Treasury Presentation to TBAC
Office of Debt Management

Fiscal Year 2017 Q4 Report
Table of Contents

2

I. Executive Summary p. 4

II. Fiscal

A. Quarterly Tax Receipts p. 6

B. Monthly Receipt Levels p. 7

C. Eleven Largest Outlays p. 8

D. Treasury Net Nonmarketable Borrowing p. 9

E. Cumulative Budget Deficits p. 10

F. Deficit and Borrowing Estimates p. 11

G. Budget Surplus/Deficit p. 12

III. Financing

A. Sources of Financing p. 15

B. OMB’s Projections of Net Borrowing from the Public p. 17

C. Interest Rate Assumptions p. 18

D. SOMA Normalization Impact on Net Marketable Borrowing p. 19

IV. Portfolio Metrics

A. Historical Weighted Average Maturity of Marketable Debt Outstanding p. 23

B. Maturity Profile p. 24

V. Demand

A. Summary Statistics p. 29

B. Bid-to-Cover Ratios p. 30

C. Investor Class Awards at Auction p. 35

D. Primary Dealer Awards at Auction p. 39

E. Direct Bidder Awards at Auction p. 40

F. Foreign Awards at Auction p. 41
Section I:

Executive Summary

3
Receipts and Outlays

• During fiscal year 2017, total receipts were up by 1 percent year-over-year driven mainly by individual income and payroll taxes which 

increased by $110 billion. YoY corporate taxes have declined $7 billion; one contributing factor could be the tax extension relief offered 

to companies affected by Hurricanes Harvey and Irma. 

• During fiscal year 2017, total outlays were up by $128 billion (3 percent) year-over-year driven mainly by these 5 categories: Health and 

Human Services outlays were $14 billion higher due to increases in Medicare and Medicaid. Social Security Administration outlays were 

up $24 billion due to increases in program enrollment. Treasury outlays have increased $20 billion mainly due to higher inflation 

accretions. Education and Housing and Urban Development outlays were up $29 billion and $35 billion, respectively, due to large 

subsidy re-estimate differences. 

Sources of Financing 

• Based on the Quarterly Borrowing Estimate, Treasury’s Office of Fiscal Projections currently projects a net marketable borrowing need 

of $275 billion for Q1 FY 2018, with an end-of-December cash balance of $205 billion. For Q2 FY 2018, the net marketable borrowing 

need is projected to be $512 billion, with an end-of-March cash balance of $300 billion.

Projected Net Marketable Borrowing

• Treasury continues to analyze and model various scenarios to address potential funding needs based on deficit forecasts and 

expectations for SOMA Treasury redemptions. Recent Primary Dealer estimates show a wide distribution for net marketable 

borrowing, reflecting uncertainty in fiscal outlook. 

• Assumes SOMA capped redemptions end date in the first quarter of CY 2022. The assumption is based on the September FEDS Notes

“Projected Evolution of the SOMA Portfolio and the 10-year Treasury Term Premium Effect.” 

Demand for Treasury Securities

• Bid-to-Cover ratios for bills remain above the crisis-era levels. Demand for the short and intermediate coupons remains strong while 

Bid-to-Cover ratios for longer term coupons, FRNs and TIPS remain flat. 

Award allocation

• September total foreign awards were below average. One contributing factor was the deferred settlement date for month-end coupon 

auctions (2s, 5s and 7s) due to September 30, 2017 falling on a weekend. If these auction awards were included in September total, the 

foreign awards would be approximately $8 billion higher. 

Highlights of Treasury’s November 2017 Quarterly Refunding Presentation

to the Treasury Borrowing Advisory Committee (TBAC)

4
Section II:

Fiscal

5
6

Source: United States Department of the Treasury 

(50%)

(40%)

(30%)

(20%)

(10%)

0%

10%

20%

30%

40%

50%

60%

Sep-07

Dec-07

Mar-08

Jun-08

Sep-08

Dec-08

Mar-09

Jun-09

Sep-09

Dec-09

Mar-10

Jun-10

Sep-10

Dec-10

Mar-11

Jun-11

Sep-11

Dec-11

Mar-12

Jun-12

Sep-12

Dec-12

Mar-13

Jun-13

Sep-13

Dec-13

Mar-14

Jun-14

Sep-14

Dec-14

Mar-15

Jun-15

Sep-15

Dec-15

Mar-16

Jun-16

Sep-16

Dec-16

Mar-17

Jun-17

Sep-17

Year-over-Year % Change

Quarterly Tax Receipts

Corporate Taxes Non-Withheld Taxes (incl SECA) Withheld Taxes (incl FICA)
7

Individual Income Taxes include withheld and non-withheld. Social Insurance Taxes include FICA, SECA, RRTA, UTF deposits, FUTA and 

RUIA. Other includes excise taxes, estate and gift taxes, customs duties and miscellaneous receipts. 

Source: United States Department of the Treasury 

0

20

40

60

80

100

120

140

Sep-07

Jan-08

May-08

Sep-08

Jan-09

May-09

Sep-09

Jan-10

May-10

Sep-10

Jan-11

May-11

Sep-11

Jan-12

May-12

Sep-12

Jan-13

May-13

Sep-13

Jan-14

May-14

Sep-14

Jan-15

May-15

Sep-15

Jan-16

May-16

Sep-16

Jan-17

May-17

Sep-17

$ bn

Monthly Receipt Levels

(12-Month Moving Average)

Individual Income Taxes Corporation Income Taxes Social Insurance Taxes Other
0

200

400

600

800

1,000

1,200

HHS

SSA

Defense

Treasury

Agriculture

Labor

VA

Transportation

OPM

Education

Other Defense Civil

$ bn

Eleven Largest Outlays

Oct - Sep FY 2016 Oct - Sep FY 2017

Source: United States Department of the Treasury 8
9 Source: United States Department of the Treasury 

(40)

(30)

(20)

(10)

0

10

20

30

Q4-07Q1-08Q2-08Q3-08Q4-08Q1-09Q2-09Q3-09Q4-09Q1-10Q2-10Q3-10Q4-10Q1-11Q2-11Q3-11Q4-11Q1-12Q2-12Q3-12Q4-12Q1-13Q2-13Q3-13Q4-13Q1-14Q2-14Q3-14Q4-14Q1-15Q2-15Q3-15Q4-15Q1-16Q2-16Q3-16Q4-16Q1-17Q2-17Q3-17Q4-17

$ bn

Fiscal Quarter

Treasury Net Nonmarketable Borrowing

Foreign Series State and Local Govt. Series (SLGS) Savings Bonds
10 Source: United States Department of the Treasury 

0

100

200

300

400

500

600

700

800

October

November

December

January

February

March

April

May

June

July

August

September

$ bn

Cumulative Budget Deficits by Fiscal Year

FY2015 FY2016 FY2017
11

FY 2018-2020 Deficits and Net Marketable Borrowing Estimates In $ billions

Primary 

Dealers1 CBO2 CBO3 OMB4

FY 2018 Deficit Estimate 677 563 593 440

FY 2019 Deficit Estimate 786 689 689 526

FY 2020 Deficit Estimate 853 775 664 488

FY 2018 Deficit Range 560-850

FY 2019 Deficit Range 650-975

FY 2020 Deficit Range 680-1100

FY 2018 Net Marketable Borrowing Estimate 869 881* 912* 529

FY 2019 Net Marketable Borrowing Estimate 906 745 748 604

FY 2020 Net Marketable Borrowing Estimate 946 826 719 552

FY 2018 Net Marketable Borrowing Range 635-1100

FY 2019 Net Marketable Borrowing Range 661-1100

FY 2020 Net Marketable Borrowing Range 720-1150

Estimates as of: Oct-17 Jul-17 Jun-17 May-17

1Based on primary dealer feedback on October 23, 2017. Estimates above are averages. 

2Summary Table 1 of CBO's "An Update to the Budget and Economic Outlook: 2017 to 2027"

3Table 1 and 2 of CBO's "An Analysis of the President's 2018 Budget"

4Table S-10 of OMB's “Budget of the United States Government, Fiscal Year 2018” 

*For FY 2018, the restoration of extraordinary measures used during debt limit impasse artificially adds this amount to 

“Other means of financing” which shows a larger net borrowing assumption.
(12%)

(10%)

(8%)

(6%)

(4%)

(2%)

0%

2%

(1,600)

(1,400)

(1,200)

(1,000)

(800)

(600)

(400)

(200)

0

200

200820092010

20112012

20132014

20152016

201720182019

20202021

202220232024

20252026

2027

% of GDP

$ bn

Fiscal Year

Budget Surplus/Deficit

Surplus/Deficit (LHS) Surplus/Deficit (RHS)

Projections are from Table S-10 of “Budget of The U.S. Government Fiscal Year 2018.” 12

OMB’s Projection
Section III:

Financing

13
14

Assumptions for Financing Section (pages 15 to 20)

• Portfolio and SOMA holdings as of 09/30/2017.

• Assumes SOMA capped redemptions end date in the first quarter of CY 2022. The assumption is based 

on September FEDS Notes of “Projected Evolution of the SOMA Portfolio and the 10-year Treasury 

Term Premium Effect.” 

• Assumes announced issuance sizes and patterns constant for nominal coupons, TIPS, and FRNs as of 

09/30/2017, while using an average of ~$1.8 trillion of bills outstanding. 

• The principal on the TIPS securities was accreted to each projection date based on market ZCIS levels 

as of 09/30/2017. 

• No attempt was made to match future financing needs. 
15

Sources of Financing in Fiscal Year 2017 Q4

*An end-of-September 2017 cash balance of $159 billion versus a beginning-of-July 2017 cash balance of $181 billion. By keeping the cash 

balance constant, Treasury arrives at the net implied funding number. 

Gross issuance values include SOMA add-ons.

Net Bill Issuance 84 Security Gross Maturing Net Gross Maturing Net

Net Coupon Issuance 105 4-Week 475 500 (25) 2,318 2,343 (25)

Subtotal: Net Marketable Borrowing 189 13-Week 513 507 6 1,975 1,964 11

26-Week 435 372 63 1,663 1,564 99

Ending Cash Balance 159 52-Week 60 60 0 260 230 30

Beginning Cash Balance 181 CMBs 105 65 40 268 228 40

Subtotal: Change in Cash Balance (22) Bill Subtotal 1,588 1,504 84 6,484 6,329 155

Net Implied Funding for FY 2017 Q4* 211

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 43 41 2 173 164 9

2-Year 55 26 29 315 240 75

3-Year 80 81 (1) 313 348 (35)

5-Year 73 96 (23) 413 444 (32)

7-Year 60 60 0 340 351 (11)

10-Year 70 28 42 276 99 177

30-Year 44 11 33 172 45 126

5-Year TIPS 14 0 14 44 48 (3)

10-Year TIPS 25 17 9 76 37 39

30-Year TIPS 0 0 0 19 0 19

Coupon Subtotal 464 359 105 2,140 1,777 364

Total 2,052 1,863 189 8,624 8,105 519

Coupon Issuance Coupon Issuance

July - September 2017 July - September 2017 Fiscal Year-to-Date

Bill Issuance Bill Issuance

July - September 2017 Fiscal Year-to-Date
16

Sources of Financing in Fiscal Year 2018 Q1

*Keeping announced issuance sizes and patterns constant for nominal coupons, TIPS, and FRNs as of 09/30/2017. 

**Assumes an end-of-December 2017 cash balance of $205 billion versus a beginning-of-October 2017 cash balance of $159 billion.

Financing Estimates released by the Treasury can be found here: http://www.treasury.gov/resource-center/data-chart-center/quarterlyrefunding/Pages/Latest.aspx

Assuming Constant Coupon Issuance Sizes*

Treasury Announced Net Marketable Borrowing** 275

Net Coupon Issuance 128

Implied Change in Bills 147

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 41 41 0 41 41 0

2-Year 78 26 52 78 26 52

3-Year 72 78 (6) 72 78 (6)

5-Year 102 147 (45) 102 147 (45)

7-Year 84 72 12 84 72 12

10-Year 63 17 46 63 17 46

30-Year 39 0 39 39 0 39

5-Year TIPS 14 0 14 14 0 14

10-Year TIPS 11 0 11 11 0 11

30-Year TIPS 5 0 5 5 0 5

Coupon Subtotal 509 381 128 509 381 128

October - December 2017

October - December 2017 Fiscal Year-to-Date

Coupon Issuance Coupon Issuance
17

OMB’s projections of net borrowing from the public are from Table S-10 of “Budget of the U.S. Government Fiscal Year 2018.” 

