Treasury Presentation to TBAC
Office of Debt Management

Fiscal Year 2017 Q1 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. Net Marketable Borrowing on “Auto Pilot” Versus Deficit Forecasts p. 19

IV. Portfolio Metrics

A. Weighted Average Maturity of Marketable Debt Outstanding with Projections p. 24

B. Maturity Profile p. 25

V. Demand

A. Summary Statistics p. 30

B. Bid-to-Cover Ratios p. 31

C. Investor Class Awards at Auction p. 36

D. Primary Dealer Awards at Auction p. 40

E. Direct Bidder Awards at Auction p. 41

F. Foreign Awards at Auction p. 42
Section I:

Executive Summary

3
Receipts and Outlays

• Fiscal year-to-date receipts are $25 billion lower than the same period of the previous year, due mainly to a decrease in Federal Reserve 

Earnings. (In December 2015, FAST Act Legislation resulted in a one-time transfer of $19 billion from the Federal Reserve System to the 

Treasury.)

• In Q1 FY 2017, outlays were lower in most categories than in the same period of the previous year. After adjusting for calendar 

differences, however, year-over-year budget outlays were 3 percent higher.

• The main driver behind the growth in outlays were an increase in interest expense (+$15 billion) and HHS expenditures (+$14 billion).

Sources of Financing in Fiscal Year 2017 

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

of $57 billion for Q2 FY 2017, with an end of March cash balance of $100 billion. For Q3 FY 2017, net marketable borrowing need is 

projected to be $1 billion, with an end of June cash balance of $200 billion.

Projected Net Marketable Borrowing

• Between FY 2017 and 2019 Treasury’s net marketable borrowing could rise notably if the Federal Reserve allows the Treasury securities 

held in the SOMA portfolio to mature without reinvesting.

• As of the December 2016 Survey of Primary Dealers, the median expectation was for SOMA reinvestments to continue until June 2018.

Bid-to-Cover Ratios (BTC)

• Since October, BTC ratios for 10-year coupon securities have fallen slightly.

• BTC ratios for all other securities were stable over the October to December period.

Investor Class Allotments

• Since mid-2016, bill auction awards have been trending higher for investment funds and largely stable for other dealers and brokers and 

international institutions. Accordingly, bill auction awards fell for primary dealers.

• Over the same period, coupon auction awards were higher for primary dealers, lower for international institutions and largely stable for 

other investors.

Highlights of Treasury’s February 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%

Dec-06

Apr-07

Aug-07

Dec-07

Apr-08

Aug-08

Dec-08

Apr-09

Aug-09

Dec-09

Apr-10

Aug-10

Dec-10

Apr-11

Aug-11

Dec-11

Apr-12

Aug-12

Dec-12

Apr-13

Aug-13

Dec-13

Apr-14

Aug-14

Dec-14

Apr-15

Aug-15

Dec-15

Apr-16

Aug-16

Dec-16

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

Dec-06

Apr-07

Aug-07

Dec-07

Apr-08

Aug-08

Dec-08

Apr-09

Aug-09

Dec-09

Apr-10

Aug-10

Dec-10

Apr-11

Aug-11

Dec-11

Apr-12

Aug-12

Dec-12

Apr-13

Aug-13

Dec-13

Apr-14

Aug-14

Dec-14

Apr-15

Aug-15

Dec-15

Apr-16

Aug-16

Dec-16

$ bn

Monthly Receipt Levels

(12-Month Moving Average)

Individual Income Taxes Corporation Income Taxes Social Insurance Taxes Other
8 Source: United States Department of the Treasury 

0

50

100

150

200

250

300

HHS

SSA

Defense

Treasury

Agriculture

Labor

VA

Transportation

OPM

Education

Other Defense Civil

$ bn

Eleven Largest Outlays

Oct - Dec FY 2016 Oct - Dec FY 2017
9 Source: United States Department of the Treasury 

(40)

(30)

(20)

(10)

0

10

20

30

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

$ 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

October

November

December

January

February

March

April

May

June

July

August

September

$ bn

Cumulative Budget Deficits by Fiscal Year

FY2015 FY2016 FY2017
11

FY 2017-2019 Deficits and Net Marketable Borrowing Estimates In $ billions

Primary 

Dealers1 CBO2 CBO3 OMB MSR4 OMB5

FY 2017 Deficit Estimate 661 559 433 441 504

FY 2018 Deficit Estimate 771 487 383 330 454

FY 2019 Deficit Estimate 863 601 518 427 550

FY 2017 Deficit Range 525-1010

FY 2018 Deficit Range 587-1035

FY 2019 Deficit Range 690-1200

FY 2017 Net Marketable Borrowing Estimate 699 670 508 573 635

FY 2018 Net Marketable Borrowing Estimate 837 578 452 436 561

FY 2019 Net Marketable Borrowing Estimate 927 676 578 534 659

FY 2017 Net Marketable Borrowing Range 535-1160

FY 2018 Net Marketable Borrowing Range 540-1185

FY 2019 Net Marketable Borrowing Range 700-1250

Estimates as of: Jan-17 Jan-17 Mar-16 Jul-16 Feb-16

1

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

2

Summary Table 1 of CBO's "The Budget and Economic Outlook: 2017 to 2027"

3

Table 1 and 2 of CBO's "An Analysis of the President's 2017 Budget"

4

Table S-11 of OMB's “The FY2017 Mid-Session Review” 

5

Table S-13 of OMB's “Budget of the United States Government, Fiscal Year 2017” 
(12%)

(10%)

(8%)

(6%)

(4%)

(2%)

0%

(1,600)

(1,400)

(1,200)

(1,000)

(800)

(600)

(400)

(200)

0

20072008200920102011201220132014201520162017201820192020202120222023202420252026

% of GDP

$ bn

Fiscal Year

Budget Surplus/Deficit

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

Projections are from Table S-11 of “The FY2017 Mid-Session Review.” 12

OMB’s Projection
Section III:

Financing

13
14

Assumptions for Financing Section (pages 15 to 22)

• Portfolio and SOMA holdings as of 12/31/2016.

