© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133

Corporate Bonds as Eligible 

Collateral for Derivative Transactions

Presentation to the CFTC & SEC Staff

October 20, 2011
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 2

Summary

ß U.S. Life Insurance Industry is the second largest buyer of 

corporate bonds in the U.S.

ß High quality corporate bonds are an eligible collateral type under 

most bi-lateral credit-support annexes (“CSAs”) between life 

insurers and their derivative bank/dealer counterparties

ß We believe that high quality corporate bonds should be eligible 

collateral to satisfy the proposed derivatives margin requirements 

imposed by Dodd-Frank

ß Our analysis demonstrates that with reasonable diversification and 

appropriate haircuts, high-quality corporate bonds utilized as 

derivatives collateral provide more than adequate protection in the 

event of a counterparty default

The material contained in this presentation including, but not limited to, the calculations and analysis, was prepared by ACLI solely for 

illustrative purposes, and should not be reproduced, distributed, relied upon or used for any purpose.
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 3

U.S. Life Insurers: Key Investors in U.S. 

Corporate Securities

ß Life insurers provide the second largest U.S. source of 

corporate bond financing; holding 13.5% of total U.S. 

corporate debt outstanding (over $2 Trillion at end of 2010)

ß In 2008, approximately 56% of life insurers’ $4.6 Trillion of 

total assets were held in bonds

• 42% in corporate bonds

• 14% in government bonds

ß Over 41% of corporate bonds purchased by life insurers 

have maturities in excess of 20 years (at time of purchase)

Based on data from NAIC and the U.S. Federal Reserve Board, Flow of Funds Accounts of the U.S. See American Council of Life 

Insurers, Life Insurers Fact Book (2009).
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 4

Analysis: Selecting an Appropriate 

Universe

Challenges

ß Develop a broad universe of high-quality issuers without directly 

referencing public rating agency ratings

ß Ensure universe of securities is limited to large liquid issues

ß Determine that a ready source of daily pricing exists for securities 

within universe

ß Verify that a source of historical data is available for back-testing 

purposes

Approaches Considered

ß Utilizing the CDX IG Index for Issuers; not enough individual CUSIPs

ß Determining universe based on credit spreads; stability of universe 

a concern, would include small issue size 
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 5

Analysis: Universe Selection

ß We decided to explore broad-based indices of U.S. Credit published by 

major broker-dealers

ß This approach would have many advantages, including:

• Clearly defined and publicly available index rule book

• Defined list of eligible CUSIPs

• Securities limited to large liquid issues as defined in the index rules

• Ready source of daily pricing & historical data

ß A number of Dealers construct and maintain indices on corporate credit

• Bank of America, Barclays, JPMorgan

ß We selected the Barclays U.S. Credit Index as the source data for our 

analysis

• One of the oldest, most established index in the U.S. (predecessor. Lehman 

U.S. Credit index was established in 1973)

• Widely benchmarked by money managers, thus wide acceptability by other 

real money derivative end users

Source: Barclays Capital Indices, POINT ©2011 Barclays Capital Inc. Used with permission. Barclays Capital and POINT are registered 

trademarks of Barclays Capital Inc.
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 6

Analysis: Barclays U.S. Credit Index

ß Barclays U.S. Credit Index comprises the U.S. Corporate Index and a 

non-corporate component that includes foreign agencies, sovereigns, 

supranationals and local authorities

ß Only high quality U.S. $-denominated fixed-rate securities are included 

in the index

ß Index history is available back to 1973

ß U.S. Credit Index is a subset of the U.S. Government/Credit Index and 

the U.S. Aggregate Index

Barclays U.S. Credit Index

Issues: 4,430 Currency: USD

Amt Outstanding: $3.4 trillion Avg Maturity: 10-yrs

Source: Barclays Capital Indices, POINT ©2011 Barclays Capital Inc. Used with permission. Barclays Capital and POINT are registered 

trademarks of Barclays Capital Inc.
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 7