“Other” represents borrowing from the public to provide direct and guaranteed loans.

529

604

552 515 493

369

263 229

163 35

50%

55%

60%

65%

70%

75%

80%

(700)

(500)

(300)

(100)

100

300

500

700

900

2018201920202021202220232024202520262027

$ bn

OMB's Projection of Borrowing from the Public

Primary Deficit Net Interest Other Debt Held by Public

as % of GDP (RHS)

Debt Held by Public Net of

Financial Assets as a % of GDP (RHS)

The bubble represents the total net borrowing from the public for that year

$ bn %

Primary Deficit (2,017) -54

Net Interest 5,166 138

Other 603 16

Total 3,752 100

FY2018 - FY2027 Cumulative Total
18

OMB's economic assumption of the 10-Year Treasury Note rates are from Table S-9 of OMB’s “Budget of the United States Government, Fiscal 

Year 2018.” The forward rates are the implied 10-Year Treasury Note rates on September 30 of that year.

1

1.5

2

2.5

3

3.5

4

20172018201920202021202220232024202520262027

10-Year Treasury Note Rate, %

Interest Rate Assumptions: 10-Year Treasury Note

OMB FY 2018 Budget Implied Forward Rates as of 09/30/2017

10-Year Treasury Rate of 2.33% 

as of 09/30/2017
19

Impact of SOMA Actions on Projected Net Borrowing Assuming Future 

Issuance Remains Constant

Treasury’s primary dealer survey estimates can be found on page 11. OMB's projections of net borrowing from the public are from Table S-10 of 

“Budget of the U.S. Government Fiscal Year 2018.” CBO's estimates of the borrowing from the public are from Summary Table 1 of “The Budget 

and Economic Outlook: 2017 to 2027.” CBO’s analysis of the President’s budget for net public borrowing estimates are from Table 2 of CBO’s 

“An Analysis of the President’s 2018 budget.” See table at the end of this section for details.

*Reflects capped SOMA Treasury redemptions up until the first quarter of CY 2022. 

**For both of FY 2018 CBO projections, the restoration of extraordinary measures used during debt limit impasse artificially adds this amount to 

“Other means of financing” which shows a larger net borrowing assumption.

0

200

400

600

800

1,000

1,200

1,400

1,600

2018201920202021202220232024202520262027

Fiscal Year

With Capped Fed Redemptions ($ bn)*

Projected Net Borrowing CBO's "An Analysis of the

President''s 2018 Budget "

OMB's FY 2018 Budget

of the U.S. Government

PD Survey Marketable

Borrowing Estimates

CBO's "An Update to the Budget and

Economic Outlook: 2017 to 2027"
20

Historical Net Marketable Borrowing and Projected Net Borrowing 

Assuming Future Issuance Remains Constant, $ billions

Net Borrowing capacity reflects capped SOMA redemptions up until the first quarter of CY 2022. 

Treasury’s primary dealer survey estimates can be found on page 11. OMB's projections of net borrowing from the public are from Table S-10 of 

“Budget of the U.S. Government Fiscal Year 2018.” CBO's estimates of the borrowing from the public are from Table 1 of “The Budget and 

Economic Outlook: 2017 to 2027.” CBO’s analysis of the President’s budget for net public borrowing estimates are from Table 2 of CBO’s “An 

Analysis of the President’s 2018 budget.”

*For FY 2018, the restoration of extraordinary measures used during debt limit impasse artificially adds this amount to “Other means of 

financing” which shows a larger net borrowing assumption.

Fiscal 

Year Bills 2/3/5 7/10/30 TIPS FRN

Historical/Projected 

Net Borrowing 

Capacity

OMB's FY 2018 

Budget of the U.S. 

Government

CBO's "An Analysis of 

the President''s 2018 

Budget "

Primary Dealer 

Survey

2013 (86) 86 720 111 0 830 

2014 (119) (92) 669 88 123 669 

2015 (53) (282) 641 88 164 558 

2016 289 (82) 477 64 47 795 

2017 155 9 292 55 9 519 

2018 0 92 276 55 0 423 529 912* 869 

2019 0 61 101 46 (6) 201 604 748 906 

2020 0 (31) 138 15 (7) 116 552 719 946 

2021 0 (53) 134 (4) (3) 73 515 747 

2022 0 15 205 (11) 2 211 493 797 

2023 0 27 172 (9) 6 196 369 737 

2024 0 12 152 (10) 1 155 263 694 

2025 0 (21) 157 (52) (1) 83 229 758 

2026 0 (22) 177 (43) (2) 110 163 782 

2027 0 3 151 (33) (2) 119 35 787 
Section IV:

Portfolio Metrics

21
22

Assumptions for Portfolio Metrics Section (pages 23 to 27) and Appendix

• Portfolio and SOMA holdings as of 09/30/2017.

• Assumes SOMA capped redemptions end date in the first quarter of CY 2022. The assumption is based 

on the September FEDS Notes “Projected Evolution of the SOMA Portfolio and the 10-year Treasury 

Term Premium Effect.”

• Assumes announced issuance sizes and patterns constant for nominal coupons, TIPS, and FRNs as of 

09/30/2017, while using an average of ~$1.8 trillion of bills outstanding. 

• To match OMB’s projected borrowing from the public for the next 10 years, nominal coupon securities 

(2-, 3-, 5-, 7-, 10-, and 30-year) were adjusted by the same percentage.

• The principal on the TIPS securities was accreted to each projection date based on market ZCIS levels 

as of 09/30/2017.

• OMB’s estimates of borrowing from the public are Table S-10 of the “Budget of the U.S. Government 

Fiscal Year 2018.”
23

40

45

50

55

60

65

70

75

80

1980198219841986198819901992199419961998200020022004200620082010201220142016

Weighted Average Maturity (Months)

Calendar Year

Historical Weighted Average Maturity of Marketable Debt Outstanding

Historical Historical Average from 1980 to end of FY 2017 Q4

70.2 months on

9/30/2017

59.5 months (Historical Average

from 1980 to Present)
24

This scenario does not represent any particular course of action that Treasury is expected to follow. See table on following page for details. 

0

2

4

6

8

10

12

14

16

18

20

201820192020

202120222023

2024202520262027

$ tr

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
25

This scenario does not represent any particular course of action that Treasury is expected to follow. Portfolio composition by original issuance 

type and term can be found in the appendix (Page 44).

Recent and Projected Maturity Profile, $ billions

End of Fiscal Year <= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10 Total (0,5]

2010 2,563 1,141 895 1,273 907 856 853 8,488 5,872

2011 2,620 1,334 980 1,541 1,070 1,053 1,017 9,616 6,476

2012 2,951 1,373 1,104 1,811 1,214 1,108 1,181 10,742 7,239

2013 2,939 1,523 1,242 1,965 1,454 1,136 1,331 11,590 7,669

2014 2,935 1,739 1,319 2,207 1,440 1,113 1,528 12,281 8,199

2015 3,097 1,775 1,335 2,382 1,478 1,121 1,654 12,841 8,589

2016 3,423 1,828 1,538 2,406 1,501 1,151 1,800 13,648 9,195

2017 3,631 2,027 1,504 2,433 1,466 1,180 1,946 14,188 9,596

2018 3,862 2,017 1,560 2,484 1,538 1,210 2,072 14,743 9,923

2019 3,853 2,119 1,644 2,581 1,639 1,313 2,229 15,378 10,197

2020 3,924 2,207 1,641 2,727 1,656 1,351 2,455 15,960 10,498

2021 4,012 2,182 1,782 2,776 1,692 1,380 2,682 16,506 10,752

2022 3,987 2,345 1,826 2,791 1,787 1,352 2,945 17,032 10,949

2023 4,150 2,367 1,812 2,777 1,810 1,318 3,202 17,436 11,107

2024 4,205 2,371 1,771 2,864 1,817 1,277 3,430 17,734 11,210

2025 4,177 2,344 1,788 3,007 1,771 1,234 3,679 18,001 11,316

2026 4,150 2,310 1,912 2,931 1,771 1,233 3,894 18,201 11,303

2027 4,117 2,415 1,915 2,833 1,622 1,292 4,080 18,274 11,280
26

This scenario does not represent any particular course of action that Treasury is expected to follow. See table on following page for details.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2018201920202021202220232024202520262027

Percent Compositioin

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
27

Recent and Projected Maturity Profile, percent

This scenario does not represent any particular course of action that Treasury is expected to follow. Portfolio composition by original issuance 

type and term can be found in the appendix (Page 44).

End of Fiscal Year <= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10 (0,3] (0,5]

2010 30.2 13.4 10.5 15.0 10.7 10.1 10.0 54.2 69.2

2011 27.2 13.9 10.2 16.0 11.1 10.9 10.6 51.3 67.3

2012 27.5 12.8 10.3 16.9 11.3 10.3 11.0 50.5 67.4

2013 25.4 13.1 10.7 17.0 12.5 9.8 11.5 49.2 66.2

2014 23.9 14.2 10.7 18.0 11.7 9.1 12.4 48.8 66.8

2015 24.1 13.8 10.4 18.5 11.5 8.7 12.9 48.3 66.9

2016 25.1 13.4 11.3 17.6 11.0 8.4 13.2 49.7 67.4

2017 25.6 14.3 10.6 17.1 10.3 8.3 13.7 50.5 67.6

2018 26.2 13.7 10.6 16.8 10.4 8.2 14.1 50.5 67.3

2019 25.1 13.8 10.7 16.8 10.7 8.5 14.5 49.5 66.3

2020 24.6 13.8 10.3 17.1 10.4 8.5 15.4 48.7 65.8

2021 24.3 13.2 10.8 16.8 10.3 8.4 16.2 48.3 65.1

2022 23.4 13.8 10.7 16.4 10.5 7.9 17.3 47.9 64.3

2023 23.8 13.6 10.4 15.9 10.4 7.6 18.4 47.8 63.7

2024 23.7 13.4 10.0 16.1 10.2 7.2 19.3 47.1 63.2

2025 23.2 13.0 9.9 16.7 9.8 6.9 20.4 46.2 62.9

2026 22.8 12.7 10.5 16.1 9.7 6.8 21.4 46.0 62.1

2027 22.5 13.2 10.5 15.5 8.9 7.1 22.3 46.2 61.7
Section V:

Demand

28
29

*Weighted averages of Competitive Awards.

**Approximated using prices at settlement and includes both Competitive and Non-Competitive Awards. For TIPS 10-year equivalent, a 

constant auction BEI is used as the inflation assumption.

Summary Statistics for Fiscal Year 2017 Q4 Auctions

Security 

Type Term Stop Out Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards 

($bn)

% 

Primary 

Dealer*

% 

Direct*

% 

Indirect*

Non-Competitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)**

Bill 4-Week 0.978 3.1 469.2 61.7 10.3 28.0 5.7 0.0 4.1

Bill 13-Week 1.047 3.1 502.1 52.6 7.3 40.1 7.0 0.0 14.5

Bill 26-Week 1.132 3.2 421.4 46.8 4.2 49.0 5.9 0.0 24.6

Bill 52-Week 1.220 3.2 59.2 55.6 7.0 37.5 0.7 0.0 6.7

Bill CMB 1.029 3.6 105.0 66.6 5.5 27.8 0.0 0.0 1.7

Coupon 2-Year 1.401 2.9 77.3 34.4 16.2 49.5 0.4 6.7 18.9

Coupon 3-Year 1.509 2.9 71.5 35.6 10.1 54.3 0.2 7.8 26.7

Coupon 5-Year 1.846 2.6 101.8 21.6 8.9 69.5 0.2 8.8 60.0

Coupon 7-Year 2.066 2.6 84.0 15.2 15.7 69.1 0.0 7.2 67.4

Coupon 10-Year 2.252 2.3 63.0 34.5 6.2 59.3 0.0 7.4 71.3

Coupon 30-Year 2.846 2.3 39.0 31.1 6.1 62.8 0.0 4.8 100.8

TIPS 5-Year 0.117 2.4 14.0 22.8 11.6 65.5 0.0 0.4 7.5

TIPS 10-Year 0.471 2.1 24.0 33.9 5.4 60.7 0.0 1.3 28.1

FRN 2-Year 0.058 3.3 41.0 46.7 0.9 52.5 0.0 1.5 0.0

Total Bills 1.054 3.2 1,556.8 54.8 7.2 37.9 19.3 0.0 51.7

Total Coupons 1.902 2.6 436.5 27.6 11.1 61.3 0.9 42.6 345.2

Total TIPS 0.341 2.2 37.9 29.8 7.7 62.5 0.1 1.8 35.5

Total FRN 0.058 3.3 41.0 46.7 0.9 52.5 0.0 1.5 0.0
30

1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

Sep-07Sep-08Sep-09Sep-10Sep-11Sep-12Sep-13Sep-14Sep-15Sep-16Sep-17

Bid-to-Cover Ratio

Bid-to-Cover Ratios for Treasury Bills

4-Week (13-week moving average) 13-Week (13-week moving average)