• SOMA reinvestments until June 2018, followed by SOMA redemptions until and including February 

2022. These assumptions are based on Chair Yellen’s December 2015 press conference and the median 

expectations from the December 2016 FRB-NY Survey of Primary Dealers. 

• Assumes announced issuance sizes and patterns constant for Nominal Coupons, TIPS, and FRNs as of 

12/31/2016, 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 12/31/2016. 

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

Sources of Financing in Fiscal Year 2017 Q1

*An end-of-December 2016 cash balance of $399 billion versus a beginning-of-October 2016 cash balance of $353 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 171 Security Gross Maturing Net Gross Maturing Net

Net Coupon Issuance 84 4-Week 655 610 45 655 610 45

Subtotal: Net Marketable Borrowing 255 13-Week 505 502 3 505 502 3

26-Week 427 328 99 427 328 99

Ending Cash Balance 399 52-Week 60 36 24 60 36 24

Beginning Cash Balance 353 CMBs 0 0 0 0 0 0

Subtotal: Change in Cash Balance 46 Bill Subtotal 1,647 1,476 171 1,647 1,476 171

Net Implied Funding for FY 2017 Q1* 209

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 42 41 1 42 41 1

2-Year 56 57 (1) 56 57 (1)

3-Year 77 90 (13) 77 90 (13)

5-Year 74 73 1 74 73 1

7-Year 61 65 (4) 61 65 (4)

10-Year 68 23 45 68 23 45

30-Year 42 19 23 42 19 23

5-Year TIPS 14 0 14 14 0 14

10-Year TIPS 12 0 12 12 0 12

30-Year TIPS 5 0 5 5 0 5

Coupon Subtotal 452 368 84 452 368 84

Total 2,099 1,844 255 2,099 1,844 255

Coupon Issuance Coupon Issuance

October - December 2016 October - December 2016 Fiscal Year-to-Date

Bill Issuance Bill Issuance

October - December 2016 Fiscal Year-to-Date
16

Sources of Financing in Fiscal Year 2017 Q2

*Keeping announced issuance sizes and patterns constant for Nominal Coupons, TIPS, and FRNs as of 12/31/2016. 

**Assumes an end-of-March 2017 cash balance of $100 billion versus a beginning-of-January 2017 cash balance of $399 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** 57

Net Coupon Issuance 101

Implied Change in Bills (44)

Security Gross Maturing Net Gross Maturing Net

2-Year FRN 44 41 3 85 82 3

2-Year 116 105 11 172 162 10

3-Year 76 90 (14) 153 180 (27)

5-Year 152 143 8 225 216 9

7-Year 125 131 (7) 185 196 (11)

10-Year 67 22 45 135 45 89

30-Year 41 0 41 84 19 65

5-Year TIPS 0 0 0 14 0 14

10-Year TIPS 26 21 5 38 21 18

30-Year TIPS 8 0 8 13 0 13

Coupon Subtotal 654 553 101 1,106 921 185

January - March 2017

January - March 2017 Fiscal Year-to-Date

Coupon Issuance Coupon Issuance
573

436

534 530

550

652 667 650

739

808

55%

60%

65%

70%

75%

80%

(400)

(200)

0

200

400

600

800

1,000

2017201820192020202120222023202420252026

$ 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)

17

OMB’s projections of net borrowing from the public are from Table S-11 of “The FY2017 Mid-Session Review.” Data labels at the top represent 

the change in debt held by the public in $ billions. “Other” represents borrowing from the public to provide direct and guaranteed loans.

$ bn %

Primary Deficit 233 3.8

Net Interest 5,000 81.4

Other 906 14.8

Total 6,139 100.0

FY2017 - FY2026 Cumulative Total
OMB's economic assumption of the 10-Year Treasury Note rates are from Table S-11 of “The FY2017 Mid-Session Review.” The forward rates 18

are the implied 10-Year Treasury Note rates on December 31 of that year.

1

1.5

2

2.5

3

3.5

4

4.5

20162017201820192020202120222023202420252026

10-Year Treasury Note Rate, %

Interest Rate Assumptions: 10-Year Treasury Note

OMB FY 2017 MSR Implied Forward Rates as of 12/31/2016

10-Year Treasury Rate of 2.45% 

as of 12/31/2016
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-11 of 

“The FY2017 Mid-Session Review.” CBO's estimates of the borrowing from the public are Summary Table 1 of “The Budget and Economic 

Outlook: 2017 to 2027.” See table at the end of this section for details.

*Does not reflect SOMA reinvestments after June 2018 and before February 2022. 

0

200

400

600

800

1,000

1,200

1,400

1,600

20172018201920202021202220232024202520262027

Fiscal Year

Without Fed Reinvestments ($ bn)*

Projected Net Borrowing

CBO's "The Budget and Economic Outlook: 2017 to 2027"

0

200

400

600

800

1,000

1,200

1,400

1,600

20172018201920202021202220232024202520262027

Fiscal Year

With Fed Reinvestments ($ bn)

OMB's FY 2017 Mid-Session Review

PD Survey Marketable Borrowing Estimates
20 Assumes normalization will be complete by FY 2023, which implies no additional funding gap.