Analysis: Single CUSIP Statistics

Results

ß We began our analysis looking largest 10-day moves across all of the 

individual CUSIPs in the Barclays Credit Index universe

ß Our analysis, summarized in the table below, lists the number of individual 

CUSIPs that had a 10-day price decline, bucketed by severity of the decline 

ß For example, in 2008, 628 CUSIPs experienced a 10-day price decline of 

more than 20%

ß Conclusion: Tail events are rare, but they do occur

Period Total >0% >10% >20% >30% >40% >50% >60% >70% >80% >90% 100%

2007-2011 6493 6383 2140 708 278 155 85 39 18 11 9 0

2011 4552 4452 2 0 0 0 0 0 0 0 0 0

2010 4735 4730 58 5 0 0 0 0 0 0 0 0

2009 4332 4312 567 182 77 44 16 7 6 2 1 0

2008 3947 3862 1988 628 227 120 71 32 12 9 8 0

2007 3642 3635 79 13 1 0 0 0 0 0 0 0
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 8

Challenge: Develop Rules to Reduce 

Exposure to Tail Risk

ß Our Hypothesis: Diversification rules limiting concentration should 

reduce exposure to tail risk

ß Diversification Rules adopted for our analysis:

• 5% Maximum Issuer Weight

• 45% Maximum Sector Weighting (Financial Institutions, Industrials, 

Utilities, Transportation, Agencies, Local Authorities, Sovereign, and 

Supranational)

ß We tested the 4 highest periods of historical volatility since 2007

ß Results: Benefits of diversification come quickly as CUSIPs are 

added across sectors
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 9

Portfolio Simulation

Testing Methodology

ß Step 1: Chose a single month to run to ensure a continuous set 

of CUSIPs 

ß Step 2: Selected a random portfolio on the 1st Day of the month 

subject to diversification rules

ß Step 3: Calculated the market value of the equally weighted 

portfolio as it evolves through the month

ß Step 4: Calculated the largest 10-day price drop that occurred 

during the month

ß Step 5: Store the result

Repeat this procedure to gain the full distribution of simulated portfolio results
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 10

Portfolio Simulation

Benefits of Issuer Diversification

Most diversification benefit is achieved with a small increase in CUSIPs

0

500

1,000

1,500

2,000

2,500

3,000

-90 -80 -70 -60 -50 -40 -30 -20 -10 0

Portfolio % Chg

Simulations: 10,000

Mean -7.58

Median -4.96

Maximum 0.00

Minimum -94.41

Std. Dev. 10.10

0

200

400

600

800

1,000

1,200

-20 -18 -16 -14 -12 -10 -8 -6 -4 -2

Portfolio % Chg

Simulations: 10,000

Mean -6.44

Median -5.97

Maximum -1.65

Minimum -19.61

Std. Dev. 2.32

Portfolio 10-Day Maximum Decline by Number of CUSIPs in Portfolio

September 2008

0

200

400

600

800

1,000

1,200

1,400

1,600

-14 -12 -10 -8 -6 -4 -2

Portfolio % Chg

Simulations: 10,000

Mean -6.06

Median -5.87

Maximum -2.19

Minimum -13.59

Std. Dev. 1.45

20 CUSIPPortfolio

0

200

400

600

800

1,000

1,200

1,400

1,600

-8 -7 -6 -5 -4

Portfolio % Chg

Simulations:10,000

Mean -5.58

Median -5.55

Maximum -3.38

Minimum -8.66

Std. Dev. 0.72

1 CUSIP Portfolio 10 CUSIP Portfolio

20 CUSIP Portfolio 50 CUSIP Portfolio

Portfolio % Loss Portfolio % Loss

Portfolio % Loss Portfolio % Loss

Occurrences Occurrences

Occurrences Occurrences
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 11

Portfolio Simulation

Broad-Based Historical Simulation of worst case decline over a 10-day 

period using a 99% confidence interval

Haircuts of 15-20% Provide Significant Cushion

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

-16 -14 -12 -10 -8 -6 -4 -2

Simulations 250,000

Mean -6.08

Median -5.89

Maximum -2.04

Minimum -16.92

Std. Dev. 1.45

99th Percentile – 10.25%

Portfolio 10-Day Maximum Decline 20 CUSIPs - 45% Sector Max

September 2008

Portfolio % Loss

Occurrences
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 12

Portfolio Overlap

Overlap Between Chosen Index and Alternative Suggests High Degree of 

Liquidity

ß We compared the pricing between the Barclay’s U.S. Credit Index 

and the Bank of America ML US Corporate Index where there was 

CUSIP overlap from 2007-2010

ß 95% of observations were priced within +/- 3.75pts between indices

Source #1: Barclays Capital Indices, POINT ©2011 Barclays Capital Inc. Used with permission. Barclays Capital and POINT are

registered trademarks of Barclays Capital Inc. Source #2: Bank of America Merrill Lynch