26-Week (13-week moving average) 52-Week (6-month moving average)
31

2

2.5

3

3.5

4

4.5

Mar-15

Apr-15

May-15

Jun-15

Jul-15

Aug-15

Sep-15

Oct-15

Nov-15

Dec-15

Jan-16

Feb-16

Mar-16

Apr-16

May-16

Jun-16

Jul-16

Aug-16

Sep-16

Oct-16

Nov-16

Dec-16

Jan-17

Feb-17

Mar-17

Apr-17

May-17

Jun-17

Jul-17

Aug-17

Sep-17

Bid-to-Cover Ratio

Bid-to-Cover Ratios for FRNs

(6-Month Moving Average)
32

1

1.5

2

2.5

3

3.5

4

4.5

Sep-12

Dec-12

Mar-13

Jun-13

Sep-13

Dec-13

Mar-14

Jun-14

Sep-14

Dec-14

Mar-15

Jun-15

Sep-15

Dec-15

Mar-16

Jun-16

Sep-16

Dec-16

Mar-17

Jun-17

Sep-17

Bid-to-Cover Ratio

Bid-to-Cover Ratios for 2-, 3-, and 5-Year Nominal Securities

(6-Month Moving Average)

2-Year 3-Year 5-Year
33

1

1.5

2

2.5

3

3.5

Sep-12

Dec-12

Mar-13

Jun-13

Sep-13

Dec-13

Mar-14

Jun-14

Sep-14

Dec-14

Mar-15

Jun-15

Sep-15

Dec-15

Mar-16

Jun-16

Sep-16

Dec-16

Mar-17

Jun-17

Sep-17

Bid-to-Cover Ratio

Bid-to-Cover Ratios for 7-, 10-, and 30-Year Nominal Securities

(6-Month Moving Average)

7-Year 10-Year 30-Year
34

1

1.5

2

2.5

3

3.5

Sep-06Sep-07Sep-08Sep-09Sep-10Sep-11Sep-12Sep-13Sep-14Sep-15Sep-16Sep-17

Bid-to-Cover Ratio

Bid-to-Cover Ratios for TIPS

5-Year 10-Year (6-month moving average) 20-Year 30-Year
35

Excludes SOMA add-ons. The “Other” category includes categories that are each less than 5%, which include Depository Institutions, Individuals, 

Pension and Insurance.

0%

5%

10%

15%

20%

25%

30%

35%

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

13-week moving average

Percent Awarded in Bill Auctions by Investor Class 

(13-Week Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
36

Excludes SOMA add-ons. The “Other” category includes categories that are each less than 5%, which include Depository Institutions, Individuals, 

Pension and Insurance.

0%

10%

20%

30%

40%

50%

60%

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

6-month moving average

Percent Awarded in 2-, 3-, and 5-Year Nominal Security 

Auctions by Investor Class (6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
37

Excludes SOMA add-ons. The “Other” category includes categories that are each less than 5%, which include Depository Institutions, Individuals, 

Pension and Insurance.

0%

10%

20%

30%

40%

50%

60%

70%

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

6-month moving average

Percent Awarded in 7-, 10-, 30-Year Nominal Security Auctions 

by Investor Class (6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
38

Excludes SOMA add-ons. The “Other” category includes categories that are each less than 5%, which include Depository Institutions, Individuals, 

Pension and Insurance.

0%

10%

20%

30%

40%

50%

60%

70%

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

6-month moving average

Percent Awarded in TIPS Auctions by Investor Class

(6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
39

Excludes SOMA add-ons. 

10%

20%

30%

40%

50%

60%

70%

80%

Mar-13

May-13

Jul-13

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

% of Total Competitive Amount Awarded

Primary Dealer Awards at Auction

4/13/26-Week (13-week moving average) 52-Week (6-month moving average)

2/3/5-Year (6-month moving average) 7/10/30-Year (6-month moving average)

TIPS (6-month moving average)
40 Excludes SOMA add-ons. 

0%

5%

10%

15%

20%

25%

Mar-13

May-13

Jul-13

Sep-13

Nov-13

Jan-14

Mar-14

May-14

Jul-14

Sep-14

Nov-14

Jan-15

Mar-15

May-15

Jul-15

Sep-15

Nov-15

Jan-16

Mar-16

May-16

Jul-16

Sep-16

Nov-16

Jan-17

Mar-17

May-17

Jul-17

Sep-17

% of Total Competitive Amount Awarded

Direct Bidder Awards at Auction

4/13/26-Week (13-week moving average) 52-Week (6-month moving average)

2/3/5 (6-month moving average) 7/10/30 (6-month moving average)

TIPS (6-month-moving average)
41 Foreign includes both private sector and official institutions.

0

20

40

60

80

100

120

Sep-15

Oct-15

Nov-15

Dec-15

Jan-16

Feb-16

Mar-16

Apr-16

May-16

Jun-16

Jul-16

Aug-16

Sep-16

Oct-16

Nov-16

Dec-16

Jan-17

Feb-17

Mar-17

Apr-17

May-17

Jun-17

Jul-17

Aug-17

Sep-17

$ bn

Total Foreign Awards of Treasuries at Auction, $ billions

Bills 2,3,5 7,10,30 TIPS FRN
Appendix

42
43

This scenario does not represent any particular course of action that Treasury is expected to follow. See table on following page for details.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2018201920202021202220232024202520262027

End of Fiscal Year

Projected Portfolio Composition by Issuance Type

Bills 2,3,5 7,10,30 TIPS (principal accreted to projection date) FRN
44

Recent and Projected Portfolio Composition by Issuance Type, Percent

This scenario does not represent any particular course of action that Treasury is expected to follow. 

End of Fiscal 

Year Bills 2-, 3-, 5-Year Nominal Coupons

7-, 10-, 30-Year 

Nominal 

Coupons

Total 

Nominal 

Coupons

TIPS (principal accreted 

to projection date) FRN

2010 21.1 40.1 31.8 71.9 7.0 0.0

2011 15.4 41.4 35.9 77.3 7.3 0.0

2012 15.0 38.4 39.0 77.4 7.5 0.0

2013 13.2 35.8 43.0 78.7 8.1 0.0

2014 11.5 33.0 46.0 79.0 8.5 1.0

2015 10.6 29.4 49.0 78.3 8.8 2.2

2016 12.1 27.0 49.6 76.6 8.9 2.4

2017 12.7 25.9 50.0 75.8 9.1 2.4

2018 12.2 25.9 50.3 76.2 9.3 2.3

2019 11.7 26.7 50.0 76.7 9.4 2.2

2020 11.3 27.0 50.3 77.3 9.3 2.1

2021 10.9 27.1 50.8 77.9 9.2 2.0

2022 10.6 26.9 51.6 78.5 9.0 1.9

2023 10.3 26.5 52.3 78.8 8.9 1.9

2024 10.2 25.9 53.1 79.0 8.9 1.9

2025 10.0 25.3 54.1 79.4 8.7 1.9

2026 9.9 24.7 54.9 79.7 8.6 1.8

2027 9.9 24.1 55.6 79.7 8.6 1.8
*Weighted averages of competitive awards. 45

**Approximated using prices at settlement and includes both competitive and non-competitive awards.

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % 

Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

4-Week 7/6/2017 0.950 3.02 39.6 65.0 9.1 25.9 0.4 0.0 0.3

4-Week 7/13/2017 0.950 3.15 39.6 58.4 14.2 27.3 0.4 0.0 0.3

4-Week 7/20/2017 0.955 3.06 44.5 54.3 12.2 33.5 0.5 0.0 0.4

4-Week 7/27/2017 0.980 2.95 44.6 67.7 12.0 20.3 0.4 0.0 0.4

4-Week 8/3/2017 0.990 2.90 44.6 66.1 8.4 25.5 0.4 0.0 0.4

4-Week 8/10/2017 0.985 3.06 44.6 53.1 11.0 35.9 0.4 0.0 0.4

4-Week 8/17/2017 0.940 3.02 34.4 61.8 6.2 31.9 0.5 0.0 0.3

4-Week 8/24/2017 0.940 3.06 29.6 74.5 5.3 20.2 0.4 0.0 0.3

4-Week 8/31/2017 0.960 3.43 24.6 70.3 5.9 23.8 0.4 0.0 0.2

4-Week 9/7/2017 1.300 3.04 19.6 58.5 16.9 24.6 0.4 0.0 0.2

4-Week 9/14/2017 0.970 3.49 34.5 52.4 10.3 37.3 0.5 0.0 0.3

4-Week 9/21/2017 0.960 3.18 34.5 61.3 12.9 25.8 0.5 0.0 0.3

4-Week 9/28/2017 0.970 3.18 34.5 62.8 9.2 28.0 0.5 0.0 0.3

13-Week 7/6/2017 1.045 3.21 38.5 42.7 4.2 53.1 0.5 0.0 1.1

13-Week 7/13/2017 1.040 2.87 38.5 59.6 9.0 31.4 0.5 0.0 1.1

13-Week 7/20/2017 1.050 2.94 38.5 63.4 10.4 26.2 0.5 0.0 1.1

13-Week 7/27/2017 1.180 2.87 37.4 55.9 5.6 38.4 0.6 0.0 1.1

13-Week 8/3/2017 1.070 3.18 38.4 44.9 11.9 43.2 0.5 0.0 1.1

13-Week 8/10/2017 1.040 3.62 37.6 31.3 6.1 62.6 0.5 0.0 1.1

13-Week 8/17/2017 1.015 3.52 38.3 39.2 4.8 56.0 0.6 0.0 1.1

13-Week 8/24/2017 1.000 3.11 38.4 51.5 6.4 42.0 0.5 0.0 1.1

13-Week 8/31/2017 1.020 3.03 38.3 60.7 5.7 33.6 0.5 0.0 1.1

13-Week 9/7/2017 1.020 3.18 38.5 59.0 6.1 34.9 0.5 0.0 1.1

13-Week 9/14/2017 1.035 3.03 38.2 46.0 7.6 46.3 0.5 0.0 1.1

13-Week 9/21/2017 1.045 3.05 41.1 55.6 8.9 35.6 0.6 0.0 1.2

13-Week 9/28/2017 1.050 2.89 40.4 72.2 8.1 19.7 0.6 0.0 1.2

26-Week 7/6/2017 1.130 3.21 32.2 52.6 3.1 44.3 0.5 0.0 1.9

26-Week 7/13/2017 1.125 3.20 32.2 45.3 8.3 46.4 0.5 0.0 1.9

26-Week 7/20/2017 1.105 3.54 32.0 32.4 2.5 65.1 0.6 0.0 1.9

26-Week 7/27/2017 1.130 2.91 31.5 56.6 2.7 40.7 0.5 0.0 1.9

26-Week 8/3/2017 1.130 3.08 32.3 48.6 3.4 48.0 0.4 0.0 1.9

26-Week 8/10/2017 1.140 3.05 32.0 58.2 6.7 35.1 0.5 0.0 1.9

26-Week 8/17/2017 1.115 3.47 31.8 38.6 5.3 56.1 0.5 0.0 1.9

26-Week 8/24/2017 1.115 3.02 31.8 48.3 4.1 47.6 0.4 0.0 1.8

26-Week 8/31/2017 1.115 3.41 31.6 39.3 3.1 57.7 0.4 0.0 1.9

26-Week 9/7/2017 1.115 3.08 31.9 60.2 4.7 35.1 0.4 0.0 1.9

26-Week 9/14/2017 1.140 3.12 32.2 44.3 2.9 52.7 0.4 0.0 1.9

26-Week 9/21/2017 1.180 3.21 35.0 44.8 3.8 51.3 0.5 0.0 2.0

26-Week 9/28/2017 1.170 3.34 34.8 39.5 4.1 56.4 0.4 0.0 2.0

52-Week 7/20/2017 1.190 3.17 19.7 49.0 8.0 43.0 0.3 0.0 2.3

52-Week 8/17/2017 1.230 3.25 19.7 61.5 6.0 32.4 0.2 0.0 2.2

52-Week 9/14/2017 1.240 3.16 19.8 56.2 6.9 37.0 0.2 0.0 2.2

CMB 8/1/2017 1.010 3.94 20.0 74.1 12.0 13.9 0.0 0.0 0.1

CMB 9/1/2017 1.060 3.04 40.0 69.2 6.4 24.3 0.0 0.0 1.5

CMB 9/7/2017 1.010 3.54 25.0 50.8 2.2 47.0 0.0 0.0 0.1

CMB 9/8/2017 1.010 4.28 20.0 73.8 1.5 24.7 0.0 0.0 0.0

Bills
46

*Weighted averages of competitive awards.