0 

(106)

(431)

(342)

(227)

(110)

0 

(500)

(450)

(400)

(350)

(300)

(250)

(200)

(150)

(100)

(50)

0

50

2017201820192020202120222023

$ bn

Fiscal Year

Additional Funding Gap Assuming No SOMA Roll after June 2018
21

Historical Net Marketable Borrowing and Projected Net Borrowing 

Assuming Future Issuance Remains Constant, $ billions

Net Borrowing capacity does not reflect SOMA reinvestments after June 2018 and before February 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-11 of 

“The FY2017 Mid-Session Review.” CBO's estimates of the borrowing from the public are from Table 1 and 2 of “The Budget and Economic 

Outlook: 2017 to 2027.”

Fiscal 

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

Historical/Projected 

Net Borrowing 

Capacity

OMB's FY 2017 MidSession Review

CBO's "The Budget and 

Economic Outlook: 

2017 to 2027"

Primary Dealer 

Survey

2012 139 148 738 90 0 1,115 

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 156 9 292 55 9 520 573 670 699 

2018 0 121 293 56 3 473 436 578 837 

2019 0 (24) 67 42 (9) 76 534 676 927 

2020 0 (86) 83 15 (9) 3 530 753 

2021 0 (76) 99 (20) 0 2 550 859 

2022 0 12 142 (13) 2 142 652 1,017 

2023 0 44 157 (13) 7 195 667 1,055 

2024 0 30 136 (13) 1 154 650 1,082 

2025 0 12 123 (53) (1) 82 739 1,220 

2026 0 (18) 174 (45) (2) 109 808 1,352 
Section IV:

Portfolio Metrics

22
23

Assumptions for Portfolio Metrics Section (pages 25 to 30) and Appendix

• Portfolio and SOMA holdings as of 12/31/2016.

• SOMA reinvestments until June 2018, followed by SOMA redemptions until and including February 

2022. These assumptions are based on Chair Yellen’s December 2015 press conference and the median 

expectations from the December 2016 FRB-NY Survey of Primary Dealers. 

• Assumes announced issuance sizes and patterns constant for Nominal Coupons, TIPS, and FRNs as of 

12/31/2016, 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 12/31/2016. 

• OMB’s estimates of borrowing from the public are Table S-11 of the “Fiscal Year 2017 Mid-Session 

Review.”
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 24

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury.

40

45

50

55

60

65

70

75

80

85

198019821984198619881990199219941996199820002002200420062008201020122014201620182020202220242026

Weighted Average Maturity (Months)

Calendar Year

Weighted Average Maturity of Marketable Debt Outstanding

Historical Adjust Nominal Coupons to Match Financing Needs Historical Average from 1980 to end of FY 2017 Q1

68.9 months on

12/31/2016

59.3 months

(Historical Average

from 1980 to Present)
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 25

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details. 

0

5

10

15

20

25

2017201820192020202120222023202420252026

$ tr

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
26

This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 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]

2009 2,702 774 663 962 559 643 695 6,998 5,101

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 3,632 2,036 1,512 2,459 1,475 1,187 1,950 14,251 9,639

2018 3,870 2,016 1,555 2,479 1,533 1,200 2,065 14,718 9,920

2019 3,854 2,112 1,630 2,577 1,628 1,276 2,205 15,283 10,174

2020 3,919 2,202 1,607 2,737 1,674 1,287 2,419 15,845 10,464

2021 4,008 2,159 1,789 2,793 1,701 1,335 2,643 16,428 10,750

2022 3,966 2,398 1,829 2,884 1,800 1,333 2,906 17,116 11,076

2023 4,204 2,425 1,868 2,913 1,876 1,349 3,185 17,822 11,411

2024 4,271 2,503 1,912 3,046 1,954 1,372 3,453 18,510 11,732

2025 4,310 2,596 1,931 3,331 1,969 1,403 3,751 19,291 12,168

2026 4,403 2,578 2,171 3,387 2,073 1,484 4,044 20,141 12,540
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the basic 27

trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2017201820192020202120222023202420252026

Percent Compositioin

Projected Maturity Profile from end of Fiscal Year

<= 1yr (1,2] (2,3] (3,5] (5,7] (7,10] > 10
28

Recent and Projected Maturity Profile, percent

This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 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]

2009 38.6 11.1 9.5 13.7 8.0 9.2 9.9 59.1 72.9

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 25.5 14.3 10.6 17.3 10.4 8.3 13.7 50.4 67.6

2018 26.3 13.7 10.6 16.8 10.4 8.2 14.0 50.6 67.4

2019 25.2 13.8 10.7 16.9 10.7 8.3 14.4 49.7 66.6

2020 24.7 13.9 10.1 17.3 10.6 8.1 15.3 48.8 66.0

2021 24.4 13.1 10.9 17.0 10.4 8.1 16.1 48.4 65.4

2022 23.2 14.0 10.7 16.8 10.5 7.8 17.0 47.9 64.7

2023 23.6 13.6 10.5 16.3 10.5 7.6 17.9 47.7 64.0

2024 23.1 13.5 10.3 16.5 10.6 7.4 18.7 46.9 63.4

2025 22.3 13.5 10.0 17.3 10.2 7.3 19.4 45.8 63.1

2026 21.9 12.8 10.8 16.8 10.3 7.4 20.1 45.4 62.3
Section V:

Demand

29
30

*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 Q1 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 0.333 3.4 649.0 54.4 5.3 40.3 3.9 0.0 5.6

Bill 13-Week 0.432 3.4 495.3 59.4 6.0 34.6 5.1 0.0 14.0

Bill 26-Week 0.560 3.6 417.2 44.9 2.3 52.8 4.4 0.0 23.7

Bill 52-Week 0.735 3.5 59.5 56.6 2.9 40.5 0.5 0.0 6.6

Coupon 2-Year 1.073 2.6 77.5 55.0 10.9 34.1 0.5 7.8 18.9

Coupon 3-Year 1.177 2.8 71.9 45.3 8.9 45.8 0.1 5.3 25.3

Coupon 5-Year 1.707 2.5 101.9 31.8 4.5 63.6 0.1 10.2 59.8

Coupon 7-Year 2.051 2.6 84.0 20.1 13.8 66.0 0.0 8.4 67.1

Coupon 10-Year 2.096 2.4 63.0 35.6 7.1 57.3 0.0 5.0 68.1

Coupon 30-Year 2.846 2.3 39.0 29.7 9.6 60.7 0.0 3.3 95.3

TIPS 5-Year 0.120 2.7 14.0 18.7 8.0 73.3 0.0 0.0 6.8

TIPS 10-Year 0.369 2.4 11.0 18.2 9.3 72.5 0.0 1.2 12.9

TIPS 30-Year 0.666 2.3 5.0 21.6 9.1 69.4 0.0 0.3 15.0

FRN 2-Year 0.169 3.5 41.0 57.6 0.6 41.8 0.0 0.9 0.0

Total Bills 0.436 3.5 1,620.9 53.5 4.7 41.8 13.9 0.0 50.0

Total Coupons 1.731 2.5 437.1 36.3 9.0 54.8 0.9 40.0 334.5

Total TIPS 0.302 2.5 29.9 19.0 8.6 72.4 0.1 1.5 34.7

Total FRN 0.169 3.5 41.0 57.6 0.6 41.8 0.0 0.9 0.0
1

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

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

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

5

5.5

Jun-14

Jul-14

Aug-14

Sep-14

Oct-14

Nov-14

Dec-14

Jan-15

Feb-15

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

Bid-to-Cover Ratio

Bid-to-Cover Ratios for FRNs

(6-Month Moving Average)

32
33

1

1.5

2

2.5

3

3.5

4

4.5

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

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
34

1

1.5

2

2.5

3

3.5

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

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
1

1.5

2

2.5

3

3.5

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

Bid-to-Cover Ratio

Bid-to-Cover Ratios for TIPS

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

35
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%

5%

10%

15%

20%

25%

30%

35%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

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
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%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

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
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%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

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
39 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%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

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
40 Excludes SOMA add-ons. 

20%

30%

40%

50%

60%

70%

80%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

% 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)
41 Excludes SOMA add-ons. 

0%

5%

10%

15%

20%

25%

30%

Dec-12

Feb-13

Apr-13

Jun-13

Aug-13

Oct-13

Dec-13

Feb-14

Apr-14

Jun-14

Aug-14

Oct-14

Dec-14

Feb-15

Apr-15

Jun-15

Aug-15

Oct-15

Dec-15

Feb-16

Apr-16

Jun-16

Aug-16

Oct-16

Dec-16

% 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)
42 Foreign includes both private sector and official institutions.

0

20

40

60

80

100

120

Dec-14

Jan-15

Feb-15

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

$ bn

Total Foreign Awards of Treasuries at Auction, $ billions

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

43
This scenario does not represent any particular course of action that Treasury is expected to follow. Instead, it is intended to demonstrate the basic 44

trajectory of average maturity absent changes to the mix of securities issued by Treasury. See table on following page for details.

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2017201820192020202120222023202420252026

End of Fiscal Year

Projected Portfolio Composition by Issuance Type

Bills 2,3,5 7,10,30 TIPS (principal accreted to projection date) FRN
45

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. Instead, it is intended to demonstrate the 

basic trajectory of average maturity absent changes to the mix of securities issued by Treasury. 