Cumulative % Overlap Within Price Bound

Overlap
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 13

Conclusions & Recommendations

ß Corporate bond tail risk can be controlled with basic diversification rules

ß Limiting issuer exposure to 5% per Issuer and High Level Sector exposures to 

45% achieves this result

ß Further diversification past these rules provides little incremental benefit while 

substantially increasing operational burdens

ß Corporate bonds haircut by 15-20% provide significant cushion when compared 

against historically stressful periods 

ß High quality Corporate bonds, appropriately haircut and diversified, should be an 

eligible collateral option for both cleared and uncleared derivative exposure

ß Other high-quality collateral types such as Agency Debentures and Agency 

RMBS should be considered as eligible collateral as well
Appendix
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 15

Source: Barclays Capital Indices, POINT ©2011 Barclays Capital Inc. Used with permission. Barclays Capital and POINT are registered 

trademarks of Barclays Capital Inc.

Portfolio Simulation

Historical Index Price Volatility

We selected the 4 highest volatility months since 2007 to test

Barclay’s Credit Index: Relative Index Price Volatility by Month

2007-2011
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 16

Portfolio 10-Day Maximum Decline by Historical Period

20 CUSIPs – 45% Sector Max

Portfolio Simulation

Historical Simulation

Results are intuitively in line with historical index level volatility

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

-16 -14 -12 -10 -8 -6 -4 -2

Portfolio % Chg

Simulations:250,000

Mean -6.07

Median -5.89

Maximum -2.04

Minimum -16.92

Std. Dev. 1.45

0

4,000

8,000

12,000

16,000

20,000

24,000

28,000

32,000

-16 -14 -12 -10 -8 -6 -4 -2

Portfolio % Chg

Simulations:250,000

Mean -7.59

Median -7.57

Maximum -0.52

Minimum -17.08

Std. Dev. 1.64

September 2008 October 2008

0

5,000

10,000

15,000

20,000

25,000

30,000

-8 -7 -6 -5 -4 -3 -2 -1 0

Portfolio % Chg

Simulations: 250,000

Mean -2.82

Median -2.69

Maximum -0.12

Minimum -8.44

Std. Dev. 0.91

0

5,000

10,000

15,000

20,000

25,000

30,000

-8 -7 -6 -5 -4 -3 -2 -1 0

Portfolio % Chg

Simulations: 250,000

Mean -2.63

Median -2.50

Maximum 0.00

Minimum -8.35

Std. Dev. 0.95

February 2009 March 2009

Portfolio % Loss Portfolio % Loss

Portfolio % Loss Portfolio % Loss

OccurrencesOccurrences

Occurrences

Occurrences
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 17

Portfolio Cumulative Maximum Decline 20 CUSIPs - 45% Sector Max

September 2008

Portfolio Simulation

Historical Simulation: Cumulative Monthly Change

0

5,000

10,000

15,000

20,000

25,000

30,000

-16 -14 -12 -10 -8 -6 -4 -2

Simulations 250,000

Mean -6.39

Median -6.10

Maximum -1.63

Minimum -17.38

Std. Dev. 1.91

Portfolio % Loss

Occurrences
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 18

Discount Window Corporate Collateral Margin 

Table1

1Extracted from the Federal Reserve Discount Window & Payment System Risk Collateral Margins Table

As of January 3, 2011 Overlap

Margin for Securities as a % of Market Value

Collateral Type Duration Buckets

Corporate Bonds 0-5 > 5-10 >10

AAA rated - U.S. Dollar Denominated 97% 95% 94%

BBB-AA rated - U.S. Dollar Denominated 95% 93% 92%

AAA rated - Foreign Denominated7 91% 89% 88%

ß FRB currently accepts Investment Grade corporate bonds as collateral at the Discount 

Window based on a schedule
© AMERICAN COUNCIL OF LIFE INSURERS

101 Constitution Ave., NW, Washington, DC 20001-2133 19

Disclaimer

The material contained in this presentation including, but not limited to, the 

calculations and analysis, was prepared by ACLI solely for illustrative purposes, 

and should not be reproduced, distributed, relied upon or used for any purpose.