**Approximated using prices at settlement and includes both competitive and non-competitive awards. For TIPS’ 10-Year equivalent, a constant 

auction BEI is used as the inflation assumption.

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % 

Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

2-Year 7/31/2017 1.395 3.06 25.7 24.6 16.9 58.5 0.2 2.6 6.5

2-Year 8/31/2017 1.345 2.86 25.8 41.6 12.6 45.8 0.1 0.8 5.9

2-Year 10/2/2017 1.462 2.88 25.8 36.8 19.0 44.2 0.1 3.2 6.5

3-Year 7/17/2017 1.573 2.87 23.8 37.6 9.9 52.6 0.1 0.5 8.2

3-Year 8/15/2017 1.520 3.13 23.8 25.8 10.2 64.1 0.0 7.2 10.6

3-Year 9/15/2017 1.433 2.70 23.9 43.4 10.4 46.2 0.0 0.0 7.9

5-Year 7/31/2017 1.884 2.58 34.0 24.1 6.2 69.8 0.0 3.5 20.5

5-Year 8/31/2017 1.742 2.58 33.9 17.5 13.5 69.1 0.1 1.1 18.9

5-Year 10/2/2017 1.911 2.52 33.9 23.3 7.1 69.6 0.1 4.2 20.6

7-Year 7/31/2017 2.126 2.54 28.0 20.6 11.6 67.7 0.0 2.8 23.0

7-Year 8/31/2017 1.941 2.46 28.0 14.6 16.6 68.8 0.0 0.9 21.2

7-Year 10/2/2017 2.130 2.70 28.0 10.4 19.0 70.6 0.0 3.5 23.2

10-Year 7/17/2017 2.325 2.45 20.0 29.5 5.7 64.8 0.0 0.5 20.4

10-Year 8/15/2017 2.250 2.23 23.0 35.3 6.8 57.9 0.0 6.9 30.9

10-Year 9/15/2017 2.180 2.28 20.0 38.7 6.0 55.3 0.0 0.0 20.0

30-Year 7/17/2017 2.936 2.31 12.0 31.9 6.4 61.7 0.0 0.3 27.7

30-Year 8/15/2017 2.818 2.32 15.0 27.8 5.4 66.8 0.0 4.5 45.8

30-Year 9/15/2017 2.790 2.21 12.0 34.4 6.8 58.8 0.0 0.0 27.4

2-Year FRN 7/31/2017 0.060 3.32 15.0 38.7 2.0 59.2 0.0 1.5 0.0

2-Year FRN 8/25/2017 0.060 3.09 13.0 49.6 0.4 50.1 0.0 0.0 0.0

2-Year FRN 9/29/2017 0.055 3.46 13.0 52.9 0.0 47.1 0.0 0.0 0.0

Issue Settle Date Stop Out 

Rate (%)*

Bid-to-Cover 

Ratio*

Competitive 

Awards ($bn)

% Primary 

Dealer* % Direct* % 

Indirect*

NonCompetitive 

Awards ($bn)

SOMA 

Add Ons 

($bn)

10-Year 

Equivalent 

($bn)*

5-Year TIPS 8/31/2017 0.117 2.41 14.0 22.8 11.6 65.5 0.0 0.4 7.5

10-Year TIPS 7/31/2017 0.489 1.98 13.0 39.5 8.0 52.5 0.0 1.3 16.1

10-Year TIPS 9/29/2017 0.450 2.32 11.0 27.3 2.3 70.4 0.0 0.0 12.0

Nominal Coupons

TIPS
Office of Debt Management

Floating Rate Note Cost Comparison

October 2017
Executive Summary

2

 Treasury floating rate notes (FRNs) were introduced in January 2014.

 Quarterly issuance of $41 billion (excl. SOMA auction add-ons) has resulted in cumulative 

issuance of $615 billion, $328 billion of which is currently outstanding

 Since 2014, FRNs have been less costly to issue than 2-year fixed-rate notes, comparable in cost to 

1-year bills, but more expensive than 3-month and 6-month bills.

 Seven FRN issues have matured, representing a total notional (ex-SOMA) of $287 billion.

 Matured FRN interest costs have totaled $1.5 billion for an average annual yield of ~25 bps.

 Using FRN equivalent notional and issuance weeks:

 2-year fixed-rate notes would have cost $2.9 billion, or an average annual yield of ~50 bps

 3-month bills would have cost $0.8 billion, or an average annual yield of ~15 bps.

 A few important caveats:

 FRN auctions are $13-15 billion in size, compared to an average of $27 billion in 2-year fixedrate notes and $30 billion in 3-month bills.

 This study focuses only on FRNs that have matured, with original issue dates between January 

2014 and July 2015.
Cost Comparison

3

 To date, realized costs of the FRN program compare favorably to the 2-year fixed, resulting in 

savings of approximately $1.3 billion:

 However, because this analysis incorporates only realized costs (i.e., matured securities), it does 

not include FRNs issued between 4Q 2015 and 1Q 2017 when spreads to the index widened 

noticeably.

 Using market-implied forwards (as of Sept 29), one can estimate the unrealized costs of FRNs 

currently outstanding:

 In this instance, the aggregate realized and unrealized costs of FRNs would still result in a 

net savings of approximately $0.2 billion versus the 2-year fixed.

($400)

($300)

($200)

($100)

$0

$100

$200

$300

$400

$500

$600

Jan-2016 Apr-2016 Jul-2016 Oct-2016 Jan-2017 Apr-2017 Jul-2017

millions

Maturity Date

Relative Interest Cost: FRNs and 2Yr Notes

FRN 2Yr Fixed FRN Cost less 2Yr Fixed Cost
Investor Auction Activity

4

 FRNs are most comparable to both the 2-year fixed-rate note and the 3-month bill:

 New FRN issues are $15 billion the first month of each quarter, with two monthly $13 billion 

re-openings.

 The interest rate is reset daily based on the most recently auctioned 3-month bill plus a spread, 

known as the discount margin, that is set at the initial FRN auction.

 Interest is paid every 3 months, compared to every 6 months for the 2-year fixed-rate note.

Investor Class 

Auction Allotments (2016)

67.3%

21.8%

8.7%

2.2%

3-Month Bill

58.1%

11.3%

15.9%

14.8%

2-Year FRN

40.7%

37.4%

17.8%

4.1%

2-Year Nominal
Conclusions

5

 To finance potential SOMA redemptions, consideration should be given to the potential for 

increasing FRN issuance - possibly in 1H 2018.

 FRNs have been effective in reducing interest costs at the 2-year tenor, saving approximately $1.3 

billion in interest payments for matured issues. To date, realized interest costs for the FRN are 

comparable to the 1-year bill.

 FRNs have successfully broadened Treasury’s investor base.

 Conversations with some market participants have indicated that there is scope to increase FRN 

issuance.

 The most recent Primary Dealer Auction Size Survey indicates a maximum recommended 

auction size of $19 billion.

 Discount margins (i.e., spread to the 3-month) are near all-time lows with the September 

auction stop-out at 6 bps. Market participants have indicated that the FRN is particularly 

attractive in a rising rate environment.
Office of Debt Management

TIPS Program Review

October 2017
Executive Summary

2

 Introduced in 1997, TIPS represent over $1.2 trillion or approximately 9 percent of the marketable 

debt portfolio. TIPS are the largest inflation-linked debt program in the world.

 TIPS benefit Treasury given that investors typically demand a higher yield on nominal debt to 

compensate for risks associated with future inflation expectations.

 Thus, issuing inflation-indexed debt eliminates that risk and Treasury avoids having to pay an inflation risk 

premium at auction.

 Benefit financial markets by providing a new debt security and deepening the Treasury investor base.

 Occasional changes to the TIPS program.

 Originally sold 5- and 10-year tenors; 30-year maturity added in 1998, but discontinued in 2001.

 20-year maturity introduced in 2004, but discontinued in 2009 in favor of reintroduced 30-year maturity.

 Monthly issuance began in 2011.

 Since inception, TIPS have been less costly compared to equivalent nominal coupons.

 Approximately $49 billion in lower costs compared to nominal issuance.

 Although TIPS auctions typically attract stronger levels of participation from investment funds 

than their nominal coupon counterparts, TIPS appear to have had limited success in significantly 

diversifying Treasury’s investor base.

 Despite a prolonged period of low expectations for future inflation, investors continue to support 

the program, but have suggested potential changes over the years.
Cost Comparison

3

 TIPS have saved approximately $49 billion compared to issuing an equivalent nominal security. The auction 

implied break-even inflation rate generally has been higher than the realized.

 During periods when the inflation rate decreases (2008 to 2009 and 2014 to 2016), there is an inflation savings on 

the outstanding portfolio.

 Given that Treasury does not time the market and continues to issue during times of low inflation, those issuances 

would incur inflation costs when the inflation rate increases (such as 2010 to 2013). 

 This does not ensure savings in the future, but does illustrate the value of diversifying the inflation risk to Treasury 

by issuing both fixed and floating inflation coupons.

(150)

(100)

(50)

0

50

100

150

200

1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

$ bn

Historical Costs/Savings

Decreasing 

inflation

Increasing inflation

Decreasing inflation

Inflation Cost ($68)

Interest Cost $19

Total Ex Post Cost ($49)

As of August 2017

Chung, D., C. Kim, and A. Zhang. “An Ex Post Performance Analysis of the TIPS Program.” The Journal of Fixed Income (Spring 2013), pp. 31-47.

Dudley, W., J. Roush, and M. Ezer. “The Case for TIPS: An Examination of the Costs and Benefits.” FRBNY Economic Policy Review (July 2009), pp. 1-17.
Investor Auction Activity

4

 In recent years, TIPS 

auctions have experienced 

increasing levels of 

participation from 

investment funds, more so 

than in nominal coupon 

auctions, primarily at the 

expense of comparatively 

lower primary dealer 

award allocations. 

 Investor class auction 

allotments since 2012: 

39.5%

40.2%

15.9%

4.4%

5-, 10-, & 30-Year Nominals

33.7%

49.2%

14.0%

3.1%

5-, 10-, & 30-Year TIPS

0%

10%

20%

30%

40%

50%

60%

70%

Percent Awarded in TIPS Auctions by Investor Class

(6-Month Moving Average)

Other Dealers and Brokers Investment Funds Foreign and International Other
Foreign Holdings

5

 TIPS have increased from 4.4% of total Treasury investments held overseas in 2011, to 9.1% in 2016.

 Although TIPS currently represent a similar proportion of Treasury portfolios held both domestically and 

internationally, foreign holdings have been increasing at a much faster pace --- particularly within foreign 

official accounts:

 In addition, when evaluating Treasury holdings by region, it is worthy to note that the proportion represented 

by TIPS has been consistently higher in both the Caribbean and in Canada --- that having been said, aggregate 

TIPS holdings in those two regions totaled only $70 billion as of June 30, 2016:

Year Global Foreign Foreign Official Foreign Private

2016 8.8% 9.1% 8.9% 9.4%

2015 8.7% 8.3% 8.3% 8.1%

2014 8.4% 7.2% 7.3% 6.9%

2013 8.0% 6.1% 5.9% 6.7%

2012 7.6% 5.4% 5.1% 6.3%

2011 7.1% 4.4% 3.9% 5.9%

TIPS - as % of Treasury Holdings

Source: Treasury International Capital (Annual Reports)

Year Global Africa Asia Caribbean Europe Latin America Canada

2016 8.8% 1.1% 9.2% 15.8% 8.3% 5.3% 11.0%

2015 8.7% 0.4% 8.9% 16.9% 6.0% 4.5% 12.4%

2014 8.4% 3.4% 7.9% 12.5% 5.4% 4.2% 10.9%

2013 8.0% 4.4% 6.5% 8.8% 5.1% 4.4% 10.1%

2012 7.6% 1.0% 5.4% 9.9% 4.8% 4.3% 10.5%

2011 7.1% 0.1% 4.0% 7.1% 4.2% 4.8% 9.3%

TIPS - as % of Treasury Holdings

Source: Treasury International Capital (Annual Reports)
Auction Sizing and Timing

6

 TIPS issuance tripled from 2003 to 2005 and 2009 to 2012, but was decreased in 2016 along with 

nominal coupons given the improved deficit and intent to increase bills outstanding.