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

2009 28.5 36.2 27.4 63.6 7.9 0.0

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 26.2 49.7 75.9 9.1 2.4

2018 12.2 26.0 50.0 76.0 9.4 2.3

2019 11.8 26.6 49.9 76.5 9.5 2.2

2020 11.4 27.0 50.1 77.1 9.5 2.1

2021 11.0 27.2 50.6 77.8 9.2 2.0

2022 10.5 27.4 51.2 78.6 9.0 1.9

2023 10.1 27.6 51.6 79.2 8.7 1.9

2024 9.7 27.5 52.4 79.9 8.6 1.8

2025 9.3 27.6 53.2 80.8 8.1 1.7

2026 9.0 27.7 53.9 81.6 7.8 1.7
*Weighted averages of Competitive Awards. 46

**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 10/6/2016 0.260 4.13 39.7 44.4 4.5 51.2 0.3 0.0 0.3

4-Week 10/13/2016 0.265 3.37 39.6 60.4 7.1 32.5 0.3 0.0 0.3

4-Week 10/20/2016 0.245 3.66 44.6 42.9 8.2 48.9 0.3 0.0 0.4

4-Week 10/27/2016 0.240 3.75 49.6 46.9 4.8 48.3 0.3 0.0 0.4

4-Week 11/3/2016 0.240 3.45 54.6 43.7 5.5 50.8 0.3 0.0 0.5

4-Week 11/10/2016 0.270 3.39 64.5 50.4 1.6 48.1 0.4 0.0 0.6

4-Week 11/17/2016 0.305 3.29 64.6 64.5 5.4 30.1 0.3 0.0 0.6

4-Week 11/25/2016 0.340 3.24 54.6 63.1 1.6 35.3 0.3 0.0 0.5

4-Week 12/1/2016 0.365 3.57 43.7 45.4 9.1 45.5 0.3 0.0 0.4

4-Week 12/8/2016 0.340 3.23 44.5 63.5 5.5 31.0 0.4 0.0 0.4

4-Week 12/15/2016 0.480 3.21 44.6 67.3 6.4 26.3 0.3 0.0 0.4

4-Week 12/22/2016 0.490 3.01 54.6 60.5 5.4 34.0 0.3 0.0 0.5

4-Week 12/29/2016 0.485 3.48 49.6 50.6 6.3 43.1 0.3 0.0 0.4

13-Week 10/6/2016 0.310 3.37 41.5 62.7 3.7 33.6 0.4 0.0 1.2

13-Week 10/13/2016 0.360 3.18 41.5 57.8 5.0 37.1 0.4 0.0 1.2

13-Week 10/20/2016 0.340 3.27 41.5 57.3 5.4 37.3 0.4 0.0 1.2

13-Week 10/27/2016 0.340 3.48 40.6 59.4 16.3 24.2 0.4 0.0 1.2

13-Week 11/3/2016 0.350 3.30 41.4 79.7 5.2 15.2 0.4 0.0 1.2

13-Week 11/10/2016 0.420 3.29 41.4 64.0 3.0 33.0 0.4 0.0 1.2

13-Week 11/17/2016 0.515 3.13 41.4 49.2 5.5 45.2 0.4 0.0 1.2

13-Week 11/25/2016 0.480 3.53 38.4 60.0 3.9 36.2 0.4 0.0 1.1

13-Week 12/1/2016 0.490 3.84 34.7 59.7 5.0 35.3 0.3 0.0 1.0

13-Week 12/8/2016 0.490 3.64 33.5 52.7 9.3 38.0 0.4 0.0 0.9

13-Week 12/15/2016 0.530 3.71 33.4 53.3 6.6 40.1 0.4 0.0 1.0

13-Week 12/22/2016 0.515 3.19 33.3 57.1 7.6 35.3 0.5 0.0 1.0

13-Week 12/29/2016 0.555 3.44 32.6 55.5 1.6 42.9 0.4 0.0 1.0

26-Week 10/6/2016 0.490 3.58 35.2 47.6 2.3 50.2 0.4 0.0 2.0

26-Week 10/13/2016 0.495 3.50 35.2 40.0 2.0 58.0 0.3 0.0 2.0

26-Week 10/20/2016 0.470 3.30 35.4 44.6 2.7 52.7 0.3 0.0 2.0

26-Week 10/27/2016 0.475 3.50 34.7 50.8 5.0 44.2 0.3 0.0 2.0

26-Week 11/3/2016 0.500 3.48 35.2 54.6 1.9 43.4 0.4 0.0 2.0

26-Week 11/10/2016 0.535 3.41 35.5 47.7 1.4 50.9 0.3 0.0 2.0

26-Week 11/17/2016 0.625 3.13 35.5 41.1 2.0 56.9 0.3 0.0 2.0

26-Week 11/25/2016 0.605 3.84 32.4 44.3 0.9 54.8 0.3 0.0 1.8

26-Week 12/1/2016 0.610 4.27 28.8 33.2 2.3 64.6 0.3 0.0 1.7

26-Week 12/8/2016 0.615 3.72 27.6 53.6 3.2 43.3 0.3 0.0 1.6

26-Week 12/15/2016 0.645 3.63 27.5 34.9 2.8 62.3 0.4 0.0 1.6

26-Week 12/22/2016 0.645 3.35 27.5 56.0 2.5 41.4 0.4 0.0 1.6

26-Week 12/29/2016 0.660 3.83 26.7 31.8 1.3 66.8 0.3 0.0 1.6

52-Week 10/13/2016 0.680 3.46 19.8 53.5 2.2 44.3 0.2 0.0 2.2

52-Week 11/10/2016 0.695 3.35 19.8 63.3 1.5 35.2 0.2 0.0 2.2

52-Week 12/8/2016 0.830 3.58 19.8 53.0 5.1 41.9 0.2 0.0 2.2

Bills
47

*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 10/31/2016 0.855 2.53 25.8 56.2 10.1 33.7 0.2 1.6 6.0

