO COMPOSITION & RISK FACTOR EVOLUTION
T+1
T+2
T+3
T+4
T+5
T+6
T+4
T+5
T+6
P&L ALONG THE PROCESS
T+0
CLOSEOUT
PORTFOLIO
FACTOR 1
FACTOR 2
FACTOR n
T+0
MARKET
T+1
T+2
T+3
RISK FACTOR EVOLUTION
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THE CORE MODEL FOR RISK CALCULATION
DETAIL: RISK FACTOR EVOLUTION & MULTIVARIATE SCENARIO GENERATION
FACTOR 1
FACTOR 1
FACTOR 2
MULTIVARIATE
FACTOR 2
SCENARIO
...
GENERATOR
...
...
...
...
...
FACTOR n
FACTOR n
T+0 – T+1 – T+2- ... – T+N
T+0 – T+1 – T+2- ... – T+N
# SCENARIO
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
SCENARIOS TO DETERMINE P&L DURING
THE CLOSEOUT PROCESS
...
...
...
...
...
...
...
T+0 – T+1 – T+2 – ... – T+N
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THE CORE MODEL FOR RISK CALCULATION
DETAIL: P&L DETERMINATION DURING THE CLOSEOUT PROCESS
PERMANENT LOSS
TRANSIENT LOSS
PERMANENT LOSS
TRANSIENT LOSS
#2
PERMANENT LOSS
TRANSIENT LOSS
#3
...
...
...
...
...
PERMANENT LOSS
TRANSIENT LOSS
#nSCN
SCENARIOS
T+1
T+2
T+3
T+4
16
T+5
T+6
POSITIVE FLOW
NEGATIVE FLOW
WORST CASE SCENARIO
#1
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
HEDGING STRATEGIES BENEFITING FROM THE CORE MODEL
MAIN EXAMPLES
HEDGING AN OTC DERIVATIVES POSITION ON THE LISTED DERIVATIVES MARKET
CLOSEOUT RISK
CORE RISK
T+0
T+1
T+2
T+3
T+4
...
T+N
SUM OF RISKS
CURRENT MODEL
T+0
T+T
T+0
T+T
T+0
T+N
SILO 1
SILO 2
SILO 3
OTC POSITION
LISTED DERIVATIVES
COLLATERAL
CORE RISK: PORTFOLIO CLOSEOUT COST (POSITIONS + COLLATERAL) MUST BE EQUAL TO OR LESS THAN ZERO
CURRENT MODEL: COLLATERAL-HAIRCUT EQUAL TO OR GREATER THAN RISK (OTC) + RISK (LISTED DERIVATIVES)
18
HEDGING STRATEGIES BENEFITING FROM THE CORE MODEL
MAIN EXAMPLES (CONT’D)
ASSET BEING HEDGED IS POSTED AS COLLATERAL
CLOSEOUT RISK
CORE RISK
T+0
T+1
T+2
T+3
T+4
...
T+N
SUM OF RISKS
CURRENT MODEL
T+0
T+T
T+0
T+N
SILO 1
SILO 2
LISTED DERIVATIVES
COLLATERAL
CORE RISK: PORTFOLIO CLOSEOUT COST (POSITIONS + COLLATERAL) MUST BE EQUAL TO OR LESS THAN ZERO
CURRENT MODEL: COLLATERAL-HAIRCUT EQUAL TO OR GREATER THAN RISK (LISTED DERIVATIVES)
19
HEDGING STRATEGIES BENEFITING FROM THE CORE MODEL
MAIN EXAMPLES (CONT’D)
EQUITIES BORROWER HOLDING COLLATERAL IN SHARES OF THE SAME COMPANY, BUT OF A DIFFERENT TYPE
(PREFERRED VS COMMON)
CLOSEOUT RISK
CORE RISK
T+0
T+1
T+2
T+3
T+4
...
T+N
SUM OF RISKS
CURRENT MODEL
T+0
T+T
T+0
T+N
SILO 1
SILO 2
EQUITIES LENDING
COLLATERAL
CORE RISK: PORTFOLIO CLOSEOUT COST (POSITIONS + COLLATERAL) MUST BE EQUAL TO OR LESS THAN ZERO
CURRENT MODEL: COLLATERAL-HAIRCUT EQUAL TO OR GREATER THAN RISK (LENDING)
20
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
CORE MODEL IMPLEMENTATION
MODEL COMPONENTS & IT ARCHITECTURE
OPTIMAL CLOSEOUT STRATEGY
DEFINITION
SPECIFIC SOFTWARE TO DEAL WITH OPTIMIZATION ISSUES
PRICE GENERATION BASED ON
MULTIVARIATE SCENARIOS
VERY HIGH PERFORMANCE PARALLEL ARCHITECTURE USING GRAPHIC UNITS WITH
MULTIPLE PROCESSORS (GPUs)
RISK AGGREGATION &
CONTROL
HIGH PERFORMANCE SOFTWARE DEVELOPED IN C++ BY BM&FBOVESPA
INTERFACE WITH THE RTC
PLATFORM (CINNOBER)
RISK PLUG-IN DEVELOPED BY BM&FBOVESPA IN TANDEM WITH CINNOBER
22
CORE MODEL IMPLEMENTATION
TEAMS INVOLVED
MODEL DEFINITION,
PROTOTYPE
CONSTRUCTION,
DEFINITIVE MODEL
TESTING
FINANCE
CONCEPTS (MR.
MARCO
AVELLANEDA/NYU
& MR. RAMA
CONT/COLUMBIA)
RISK
MANAGEMENT
OFFICE
IT OFFICE
POST-TRADING
CORE MODEL
DEVELOPMENT
23
INDEPENDENT
ASSESMENT, FEASIBILITY
ANALYSIS, SUPPORT TO
MODEL DEFINITION
CORE MODEL IMPLEMENTATION
PROJECT STATUS - MACRO
CONCEPTUAL MODEL
MATHEMATICAL
MODEL
PROTOTYPE
RISK PLUG-IN/CORE
DEC2010
JUL2010
DEC2011
JUL2011
PROTOTYPE PRESENTATION
24
DEC2012
MAR2013
AGENDA
RISK MODELING IN MULTI-ASSET CLASS AND MULTIMARKET CLEARINGHOUSES
THE CORE MODEL FOR CLEARINGHOUSE RISK CALCULATION
HEDGING STRATEGIES THAT BENEFIT FROM THE CORE MODEL
CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
KEY BENEFITS DERIVED FROM THE CORE MODEL IMPLEMENTATION
DEVELOPED SPECIFICALLY TO DEAL WITH THE RISK MANAGEMENT PROBLEM FACED BY CLEARINGHOUSES
ROBUST MODELLING PROVIDING EFFICIENCY GAINS WITHOUT GIVING UP SAFETY
TRANSPARENT & INTUITIVE MODEL – ASSUMPTIONS CA BE EASILY VALIDATED
MARKET & LIQUIDITY RISKS ARE TREATED IN BOTH A JOINT AND A CONSISTENT MANNER
GREATER EFFICIENCY IN CAPITAL ALLOCATION FOR PORTFOLIOS WITH RISK MITIGATION STRATEGIES (HEDGE)
INCENTIVES TO THE ADOPTION OF PRUDENTIAL MEASURES TO MITIGATE RISKS
CIRCUMVENTS THE SILO APPROACH, SO LIQUIDITY FRAGMENTATION IS AVOIDED AND SYSTEMIC RISK MITIGATED
26