 Issuance sizes are near minimums in the dealer survey, potentially indicating the ability to 

increase auction sizes.

 At current issuance sizes, net issuance is about $60 billion this year, crossing over to net pay 

downs of $5 billion starting in 2021 and increasing in net pay downs to $60 billion in 2025. During 

this period, TIPS as a percent of total portfolio hovers around 9%.

 Comparing the same tenors between TIPS and nominal coupons, there is about 2 months of 

weighted average maturity (WAM) extension provided by the principal accretion for the TIPS 

securities. The contribution to the total portfolio is only 0.2 months.

Min Max

Min 

Annual

Max 

Annual

5-Year Apr/Aug/Dec 1 16/14/14 44 12 20 36 60

10-Year

Jan/Mar/May - 

Jul/Sep/Nov 2 13/11/11 70 10 17 60 102

30-Year Feb/Jun/Oct 1 7/5/5 17 6 11 18 33

Current 

Annual 

Issuance ($ bn)

Current Auction Size 

(New/Reopen)

($ bn)

Annual 

New 

Issuanance

Auction 

Calendar 

(New/Reopen)

Tenor

Primary Dealer Auction Size Survey ($ bn)
1

Treasury would like the Committee to comment on sizing considerations related to the 

issuance of Treasury bills over the short-, medium-, and long-term. What factors should 

Treasury consider when optimizing the size of bills outstanding over the coming years? 

Specifically, comment on expected drivers of demand, the investor base, auction sizing, 

and market pricing relative to other short-term money market instruments.

TBAC Charge

Sizing Treasury Bill Issuance
2

 In order to evaluate the appropriate amount of Treasury bill issuance, we examine two important considerations:

1) Investor demand for bills.

2) The impact of alternative bill issuance scenarios on the overall outstanding stock of marketable Treasury 

securities – specifically, focusing on the bill share and the weighted average maturity (WAM) of Treasury debt.

 We do not address the impact of financial stability considerations on Treasury debt management. As noted in a 

TBAC presentation last year, there is some academic evidence suggesting that an increased supply of short term, 

liquid assets by the public sector reduces the attractiveness of private short term liabilities and thus potentially 

helps to enhance the stability of the financial system. This is an important issue but it would require a reevaluation 

of the Treasury’s long held “lowest cost over time” policy and thus is beyond the scope of our charge. Moreover, 

the academic work cited suggests that the Fed might be better suited to address these stability considerations 

than Treasury.*

*See “The Demand for Short-Term, Safe Assets and Financial Stability” by Carlson, Duygan-Bump, Natalucci, Nelson, Ochoa, Stein, and den Heuvela and “The Federal Reserve’s Balance Sheet as a 

Financial-Stability Tool” by Greenwood, Hanson and Stein.

Objectives

Sizing Treasury Bill Issuance
3

I. Treasury Bill Demand

A. Current Investor Demand

B. Factors That Could Influence Future Demand

II. Treasury Bill Market Dynamics

III.Treasury Bill Supply

Agenda
4

I. Treasury Bill Demand

 A. Current Investor Demand
5

Foreign Official

330bn

19%

Foreign Private

346bn

20%

MMFs

321bn

19% Other mutual 

funds

43bn

2%

P&C Insurance

34bn

2%

Life Insurance

14bn

1%

Fed

0bn

0%

Others*

627bn

37%

Historical Bill Holdings by Investor Type Treasury Bill Holdings – Q2 2017

*Other holders include all investor types not included in the granular flow of fund breakdown, notably: banks, broker/dealers, hedge funds, clearinghouses, and retail investors.

Source: Fed Flow of Funds (via Haver). As of 25-Oct-17.

Foreign investors and U.S. Money Market Funds hold the majority of bills

Major Treasury Bill Holders by Investor Type

Total

1,715bn

0bn

100bn

200bn

300bn

400bn

500bn

600bn

700bn

800bn

900bn

1,000bn

0bn

100bn

200bn

300bn

400bn

500bn

600bn

700bn

800bn

900bn

1,000bn

200120022003200420052006200720082009201020112012201320142015201620172018

Foreign MMFs Other mutual funds

P&C Insurance Life Insurance Fed
6

Foreign Bill Holdings as a % of Total Outstanding Foreign USD Financial Assets

Source: Fed Flow of Funds (via Haver). As of 25-Oct-17.

Despite being bills’ largest investor, bills are only a tiny portion of foreign USD investments

Foreign Bill Holdings

0tn

5tn

10tn

15tn

20tn

25tn

1990 1995 2000 2005 2010 2015

Bills USTs Agencies Munis Repos

CDs CP Corporates Eq./Mut.Funds Other

0%

10%

20%

30%

40%

50%

60%

1975 1980 1985 1990 1995 2000 2005 2010 2015
7

2a7 Money Fund Relative Holdings 2a7 Money Fund Holdings by Product Type

2a7 Govt Money Fund AUM vs. Bills Outstanding 2a7 Funds vs. “MMF-Like” Mutual Funds/SMAs*

*Mutual fund classifications via Morningstar: Short = 1-3yr; Ultrashort = <1yr. SMAs report to Morningstar on a voluntary basis and thus underestimate the total AUM of SMAs with a MMF-like mandate.

Source: Morgan Stanley Research, Fed Flow of Funds (via Haver), Crane, ICI, Bloomberg, MSPD (via Haver), Morningstar. As of 24-Oct-17.

Recent allocations away from credit products have not resulted in increased bill buying

Money Market Fund Bill Holdings

2a7 Funds

2.7tn, 69%

Total

3.9tn

2,135bn, 55%

61bn, 2%

24bn, 1%

295bn, 8%

379bn, 10%

135bn, 3%

137bn, 3%

158bn, 4%

566bn, 14% 2a7 - Gov't Only

Short Govt Fund

Short Govt SMA

Short Bond SMA

Short Bond Fund

Ultrashort Bond SMA

Ultrashort Bond Fund

MMF SMA

2a7 - Prime

0.0tn

0.5tn

1.0tn

1.5tn

2.0tn

2.5tn

3.0tn Bills

RRP

Treasury Repo

UST

Agency DN

Agency Repo

Agency Coupons

CP/CDs

Other Repo

Other

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1990 1995 2000 2005 2010 2015

Bills

USTs

Agencies

Munis

Repo

CDs

CP

Corps/Foreign

Other

0.0tn

0.5tn

1.0tn

1.5tn

2.0tn

2.5tn

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

Govt MMF AUM Total Bills Total Bills (ex-Fed)
8

I. Treasury Bill Demand

 B. Factors That Could Influence Future Demand
9

Source: GS Securities Division, NY Fed. As of 24-Oct-17.

 The RRP facility is an important monetary policy tool for the Federal Reserve to manage their federal funds rate target range, 

theoretically “flooring” front-end rates by borrowing cash overnight against treasury collateral in the SOMA portfolio.

 In reality, bills persistently trade through RRP for a variety of reasons:

— RRP has a cap of 30bn per participant per day, and only certain U.S. banks, GSEs, and money-market funds have access.

— Treasury bills can be posted as collateral, and they can be sold at any time, resulting in greater re-investment flexibility.

 RRP usage spikes around month-ends when there is scarcity in dealers offering repo; bills usually richen in these episodes.

 Any changes to the RRP facility (expansion, dissolution, etc.) would directly impact bill demand.

RRP Rate vs. 1m T-Bills Reverse Repo Utilization by Counterparty Type

RRP provides a shock-absorber for excess cash over month/quarter-ends

Reverse Repo Facility (RRP)

0bn

50bn

100bn

150bn

200bn

250bn

300bn

350bn

400bn

450bn

500bn

0bn

50bn

100bn

150bn

200bn

250bn

300bn

350bn

400bn

450bn

500bn

Banks GSEs MMFs Primary Dealers

1m T-Bill Yield RRP

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

Jan Jul Jan Jul Jan Jul Jan Jul

2013 2014 2015 2016 2017

Debt Ceiling
10

Post-Crisis Bank Holdings ($bn)

HQLA Alternatives Spread to 3m T-Bills Dealer Repo Books Have Shrunk by ~$1tn Since 2012

Source: Fed H.8, GS Securities Division, SIFMA. As of 25-Oct-17.

 To comply with post-crisis bank liquidity requirements (LCR), U.S. 

banks have increased their holdings of high-quality liquid assets 

(HQLA), primarily by increasing reserves at central banks and 

holding additional agency MBS and UST securities.

 Banks are unlikely to hold bills as HQLA given they trade rich to 

low-duration alternatives, such as IOER, and banks have a 

natural demand for duration for ALM & NIM purposes.

 Balance sheet capital requirements (SLR, GAAP leverage) have 

caused dealers to shrink their repo balance sheets, increasing 

demand for alternatives such as bills and RRP.

 Changes to leverage requirements could result in a drop in bill 

demand as availability of dealer repo increases.

Demand for HQLA has been met with excess reserves, agency MBS & USTs – not bills

Commercial Banks in the U.S.

Cash/CB reserves Agy MBS Other Securities Tsy/Agy NonAgy MBS	 FF & repo

0

500

1000

1500

2000

2500

3000

3500

2010 2011 2012 2013 2014 2015 2016 2017 2018

IOER (3m Avg) CT5 on ASW (3m carry) 3m Tsy GC Repo 0 / 3m T-Bill Yield

-40

-20

0

20

40

60

80

100

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 3.5tn

3.7tn

3.9tn

4.1tn

4.3tn

4.5tn

4.7tn

4.9tn

5.1tn

2009 2010 2011 2012 2013 2014 2015 2016 2017

Dealer Repo 

Books
11

*See the BIS Summary of Changes for more information: http://www.bis.org/bcbs/publ/d317.pdf.

Source: ISDA Margin Survey 2017 (Link: http://assets.isda.org/media/85260f13-45/71e04f49-pdf/).

 In order to adhere to global margin rules, counterparties will be required to begin posting initial margin on their bilateral derivative 

positions, with a phase-in period from September 2016 through 2020.*

— Currently, only large derivatives dealers are in-scope for mandatory IM posting on inter-dealer bilateral trades, and it is expected 

that most non-dealer counterparties will not come into scope until 2020.

 ISDA’s recent margin survey estimates dealers currently have ~47bn in aggregate, delivered regulatory IM; this figure is expected to 

grow significantly when all counterparties come into scope.

 It is unlikely that incremental collateral needs for IM purposes will result in a greater demand for bills.

— Some counterparties already hold excess, unencumbered high-quality collateral that can be pledged as IM.

— Eligible collateral is negotiated on a bilateral basis, so incremental collateral demands could be met with less-liquid collateral 

such as corporate bonds or mortgage-backed securities.

— IM reducing strategies such as clearing or reducing bilateral risk exposures are expected to continue to rise in prominence.

ISDA Margin Survey (Sep’17) – Estimated Total Margin ISDA Margin Survey (Sep’17) – Margin by Collateral Type

Global margin rules mandate counterparties to post IM for all bilateral derivatives

Bilateral Derivative Initial Margin
12

II. Treasury Bill Market Dynamics
13

Bills as a % of Marketable Debt Bills as a % of GDP

Marketable Debt Outstanding by Instrument Type

Source: MSPD, Bureau of Economic Analysis. Retrieved via Haver Analytics as of 23-Oct-17.

Bill share of marketable debt is near historical lows, but bill share of GDP is elevated

Treasury Bills Outstanding

0tn

2tn

4tn

6tn

8tn

10tn

12tn

14tn

16tn

0tn

2tn

4tn

6tn

8tn

10tn

12tn

14tn

16tn

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Bills Notes Bonds TIPS FRNs

0%

2%

4%

6%

8%

10%

12%

14%

16%

0%

2%

4%

6%

8%

10%

12%

14%

16%

1952 1962 1972 1982 1992 2002 2012 2022

Bill % Bill + FRN % Bill % Long-Run Avg (7.7%)

0%

10%

20%

30%

40%

50%

0%

10%

20%

30%

40%

50%

1952 1962 1972 1982 1992 2002 2012 2022

Bill % Bill + FRN % Bill % Long-Run Avg (24.2%)
14

Outstanding Fixed Income Debt Securities Relative Fixed Income Supply

Source: Fed Flow of Funds. Retrieved via Haver Analytics as of 24-Oct-17.