2-Year 11/30/2016 1.085 2.73 25.8 50.8 13.4 35.8 0.2 2.8 6.3

2-Year 1/3/2017 1.280 2.44 25.8 58.0 9.3 32.7 0.2 3.5 6.5

3-Year 10/17/2016 1.045 2.92 24.0 37.7 10.1 52.1 0.0 0.0 7.8

3-Year 11/15/2016 1.034 2.69 24.0 49.7 7.6 42.6 0.0 5.3 9.6

3-Year 12/15/2016 1.452 2.65 23.9 48.5 9.0 42.6 0.1 0.0 7.9

5-Year 10/31/2016 1.303 2.49 34.0 35.4 4.9 59.7 0.0 2.1 19.3

5-Year 11/30/2016 1.760 2.44 34.0 35.7 4.5 59.8 0.0 3.6 20.0

5-Year 1/3/2017 2.057 2.72 33.9 24.5 4.1 71.4 0.1 4.5 20.6

7-Year 10/31/2016 1.653 2.49 28.0 25.3 13.2 61.5 0.0 1.7 21.7

7-Year 11/30/2016 2.215 2.68 28.0 18.0 9.4 72.7 0.0 3.0 22.4

7-Year 1/3/2017 2.284 2.54 28.0 17.0 19.0 64.0 0.0 3.7 23.0

10-Year 10/17/2016 1.793 2.53 20.0 30.6 6.6 62.7 0.0 0.0 20.0

10-Year 11/15/2016 2.020 2.22 23.0 39.2 8.3 52.5 0.0 5.0 28.2

10-Year 12/15/2016 2.485 2.39 20.0 36.5 6.0 57.5 0.0 0.0 20.0

30-Year 10/17/2016 2.470 2.44 12.0 28.5 6.1 65.4 0.0 0.0 28.2

30-Year 11/15/2016 2.902 2.11 15.0 33.1 12.5 54.5 0.0 3.3 40.7

30-Year 12/15/2016 3.152 2.39 12.0 26.8 9.3 63.9 0.0 0.0 26.4

2-Year FRN 10/31/2016 0.170 3.35 15.0 61.3 1.3 37.4 0.0 0.9 0.0

2-Year FRN 11/25/2016 0.169 3.32 13.0 48.3 0.4 51.3 0.0 0.0 0.0

2-Year FRN 12/30/2016 0.169 3.80 13.0 62.6 0.0 37.4 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 12/30/2016 0.120 2.68 14.0 18.7 8.0 73.3 0.0 0.0 6.8

10-Year TIPS 11/30/2016 0.369 2.39 11.0 18.2 9.3 72.5 0.0 1.2 12.9

30-Year TIPS 10/31/2016 0.666 2.28 5.0 21.6 9.1 69.4 0.0 0.3 15.0

Nominal Coupons

TIPS
January 2017

T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M O D E L S F O R T R E A S U R Y D E B T

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
T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M

O D E L S F O R T R E A S U R Y D E B T

January 31, 2017

Charge Question 

The primary objective of Treasury’s debt management strategy is to finance the government’s borrowing needs at the 

lowest risk-adjusted 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. A number of countries including the United States have developed quantitative models that can assist in 

the evaluation of alternative financing strategies in the face of inherent uncertainty about the future. Treasury 

requests the Committee’s input on the appropriate considerations for and use of these types of models, consistent 

with their ability to calculate interest expense associated with alternative issuance scenarios and to help debt 

managers better understand the implications of various financing choices.

1
Agenda

Page

T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M

O D E L S F O R T R E A S U R Y D E B T

2

Historical Cost of Alternative Issuance Strategies in the US 2

Debt Management Models Developed by Other Countries 8

A Debt Optimization Framework for US Treasuries 16

Appendix 23
H I S T O R I C A L C O S T O F A L T E R N A T I V E I S S U A N C E S T R A T E G I E S I N T H E U S Historical US Treasury Rates By Quarter

 As background to our discussion on key components of a US debt optimization model, we consider what issuance 

strategies have had the lowest cost historically in the US

0

2

4

6

8

10

12

14

16

18

July-61 July-65 July-69 July-73 July-77 July-81 July-85 July-89 July-93 July-97 July-01 July-05 July-09 July-13

Historical US Treasury Interest Rate Levels (%)

3 Month 2 Year 5 Year 10 Year 30 Year

3
H I S T O R I C A L C O S T O F A L T E R N A T I V E I S S U A N C E S T R A T E G I E S I N T H E U S

(10)

(5)

0

5

10

15

20

July-61 July-65 July-69 July-73 July-77 July-81 July-85 July-89 July-93 July-97 July-01 July-05 July-09 July-13

Historical Rates and Rolling Average Rates (%)

2 Year Rate Level Average Rate Rolling For Next 2 Years Realized Term Premium

Historical Premium Of Issuing Term Debt Compared To Rolling Short Debt

2 Year Realized Term Premium = Spot 2 Year Rate - Average 3M Rate Rolling For Next 2 Years

4
H I S T O R I C A L C O S T O F A L T E R N A T I V E I S S U A N C E S T R A T E G I E S I N T H E U S

(10)

(5)

0

5

10

15

20

July-61 July-65 July-69 July-73 July-77 July-81 July-85 July-89 July-93 July-97 July-01 July-05 July-09 July-13

Historical Rates and Rolling Average Rates (%)

5 Year Rate Level Average Rate Rolling For Next 5 Years Realized Term Premium

Historical Premium of Issuing Term Debt Compared to Rolling Short Debt

5 Year Realized Term Premium = Spot 5 Year Rate – Average 3M Rate Rolling For Next 5 Years 

5
H I S T O R I C A L C O S T O F A L T E R N A T I V E I S S U A N C E S T R A T E G I E S I N T H E U S

(10)

(5)

0

5

10

15

20

July-61 July-65 July-69 July-73 July-77 July-81 July-85 July-89 July-93 July-97 July-01 July-05 July-09 July-13

Historical Rates and Rolling Average Rates (%)

10 Year Rate Level Average Rate Rolling For Next 10 Years Realized Term Premium

Historical Premium of Rolling Short Debt vs Issuing Term Debt 

10 Year Realized Term Premium = Spot 10 Year Rate - Average 3M Rate Rolling For Next 10 Years

6
H I S T O R I C A L C O S T O F A L T E R N A T I V E I S S U A N C E S T R A T E G I E S I N T H E U S US Treasury Interest Expense Over Historical 5 Year Intervals