Bills have been roughly unchanged, while other asset classes have substantially grown

Bill Supply in Context: Total Fixed Income Supply

0tn

5tn

10tn

15tn

20tn

25tn

30tn

35tn

40tn

0tn

5tn

10tn

15tn

20tn

25tn

30tn

35tn

40tn

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Treasury Bills Treasury Coupons

Agencies Agency MBS

Short-Term Munis Long-Term Munis

Non-Financial Domestic CP Non-Financial Foreign CP

Financial Domestic CP Financial Foreign CP

Non-Financial Corporates Financial Corporates

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015
15

Size of Front-End Money Market Front-End Rates as a Spread to 3m T-Bills

*Rough proxy for Agency DNs/short-dated Agency coupons.

Source: GS Securities Division, Bloomberg, Fed Flow of Funds. Retrieved via Haver Analytics as of 24-Oct-17.

Treasury bill “substitutes” outstanding have outpaced growth of bills outstanding

Bill Supply in Context: Front-End Money Markets

0tn

5tn

10tn

15tn

20tn

25tn

0tn

5tn

10tn

15tn

20tn

25tn

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

Bills

Agencies Held by MMFs*

Short-Term Munis

CP

Federal Funds & Repo

Time & Savings Deposits

Checkable Deposits & Currency

Foreign Deposits

0 / 3m T-Bill 3m Agy DN 3m AA non-fin. CP 3m AA fin. CP 3m Tsy GC Repo Fed Funds

IOER

-50

-25

0

25

50

75

100

125

150

175

200

225

250

275

300

325

350

375

400

2002 2004 2006 2008 2010 2012 2014 2016 2018
16

1m T-Bill vs. 1m GC Repo (Avg = -15) 3m T-Bill vs. 3m GC Repo (Avg = -14)

-60

-55

-50

-45

-40

-35

-30

-25

-20

-15

-10

- 5

0

5

10

15

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

1985-Present: Trailing 1m Average Post-Crisis: 2009 to Present

Source: GS Securities Division. As of 23-Oct-17.

Bills trade rich to GC repo (SOFR proxy), especially in a flight-to-quality

Treasury Bills Relative Value

1m T-Bill vs. 1m GC Repo (bps) 3m T-Bill vs. 3m GC Repo (bps)

-375

-350

-325

-300

-275

-250

-225

-200

-175

-150

-125

-100

-75

-50

-25

0

1985 1990 1995 2000 2005 2010 2015

Black Monday

Russia Default

Great Recession

Debt Ceiling

Richer

Cheaper

Dot-com bust

Advanced approach banks 

begin disclosing SLR

Volatile funding 

markets amid balance 

sheet pressures can 

squeeze bills over 

month-ends

2a7

Reform
17

5y Note - 3m Bill vs. OIS curve (bps) Bills % Mktable Debt (rhs) Regr*

-40

-30

-20

-10

0

10

20

30

40

50

60

70

8

10

12

14

16

18

20

22

24

26

28

30

32

34

2009 2010 2011 2012 2013 2014 2015 2016 2017 2018

*Linear Regression: [5y vs. OIS – 3m vs. OIS] = 21.33bps – 0.26bps/% × [Bills %] R2 = 56%

Source: GS Securities Division, MSPD (via Haver). As of 23-Oct-17.

 When bill supply increases relative to coupons, bills cheapen and coupons richen relative to one another as expected.

 Regressing the relative richness of 5y note – 3m bill curve vs. the OIS curve against the marketable debt bill allocation from 2009 to 

present suggests bills cheapen ~1⁄4 bp vs. 5s for every 1% increase in bill allocation.*

 All else equal, this means normalizing from 13% back to 23% bill allocation would suggest bills would cheapen ~2.5bps vs. 5s.

3m Bill Relative Richness vs. 5y Note – 3m Libor 3m Bill Relative Richness vs. 5y Note – OIS

Bills trade rich on the curve post 2a7 reform, even adjusting for lower relative supply

Treasury Bills Relative Value

Bills

Cheaper

Bills

Richer

2a7

Reform

5y - 3m Bill vs. 3m$L Curve (bps) Bills % Mktable Debt (rhs)

-50

0

50

100

150

200

250

300

350

400

450

500

550

8

10

12

14

16

18

20

22

24

26

28

30

32

34

36

1988 1993 1998 2003 2008 2013 2018
18

Note: The GHS estimate of the Tbill premium is based on the difference between actual T-bill yields and a curve that is fitted using all outstanding nominal Treasury coupon securities with a maturity 

greater than 3 months.. The curve is fitted using the model developed by Gurkaynak, Sack and Wright (2007). 

Source: Greenwood, Robin, Samuel G. Hansen, and Jeremy C. Stein, 2015, “A Comparative Advantage Approach to Government Debt Maturity,” Journal of Finance.

GHS Estimate of T-Bill Premium (1983-2009)

Even pre-MMF reform, academic research suggested that Treasury should consider issuing more bills. A couple of reasons have been 

offered: (1) financial stability considerations; and, (2) the existence of a T-bill premium. This premium seems to be especially large at 

the very short-end of the bill curve.

Research presented at the Nov’16 TBAC meeting supports the existence of bill premia

Revisiting the T-Bill Premium
19

III. Treasury Bill Supply
20

1. Baseline and Pessimistic Budget Deficit estimates based on August Treasury Dealer Survey (for 2018-19) and latest CBO Baseline 

(June 2017 Update). See next slide for more details.

2. SOMA runoff in line with latest NY Fed estimates*:

 FY Amount

 2018 $175 bil

 2019 $284 bil

 2020 $221 bil

 2021 $168 bil

SOMA assumed to be normalized at the end of FY 2021, so no further runoff of Treasuries beyond that point.

3. Treasury Cash Balance Target = $300 bil for FY 2018-27.

4. Nonmarketable + Other Means of Finance = $60 bil for FY 2018-27.

5. Financing Gap is the amount of issuance that will be needed if coupon sizes are held steady at current level and net bill issuance is 

set to zero (i.e., Financing Gap = Budget Deficit – Net Marketable Coupon Issuance + Change in Cash Balance - (Net 

Nonmarketable Issuance + Other Means of Finance)).

* See “Projections for the SOMA Portfolio and Net Income”, Federal Reserve Bank of New York, July 2017 (median scenario with September 2017 announcement/October 2017 implementation).

Assumptions for Alternative Financing Scenarios

Sizing Treasury Bill Supply
21

Budget Deficit Assumptions

 Baseline scenario is derived from the Primary Dealer mean from the August 2017 survey in FY 2018-19 and the latest (June 2017) 

CBO Baseline thereafter.

 Alternative scenario is derived from the high estimate in the August 2017 Primary Dealer survey for FY 2018-19, a linear 

interpolation in 2020-2021 and the latest (June 2017) CBO baseline thereafter.

Budget Deficit Assumptions

Sizing Treasury Bill Supply

Fiscal Year Baseline % of GDP Alternative % of GDP 

2017 (actual) 666bn 3.5 666bn 3.5

2018 690bn 3.5 875bn 4.4

2019 789bn 3.8 980bn 4.7

2020 775bn 3.6 995bn 4.7

2021 879bn 4.0 1,011bn 4.6

2022 1,027bn 4.5 1,027bn 4.5

2023 1,057bn 4.4 1,057bn 4.4

2024 1,083bn 4.3 1,083bn 4.3

2025 1,225bn 4.7 1,225bn 4.7

2026 1,352bn 5.0 1,352bn 5.0

2027 1,463bn 5.2 1,463bn 5.2
22

Financing Gap is the amount of issuance that will be needed if coupon sizes are held steady at current level and net bill issuance is set to zero (i.e., Financing Gap = Budget Deficit – Net Marketable 

Coupon Issuance + Change in Cash Balance - (Net Nonmarketable Issuance + Other Means of Finance)).

FY18 Financing Gap excludes 131bn of bill issuance needed to restore the treasury general account (TGA) cash balance.

Financing Gap Estimates

Sizing Treasury Bill Supply

0bn

200bn

400bn

600bn

800bn

1,000bn

1,200bn

1,400bn

1,600bn

2018 2019 2020 2021 2022 2023 2024 2025 2026 2027

Baseline Alternative Fiscal Year
23

Bills as a % of Marketable Debt* WAM of Debt*

*Calculations performed under the “Baseline” deficit scenario. Financing within the bill and coupon allocations is done pro-rata across the curve.

Issuing 1/3 Bills, 2/3 Coupons minimizes WAM impact while normalizing bill supply

Sizing Treasury Bill Supply

0%

10%

20%

30%

40%

50%

0%

10%

20%

30%

40%

50%

2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027

All Bills 1/2 Bills 1/3 Bills 1/4 Bills All Coups

4.5

5.0

5.5

6.0

6.5

7.0

4.5

5.0

5.5

6.0

6.5

7.0

2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027

All Bills 1/2 Bills 1/3 Bills 1/4 Bills All Coups

Fiscal Year Fiscal Year
24

Average Auction Size: 2010-Present* Estimated Auction Sizes: 2020**

*Average is shown per auction, including re-openings. 4w/13w/26w bills are auctioned weekly; 52w bills are 4-weekly; CMBs are ad-hoc; and all others are monthly.

**The top of the PD range shows dealer estimated “maximum auction size that could be issued without causing significant yield deviations from fair value” in 2017. In the baseline/alternative scenarios, 

the financing gap is assumed to be filled 1/3 in bills and 2/3 in coupons+TIPS, pro-rata across the curve according to 2017YTD average auction size. FRNs are kept unchanged and CMB are excluded.

Source: Treasury Direct, Primary Dealer Survey Q2’17. As of 23-Oct-17.

Impact on auction sizes

Sizing Treasury Bill Supply

32 36 38 39 33 34 48 43

28 29 31 32

26 25

35 38

28 27 28 27

25 24

30 32 25 24 25 24

24 21

24 20 20 18

23 30

31 29

14 27 14 14

15

41 37

35 34 30

26 30

29

37

33

34 31 28

24 25

26

39

37

35 35 35

35 39

38

31

30

29 29 29

29

32

31

23

22

23 22 22

22

22

23 15

14

15 14 14

14

14

10 14

11

12 13 13

13

12

12

0bn

50bn

100bn

150bn

200bn

250bn

300bn

350bn

0bn

50bn

100bn

150bn

200bn

250bn

300bn

350bn

2010 2011 2012 2013 2014 2015 2016 2017TD

Calendar

Year

4w Bill 13w Bill 26w Bill 52w Bill CMB

2y FRN 2y Note 3y Note 5y Note 7y Note

10y Note 30y Bond TIPS

0bn

5bn

10bn

15bn

20bn

25bn

30bn

35bn

40bn

45bn

50bn

55bn

60bn

65bn

0bn

5bn

10bn

15bn

20bn

25bn

30bn

35bn

40bn

45bn

50bn

55bn

60bn

65bn

4w

Bill

13w

Bill

26w

Bill

52w

Bill

2y

FRN

2y

Note

3y

Note

5y

Note

7y

Note

10y

Note

30y

Bond

TIPS

PD Survey Range Baseline (1/3 Bills) Alternative (1/3 Bills) 2017 Avg
25

1. The bill share of marketable Treasury debt outstanding is quite low at present relative to the historical 

norm. Similarly, the volume of bills outstanding is small relative to Money Market Mutual Fund (MMMF) 

assets.

2. However, the volume of Treasury bills outstanding as a percentage of GDP is above the long run 

average.

3. Many Treasury bill alternatives are available, although none are perfect substitute. For example, CP and 

DNs have credit risk, repo is balance sheet intensive for dealers, Fed RRP is capped and only available 

to a subset of market participants. Moreover, the FOMC may eliminate the RRP – or place further 

restrictions on it – at some point.

4. Treasury bills trade rich relative to coupons at present. There appears to be a significant correlation 

between the degree of richness and the amount of available supply.

5. Under various budget deficit scenarios, the financing gap confronting the Treasury appears likely to be 

quite sizeable in coming years. This implies a need to begin to increase auction amounts. 

6. While the bill sector can absorb a significant volume of new supply over the near term, allocating more 

than 1/3 of the financing gap expected in coming years to bills would lead to a shortening of WAM, 

necessitate bill auction sizes that approach the primary dealer maximum estimates, and result in nearly a 

doubling of the bill share of marketable Treasuries over the coming decade. 

Conclusions
D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

October 31, 2017

S T R I C T L Y P R I V A T E A N D C O N F I D E N T I A L
October 31, 2017

Charge question

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

The primary objective of Treasury’s debt management strategy is to finance the government’s borrowing needs at the lowest riskadjusted cost over time. To accomplish this, Treasury strives to issue debt in a regular and predictable pattern, but that approach 

leaves open a wide range of potential outcomes for the maturity structure of the debt. The interest expense associated with any 

issuance strategy will depend on a variety of factors that are not under the control of the debt manager, including the behavior of 

interest rates, the business cycle, and the federal government’s fiscal policy. 

Pursuant to the TBAC charge and discussion at the January 2017 meeting, please provide an update on efforts the Committee is 

making with regard to the development of issuance models. Please comment on any revisions to or extensions of the modeling 

work that was presented in January. Provide an analysis of results from these models and how aspects of these models can 

complement or be incorporated with ODM’s existing issuance model framework. Comment on the degree to which the updated 

modeling efforts can help to inform potential increases to nominal coupon auction issuance. 

1
600

800

1,000

1,200

1,400

1,600

1,800

20172018201920202021202220232024202520262027

CBO Low Median High

Treasury funding requirements over the next several years

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 Treasury financing needs projected to grow significantly over the next several years reflecting both rising fiscal deficits and Fed 

redemptions

 As highlighted in both the May 2017 and August 2017 TBAC presentations, the financing need is likely too large to address solely through 

increased bill issuance; that is particularly the case if fiscal stimulus is large and the financing need approaches the high end of 

expectations shown in the charts below

 Ongoing work around debt optimization is designed to provide insights to help Treasury choose an optimal maturity structure of issuance to 

meet the increased funding need

1. Net borrowing needs includes projected fiscal deficit + student loans and other funding needs + cash balance changes + SOMA runoff; Dealer survey projections after 2020 are extrapolated using 2019 

dealer estimates vs. 2019 CBO baseline

Fiscal deficit ($B) Projected net Borrowing needs including SOMA runoff1($B)

 Primary Dealer Survey

Year CBO Baseline Low Median High

2017 693 559 664 720

2018 563 550 690 875

2019 689 650 789 980

2020 775 736 875 1,066

2021 879 840 979 1,170

2022 1,027 988 1,127 1,318

2023 1,057 1,018 1,157 1,348

2024 1,083 1,044 1,183 1,374

2025 1,225 1,186 1,325 1,516

2026 1,352 1,313 1,452 1,643

2027 1,463 1,424 1,563 1,754

2
Use of debt optimization models for assessing risk / cost tradeoffs

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

The January 2017 TBAC presentation summarized the key components of a debt optimization model being developed 

within TBAC; since then, the model has developed further and includes the following key components:

 A stylized macroeconomic model that can be used to generate stochastic simulations of the unemployment rate, 

inflation, short term interest rates, and the primary deficit

 A model that relates term premium to the macroeconomic variables and other factors

 Debt stock dynamics that track outstanding debt in terms of maturities and costs

 An optimization module that identifies low cost strategies given alternative risk and issuance constraints

 Recent work includes the following improvements to the January 2017 model

 Consideration of a broader set of issuance strategies through the introduction of issuance kernels

 Further analysis on risk/return tradeoffs faced from alternative issuance strategies including consideration of 

alternative risk measures

 Use of the model to assess the appropriateness of extending WAM at various points in time

 Development of an optimal issuance response function that allows for issuance to vary with the macroeconomic 

environment

 Assessment of how the optimal issuance mix should change with various constraints including volatility 

constraints, and financial stability-related constraints on the supply of Treasury bills

3
Expected cost / variation trade-off

Model results with single-point issuance strategies

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The model can be used to assess the trade-off between expected funding cost and the variation in funding cost

 The analysis here focuses on strategies that concentrate all issuance into a single maturity point, ignoring issuance capacity 

or any feedback to market prices

 The purpose of this exercise is to illustrate how the model works; more realistic issuance strategies are considered next

 As previously shown, the model finds a reduction in the variability of funding cost by moving from bills into the belly of the 

curve, without a substantial increase in expected funding cost. In contrast, extending to long maturities raises funding cost 

without an additional reduction in the variation in funding costs

4

2.0

2.5

3.0

3.5

0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9

Debt service / GDP

Stdev debt service / GDP

2s 3s

5s

7s

10s

20s

30s

Bills
-1.0

-0.5

0.0

0.5

1.0

Bills 2s 3s 5s 7s 10s 30s

Kernel 4 contribution to 

issuance profile (moving into

Long End)

-1.0

-0.5

0.0

0.5

1.0

1.5

Bills 2s 3s 5s 7s 10s 30s

Kernel 3 contribution to 

issuance profile 

(mov ing into the Belly )

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Bills 2s 3s 5s 7s 10s 30s

Kernel 2 contribution to 

issuance profile 

(mov ing into Bills)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Bills 2s 3s 5s 7s 10s 30s

Baseline kernel contribution to 

issuance profile (K1)

0

200

400

600

800

Bills 2s 3s 5s 7s 10s 30s

Issuance profile

Using kernels to incorporate more realistic issuance patterns

An illustration of a particular issuance profile and its decomposition into stylized issuance kernels ($B)

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 In order to explore a broader set of issuance strategies, it is useful to simplify the full set of tenors into a smaller set of stylized 

strategies that we refer to as issuance kernels; this is both for computational reasons as well as for gaining intuition on which 

issuance strategies are most appropriate

 To see this, we characterize any given issuance profile as being the sum of different decisions – a “baseline” issuance pattern, 

which can be scaled up or down depending on total gross issuance, plus other zero sum reallocations across different curve 

strategies

 In the example outlined below, the actual dollar issuance profile (top left chart ) may be written as the weighted sum of the top right 

profile (the baseline profile scaled up to match total issuance), a weighted amount of Kernel 2 (which produces a shift out of the front

end and into the back end), and a weighted amount of Kernel 3 (which shifts gross issuance out of the wings and into the belly)1

5

1. In particular, Issuance profile shown in upper left chart can be calculated as 3,000 K1 + (-674.2) K2 + 307.4 K3 + (-24.4) K4

W1 ✖

W2 ✖ W3 ✖ W4 ✖
Model results with more realistic issuance strategies (1 of 2)

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The baseline outcome represents maintaining the current issuance pattern (it keeps bill share of debt unchanged and keeps 

current proportions of issuance across coupons)

 Shifting issuance into bills (the “more bills” scenario achieved through kernel 2) increases the variation of the debt while 

reducing expected cost relative to the baseline

 Shifting issuance towards the belly (the “more belly” scenario achieved through kernel 3) reduces debt cost variation relative 

to the “more bills” outcome without increasing the expected cost 

 Shifting issuance to the long end (the “more long-end” scenario achieved through kernel 4) raises the expected cost 

meaningfully while reducing risk only slightly relative to the baseline

6

Expected cost / variation trade-off

2.3

2.8

3.3

0.60 0.70 0.80 0.90 1.00 1.10 1.20

Debt service / GDP

Stdev debt service / GDP

More

long-end

More 

bills

More 

belly

Baseline
Expected cost / variation trade-off

Model results with more realistic issuance strategies (2 of 2)

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The loadings on these alternative strategies can be varied to trace out a more complete set of possible outcomes

 Below we again consider moving into bills, the belly, and the long end, but we now vary the degree to which the issuance 

loads up on these additional kernels and also consider strategies that combine these shifts

 This exercise creates a number of possible outcomes, and the outer limit of those outcomes presents a frontier for the 

potential trade-off that debt managers can achieve

7

2.3

2.8

3.3

0.60 0.80 1.00 1.20 1.40 1.60 1.80

Debt service / GDP

Stdev debt service / GDP

Baseline More bills1 More belly1 More bonds1 Combination of kernels

1. Varying intensity to demonstrate different possible outcomes
Optimal strategy with assumed Treasury preferences

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 Treasury would presumably prefer to reach outcomes that are as far down and left as possible on the trade-off chart

 The lines on the chart capture this preference, with lower lines representing better outcomes

 Risk-neutral cost minimization would be represented by horizontal lines, while a desire to also reduce risk would provide 

some slope to the lines

 Achieving the lowest line represents the “risk-adjusted cost minimization” from the charge

8

Expected cost / variation trade-off

2.3

2.8

3.3

0.60 0.80 1.00 1.20 1.40 1.60 1.80

Debt service / GDP

Stdev debt service / GDP

Better 

outcomes
2.3

2.5

2.7

2.9

3.1

3.3

0.6 0.7 0.8 0.9 1.0 1.1

Debt service / GDP

Stdev debt service / GDP

2.3

2.5

2.7

2.9

3.1

3.3

2.4 2.5 2.6 2.7 2.8 2.9

Debt service / GDP

Stdev total deficit/ GDP

More

long-end

More 

More belly bills

Baseline

Model results with alternative measure of risk

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 Funding risk is often discussed in terms of variation in funding costs (as used in earlier results); however, the more appropriate measure 

to use in many economic models is the variation in the fiscal deficit

 We can conduct the same exercise of considering a range of issuance strategies to trace out a frontier of potential outcomes under this 

metric for funding risk

 The negative correlation between shorter-term rates and the primary deficit makes issuing at front and intermediate maturities appear 

even more attractive, bringing the lower end of the frontier to the left in the chart (this finding is consistent with previously published work 

on debt optimization1)

 The performance of increasing bill issuance and increasing belly issuance become more similar in this case

9

Expected cost / variation trade-off

1. See for example Bolder and Deeley, “The Canadian Debt-Strategy Model: An Overview of the Principal Elements”, 2011
WAM extension since 2007

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The model can be used to assess the WAM extension that resulted from issuance changes between 2007 and 2015

 Those issuance changes boosted the projected WAM by nearly a year

 We consider additional debt management changes that would raise long-end issuance enough to boost the projected WAM 

further

10

WAM profiles under alternative issuance scenarios

3

4

5

6

7

8

9

10

2000 2005 2010 2015 2020 2025 2030 2035

1. Historical simulations from date X assume the issuance pattern as of date X is unchanged over the projection horizon, and jump off from historical debt distribution as of date X. From date X to the 

present, realized values for macro variables and rates are used. From the present to the end of the projection horizon, model-simulated values are used

Actual

1y additional extension1

Simulation with 2007 issuance1

Simulation with 2015 issuance1

2.5y additional extension1
WAM extension in the context of the model

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The previous increase in WAM appears to have been relatively efficient in this model, reducing funding risk without raising 

expected cost

 An additional extension of WAM provides a less favorable trade-off, as it raises funding costs without reducing risk 

meaningfully (and even raising risk when measured by the standard deviation of the budget)

11

Expected cost / variation trade-off

2.3

2.5

2.7

2.9

3.1

3.3

0.6 0.7 0.8 0.9 1.0 1.1

Debt service / GDP

Stdev debt service / GDP

2007 1y add'l 

extension

2015

2.5y add'l

extension

2.3

2.5

2.7

2.9

3.1

3.3

2.4 2.5 2.6 2.7 2.8 2.9

Debt service / GDP

Stdev total deficit / GDP

2007

1y add'l

extension

2015

2.5y add'l

extension
WAM and alternative measures of funding risk

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

12

 WAM has some shortcomings as a proxy for risk. In our simulations, extending WAM is a good proxy for risk reduction only 

when starting at a short average maturity. After a point, extending the WAM increases risk

 We consider several other summary measures of the debt distribution, including (1) weighted median maturity (WMM), (2) 

“truncated” WAM, which treats all debt >10y equally in terms of WAM impact, (3) the share of debt maturing in >1y, (4) the 

share of debt maturing in 2-5y, and (5) a measure of “concentration,” or the degree to which the debt outstanding differs from 

a uniform distribution

 An ideal measure that accurately captures the amount of risk reduction would have a correlation of -1. Among the measures 

considered, the share of debt maturing in 2-5y has the most negative correlation with our preferred measure of risk, 

suggesting that it may be a useful measure to consider in addition to WAM

2.50

2.52

2.54

2.56

2.58

2.60

2.62

2.64

2.66

2.68

2.70

0 5 10 15

Stdev total deficit/ GDP

WAM

Current 

>1y share -0.98 2y-5y share -0.89

TWAM -0.77 >1y share -0.44

WAM -0.70 TWAM 0.02

2y-5y share -0.55 WAM 0.11

WMM -0.51 WMM 0.29

Concentration 0.95 Concentration 0.34

Correlation w/ stdev 

funding cost1

Correlation w/ stdev 

total deficit1

1. Points correspond to the strategies explored in Slide 7
Extending the model with a dynamic debt management reaction function