Rates 

Generally 

Increasing

Rates 

Generally

Decreasing

 The below table shows interest expense and average interest rate paid during 5 year intervals over the last 50 

years

 Each strategy involves the issuer maintaining a fixed amount of outstanding debt by issuing debt of a maturity M 

where 1/M of outstanding debt is scheduled to mature each period; in this case, interest expense will be a 

simple rolling average of historical interest rates

 While interest rates have oscillated, rates generally increased prior to 1981 and decreased after 1981

 Longer-term debt strategies perform better as rates increase; shorter-term strategies perform better as rates 

decrease

 In this dataset, the benefit of longer-term issuance in rising rate environments is small relative to its disadvantage 

in declining rate environments

3 Month 2 Year 5 Year 10 Year 3 Month 2 Year 5 Year 10 Year

1967-71 $28.0 $29.0 $25.7 $23.7 5.60 5.79 5.14 4.73

1972-76 $30.7 $33.5 $33.4 $29.8 6.13 6.69 6.68 5.96

1977-81 $50.5 $43.7 $40.0 $37.1 10.10 8.74 8.01 7.43

1982-86 $44.4 $57.0 $57.9 $49.4 8.87 11.41 11.58 9.88

1987-91 $35.2 $39.3 $45.2 $52.6 7.04 7.86 9.04 10.52

1992-96 $21.6 $27.7 $35.3 $42.5 4.32 5.53 7.05 8.51

1997-01 $25.1 $28.2 $30.0 $34.9 5.03 5.64 6.00 6.98

2002-06 $12.5 $15.0 $22.3 $28.7 2.50 2.99 4.46 5.73

2007-11 $7.7 $12.5 $18.0 $23.6 1.55 2.50 3.60 4.73

2012-16 $1.3 $2.2 $8.0 $17.6 0.26 0.44 1.60 3.53

5 Year Interest Expense Per $100 Issued Average % Rate Paid Over 5 Year Intervals

Interest expense and average rate paid

7
Agenda

Page

T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M

O D E L S F O R T R E A S U R Y D E B T

8

Debt Management Models Developed by Other Countries 8

Historical Cost of Alternative Issuance Strategies in the US 2

A Debt Optimization Framework for US Treasuries 16

Appendix 23
D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Government Debt Optimization Models

 Many sovereign debt managers utilize stochastic simulation/optimization models to help inform their decisions about 

debt issuance and the optimal maturity structure of government debt.

 The Debt Management Office of Canada, UK, Sweden, Brazil, and Turkey have all published detailed working 

papers highlighting the key components of their models. Other countries (e.g., Denmark, Austria, Portugal and 

Belgium) have indicated that they utilize stochastic simulations of alternative debt management strategies.* 

 The models are generally used to help quantify the tradeoffs debt managers face between the expected cost of debt 

issuance over time and the variability of these costs across different scenarios.

 In a survey of 71 public debt managers conducted by the US Treasury and World Bank at the 2012 Sovereign Debt 

Managers forum, more than half of managers said their debt strategy is supported by stochastic simulation models 

that quantify risk/cost tradeoffs. While the survey indicated that 100% of HIC’s (high income countries) had a debt 

management strategy that was supported by quantitative analysis, only about one-third (37%) had published details 

of the model underlying their strategy. 

* See for example Bolder and Deeley, “The Canadian Debt-Strategy Model: An Overview of the Principal Elements”, 2011; Pick and Anthony, “A Simulation model for the analysis of the UK’s sovereign debt 

strategy”, 2006; “The SNDO’s Simulation Model for Government Debt Analysis”, 2002 and Advances in Risk Management of Public Debt,, OECD 2005.

27%

29%

31%

13%

0%

5%

10%

15%

20%

25%

30%

35%

Yes, deterministic and

stochastic

Yes stochastic models Yes, deterministic models N o

2012 Sovereign Debt Managers forum survey results on whether the manager has a formal debt management 

strategy based on quantitative analysis

9
D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Key Components Of Debt Simulation/Optimization Models

 In broad terms, the models used by debt managers (including the US Treasury) are quite similar and generally 

involve the following four key components:

 A simple macroeconomic model that can be used to generate stochastic simulations of different economic and 

interest rate environments. 

 A term structure model for relating the yield curve to short rates.

 An objective function of the debt manager that typically involves minimizing expected issuance costs through 

time subject to constraints on risk and other variables.

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

 The models are primarily used to quantify tradeoffs between cost and risk (i.e., an efficient frontier) rather than 

identifying a single optimal strategy.

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D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Graphical Representation Of Debt Optimization Model

Constraints Debt stock 

dynamics

Macroeconomic model Yield curve model

Stochastic simulation of 

rates, primary deficits, 

inflation

Issuance strategy

Calculation of cost and risk 

characteristics

11
0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

2014 2016 2018 2020 2022 2024 2026

Estimated Monetary Policy Rule Implied forward Actual

D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Overview Of Macroeconomic And Yield Curve Models

 Macro models used by debt managers typically involve separate equations for the output gap, inflation, short term 

policy rates, and the primary deficit. 

 A variety of yield curve models are used by debt managers to generate stochastic paths for interest rates as a 

function of the macroeconomic environment.

 One shortcoming of all of the macro models used in published papers on debt optimization is the lack of any 

clear link between short term rates derived from the model and forward rates implied from the yield curve.