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 All of the issuance strategies considered above are static issuance strategies that assume a constant mix 

of issuance across tenors through time

 We can improve on this approach by allowing the optimal issuance to vary with the macroeconomic 

environment

 The subsequent slides show preliminary results for an optimal issuance strategy that responds 

dynamically to budget deficits, term premium and short term real rates

 Solving for an optimal issuance reaction function rather than fixed issuance weights helps provide 

useful intuition on how sovereign debt issuers should modify their issuance patterns given changes in 

the macroeconomic environment

 The model optimizes by choosing the coefficients of a linear issuance response function in order to 

minimize the risk-adjusted expected costs of issuance subject to various constraints (see Appendix for 

detailed description of the model)

 Use of kernels and the linear response function reduces the dimensionality of the problem and allows 

for a large set of dynamic issuance strategies to be considered in the optimization

13
 -

 200

 400

 600

 800

 1,000

 1,200

 1,400

 1,600

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

200620082010201220142016

real2y TP 10y Deficit (RHS)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200620082010201220142016

Bills 2 3 5 7 10 30

Debt management reaction function has issuance responding significantly to 

changes in the macroeconomic environment

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

1. Bill issuance across varying tenors are all scaled to 1-year (52-week) tenor, i.e. 100B of 26-week Bills scales to 50B of 1-year equivalent Bills

Optimal issuance mix1

Sensitivity of optimal issuance to 

MEVs; % pts per 1 sigma move in MEV Macroeconomic variables

-40

-30

-20

-10

0

10

20

30

40

Bills Belly Long end

real2y term premium deficit

14

 In general, optimal issuance can respond significantly to macroeconomic variables (MEVs), including deficits, rates, and term 

premium

 Rising deficits generally favor a rotation out of bills into the belly of the curve

 High term premium favors a higher proportion of issuance in bills versus all coupons

 High real 2-year rates favors a rotation from the belly into bills

 Declining term premium and low 2-year real yields has caused the optimal mix to trend towards intermediates over time
-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

200620082010201220142016

Bills 2 3 5 7 10 30

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200620082010201220142016

Bills 2 3 5 7 10 30

Issuance under the dynamic reaction function compared to historical issuance

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 Actual issuance patterns have been more stable over time than what is signaled by the optimization model; in part this 

reflects the importance of regular and predictable issuance for Treasury

 Variability in optimal issuance over time most pronounced in bills and intermediates; by contrast, the recommended 

allocation to the long end is more stable over the sample

 Reaction function has consistently favored a lower allocation to bills and higher allocation to intermediates than actual 

issuance

 Today’s optimal mix recommends close to the largest allocation to intermediates of the last decade

 Model currently favors over 60% of issuance in 2s/3s/5s and less than 25% in bills

 Primarily reflects low real rates, and rising budget deficits

Optimal issuance mix Δ optimal – actual historical mix 1

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

200620082010201220142016

Bills 2 3 5 7 10 30

15

1. Bill issuance across varying tenors are all scaled to 1-year (52-week) tenor, i.e. 100B of 26-week Bills scales to 50B of 1-year equivalent Bills

Actual historical issuance mix1
Expected cost/variance tradeoff

Risk/return improvements from dynamic debt management reaction function

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

16

 Compared to a static issuance strategy, the debt management reaction function allows debt managers to pursue strategies 

with lower expected cost for a given volatility level

 In the chart below, the star provides the expected cost and volatility generated from the debt management reaction function; 

this lies below the efficient frontier, indicating a better outcome for debt managers compared to the static issuance strategies

 One caveat is that the model is not taking into account the importance of regular and predictable issuance for maintaining low 

issuance costs

2.3

2.8

3.3

0.60 0.80 1.00 1.20 1.40 1.60 1.80

Debt service / GDP

Stdev debt service / GDP

Baseline Vary bills Vary belly Vary bonds Blended Optimal response
Risk/cost tradeoffs in dynamic optimization

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The chart below examines how optimal issuance changes with varying degrees of risk aversion on the part of the debt manager; risk is 

quantified using 2 different measures; the first (LHS chart) relates to the volatility of budget deficits relative to GDP while the second (RHS 

chart) relates to the volatility of debt servicing costs relative to GDP. In both cases we add a penalty cost to the objective function that 

increases with the measure of risk

 In the current macroeconomic environment, the optimal mix is relatively insensitive to the degree of risk aversion under both risk 

measures with the mix changing only for very large values of the penalty cost 

 At high enough risk levels, the optimal mix shifts more heavily out of intermediates into bills when the penalty relates to budget volatility; 

as discussed above, this reflects the negative correlation in the model between rates and levels of primary deficits

 When the penalty cost relates to debt servicing cost volatility, the optimal mix shifts out of bills into the long end; for moderate to high 

levels of risk aversion, the reaction function recommends a significant allocation to the long end

Current issuance mix as we change penalty cost on budget or debt service volatility1

23% 23% 23%

48%

19% 19% 19%

23% 23% 23% 12%

9%

22% 22% 22% 12%

7% 7% 7% 9%

3% 3% 3% 8% 3% 3% 3% 1%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Penalty = 0 Base

penalty2

2x

penalty

4x

penalty

Bills 2s 3s 5s 7s 10s 30s

23% 28%

16% 11%

19% 16%

18% 19%

23%

7%

6% 7%

22%

14%

16% 17%

7%

16%

19% 20%

4%

16% 20% 20%

3% 4% 5% 5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Penalty = 0 Base

penalty2

2x

penalty

4x

penalty

Bills 2s 3s 5s 7s 10s 30s

Budget cost to GDP volatility Debt service cost to GDP volatility

1. Penalty cost applied to volatility measure; Left hand side = volatility of budget cost /GDP; Right hand side = volatility of debt service cost /GDP 

2. Base penalty set so that penalty cost = average debt servicing cost in 0 penalty case ($524B); 2x penalty cost = 2x base penalty cost

17

524 982 1,430 2,323

524 532 536 538

- 450 894 1,785

250 253 255 256

Objective function cost ($B) 524 1,020 1,516 2,507

Debt service cost ($B) 524 524 524 528

Penalty cost ($B) - 496 992 1,979

Debt service cost / GDP (bps) 250 250 250 251
Optimal issuance mix with various floors on bill issuance

Optimal coupon mix under different scenarios for bill supply

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

18

 A useful application of debt optimization models is to assess how issuance should change when other constraints are added 

to the debt manager’s objective function. 

 For example, to meet investor demand for liquidity, it may be desirable for Treasury to increase the stock of outstanding bills 

even if it raises the variation in finding costs. The chart below summarizes how the optimal issuance changes when bill 

issuance is constrained to be above various thresholds.

 As the desired level of bill issuance increases, optimization generally favors maintaining long end issuance with cuts in 

intermediate issuance absorbing all of the impact of increased bill supply

 Thus, while much of the earlier discussion supports expanding intermediate issuance, the model is also willing to substitute 

between the belly and bills as part of a broader mandate of meeting investor demand for bill supply

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

10% 20% 30% 40% 50%

Floor on bill issuance

Bills Belly Long end
Model limitations

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 As with any model, our debt optimization framework relies on a number of key inputs and assumptions in 

both the macroeconomic model and optimization framework. In some cases, sensitivity to these inputs are 

high and changing them could change the conclusions from the model. Key sensitivities worth highlighting 

include:

 Supply effects: Introducing a feedback loop where term premium and/or rates are responsive to 

issuance choices would likely bias the results further away from long end issuance

 Yield curve parameters: Assuming a model structure with greater scope for the overall level of rates to 

drift higher over time might support more long-end issuance 

 Issuance constraints: Incorporating additional constraints on issuance such as regular and predictable 

issuance, liquidity-based constraints on bill supply, or other issuance-related constraints could change 

the results of the optimizer

 Types of securities: The model considers only bills and nominal coupons and excludes TIPs and 

FRNs; extending the analysis to include a broader set of issues could change the results 

 Objective function: The current model minimizes risk-adjusted expected costs subject to various 

constraints but other objective functions could be used that would generate different results

19
Conclusions

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

 The modeling work discussed here, while having limitations, provides some meaningful insights into the relevant 

tradeoffs for Treasury in meeting its increased funding needs

 The projected path of debt supply will likely require issuance to increase across a range of maturities. However, the 

optimization framework at least offers a few guideposts for those decisions. It suggests:

 Issuance in the 2-, 3-, and 5-year sector of the curve is attractive for meeting the higher funding needs

– These tenors provide an effective trade-off between expected cost and risk, whether risk is measured by the 

variation in funding costs or budget deficits 

– Further extension of WAM from current levels by increasing long end issuance appears inefficient today 

compared to the past 

– The framework also highlights that the current environment of low real yields, low term premium, and rising 

budget deficits favors issuance in the belly of the curve

 Increased long end issuance could be appropriate in certain cases

– In general the model wants to lean away from long-end issuance

– Heavier reliance on long end issuance may be attractive when the debt manager views the cost of risk as high 

and risk is measured by the variation in funding costs

– Long- end issuance is also favored more when the macroeconomic environment is characterized by low 

deficits, and significantly negative term premium 

– The possibility that the overall level of rates may drift more over time than captured in the model could also 

support long- end issuance

– Finally, a heavier allocation to long end issuance might be appropriate when coupled with increased bill supply 

to achieve a broader mandate on the part of the debt manager to meet investor demand for liquidity

 Increased reliance on bill issuance could also be appropriate in certain cases

– The model generally prefers to move issuance from bills into intermediate maturities

– Bill issuance is more attractive when the term premium is high and budget deficits are low, which are not 

conditions that we see in place today

– However, the model also suggests that debt managers should be more willing to substitute bills for 

intermediate maturities when risk is measured by the volatility of budget deficits costs (rather than debt 

servicing costs)

20
Page

Agenda

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

Appendix 15

21
An illustration of the response function approach

 Once the kernels are specified, actual gross issuance 

notional amounts in each tenor are determined by the 

weights applied to each kernel. We refer to these 

weights as kernel loadings

 The loading on Kernel 1 (the baseline kernel) is 

determined by the total amount of gross issuance 

needed in any given period. As such, this loading is 

determined by the funding need, rather than by any 

active decision making

 However, the loadings on all the other kernels represent 

decisions to shift the issuance profile away from its 

baseline pattern. In our approach, the loadings on these 

kernels are modeled as linear functions of certain rate 

and macro variables. It is these coefficients that are the 

real target of the optimization model

 In our implementation, kernel loadings (except for the 

base kernel) are modeled as linear functions of:

 Real 2Y yield

 10Y ACM term premium, and the 

 Primary budget deficit, in dollars

 The table on the right includes the optimal response 

function produced by the model

 Low real yields in the front end, and/or high longer 

end term premium, warrant shifting issuance into Bills

 High term premium also warrants moving out of the 

Long End and into the Belly

Schematic illustrating the translation of optimal response 

function weights into kernel loadings and issuance notionals

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

Optimization model

Macro & rate 

Environment

(real 2Y rates, term premium and budget deficit)

Kernel loadings

Issuance profile

22

Kernel Loading 

Function Coeffs Constant

Real 2Y 

yield tp10y budget

Base N/A N/A N/A N/A

Into Bills -190.6 215.7 482.9 -0.5

Into Belly 138 -33.4 46.6 0.3

Into Longend -26.4 6.4 -8.9 0 Kernel
 Tenor profile: Optimal response function coefficients, along with knowledge of the macro and market conditions in each time step and in 

each path, specify the gross issuance amounts in each tenor at each time step (in each path)

 Issuance capacity: Minimum (possibly for sector presence reasons) and maximum issue size in each tenor; maximum change in issuance 

size in any period for each tenor; upper bound on duration-weighted gross issuance (Currently set to wide bands for “blue-skies” analysis 

that is intended to relax constraints related to current issuance practice) 

 Fiscal equation: Total gross issuance = Primary budget deficit + Maturing amount + 1-period debt service costs, for each period

 Minimize risk-adjusted expected value (across paths) of PV of costs of new debt issuance over long term (e.g. 40-year) horizon

 Risk-adjusted expected value=expected debt servicing costs + penalty cost for risk

 Risk measured as the sum (across paths) of absolute deviations of the cost along each path from a central cost. This is the linear 

analogue to a limit on the variance of cost across paths

 Coefficients that determine the “response function” that relates the loadings on each issuance kernel to the macro/market variables it is 

allowed to depend on

 Data regarding the debt stock at inception was sourced from the US Treasury 

 Simulated MEV for paths sourced from our Macroeconomic simulation model

A high level description of the dynamic optimization model

D E B T I S S U A N C E O P T I M I Z A T I O N M O D E L S

Constraints

Objective function

Decision variables

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