 This disconnect is potentially important in the U.S. where most macroeconomic models currently produce a 

much steeper path for the funds rate than what is implied by market forward rates and estimates of the term 

premium (see Chart).

 Testing the robustness of optimization results to alternative yield curve assumptions should be a key component 

of debt optimization.

Projected Fed funds rate derived from a simple macroeconomic model of the US economy (%)

12
D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Objective Function And Risk Constraints

 Most of the simulation/optimization models in use include an objective function that minimizes expected costs of 

new debt issuance over a long term horizon.

 Expectations are taken over multiple paths for interest rates, deficits, and inflation.

 Choice variables include allocation across different points on the yield curve usually constructed to be constant 

weights through time.

Objective function

Constraints

 Risk constraints relate to limits on variability of either debt expense or fiscal balance.

 Constraints based on fiscal balance incorporate correlation between rates and primary deficits and are better 

aligned with academic literature that highlight social welfare benefits from tax smoothing.*

 Risk measures used are either a standard volatility measure (e.g. standard deviation of debt expense or budget) 

or a VAR type limit (e.g. 95% confidence interval).

 Risk measures could also be incorporated directly into the objective function in a way that is mathematically 

equivalent to having them as a constraint.

 Other constraints typically considered reflect a desire for regular and predictable issuance and include: 

 Limiting the change in issuance amount for each tenor from period-to-period

 Limiting the overall WAM

 Maintaining a specified amount of issuance at various points on the curve (in order to support market liquidity 

and/or regulatory objectives).

 An issuance penalty function that increases cost with issue size.

* See for example Barro, 1974. “Are Government Bonds New Wealth?” Journal of Political Economy 83, no.6 (November-December):1095-117

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D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Some Differences In Models Used By Sovereign Debt Managers In Other 

Countries

 Many differences exist in the exact specification of costs and risks in the published models.

 Debt costs can be measured in absolute dollars, as a percent of outstanding debt, or as a percent of GDP; costs 

can be discounted or undiscounted.

 Risk can be calculated at a single point in time or averaged over all time periods (the Canadian model is one of 

the few that provide actual simulation results showing how the cost-risk tradeoff is impacted by alternative risk 

specifications).

 Countries that must take credit risk into consideration (i.e., countries with elevated public indebtedness or emerging 

market economies) tend to view debt management as part of an integrated asset/liability framework.

 There are variety of different approaches used to establish the initial conditions for the simulation. For example, 

Sweden starts with a portfolio that matches the specified strategy while the UK uses the actual portfolio as a 

jumping off point but sets the initial values for macroeconomic variables and the yield curve on the basis of long run 

historical averages.

 The issuance of foreign currency debt can create significant modelling complications.

 Differences in yield curves and yield curve models can have a significant effect on results

 In the UK model, the optimal cost–risk tradeoff is generally achieved by skewing issuance toward long maturity 

Gilts. This seems attributable to an assumption that the yield curve is downward sloping at the long end of the 

curve. 

 In the UK model, It can take 20 years or more to achieve a steady state cost outcome. This likely reflects the 

inclusion of a meaningful amount of 30-year and 50-year maturities (for both nominal and inflation-linked gilts) in 

the issuance mix.

14
D E B T M A N A G E M E N T M

O D E L S D E V E L O P E D B Y O T H E R C O U N T R I E S Key Insights On Issuance From The Published Models

 Intermediate issuance:

 Optimization models often find the most attractive risk reduction per unit of cost by extending from bills to 

intermediates (e.g. 5-year); the risk reduction per unit of cost tends to be lower when extending further out the 

curve.

 Optimal intermediate issuance levels appear more stable in response to changes in model parameters/risk 

constraints than front-end and long-end issuance.

 Bill issuance and liquidity demand:

 Constraining the optimization to have higher levels of bill issuance (e.g., in order to meet market needs for 

liquidity) appears to have the largest impact on reducing 10- and 30-year issuance in debt optimization with 

smaller effects on intermediates.

 Constraints on debt cost volatility vs. budget volatility:

 Setting risk constraints on the volatility of the fiscal balance rather than debt cost volatility generally results in 

higher levels of short term debt in the optimization; this reflects the negative correlation between interest rates 

and primary deficits.

 Inflation linked bonds:

 Inflation linked bonds provide a diversification benefit and reduce volatility especially when the binding 

constraints are on budgetary volatility; at low target levels of volatility, the optimal issuance strategy can include 

substantial amounts of inflation linked bonds.

 Other constraints:

 When issuance is constrained by a target WAM, 30-year debt has a larger weight; this reflects the fact that the 

marginal impact of 30-year debt on WAM is larger per unit of cost relative to 5-year and 10-year bonds.

 The inclusion of Issuance penalties that include additional costs from issuing in large size reduces the incidence 

of corner solutions with debt more evenly allocated across the curve.

15
Agenda

Page

T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M

O D E L S F O R T R E A S U R Y D E B T

16

A Debt Optimization Framework for US Treasuries 16

Historical Cost of Alternative Issuance Strategies in the US 2

Debt Management Models Developed by Other Countries 8

Appendix 23
A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S Motivation For Constructing A U.S. Debt Model

 A model allows a richer framework for considering debt management decisions than the historical exercise shown 

earlier

 Simulate the range of outcomes that could take place going forward under various assumptions about the 

economy and interest rates

 Measure some of the trade-offs involved in debt management decisions

 Explore the sensitivity of those trade-offs to different assumptions about the behavior of the economy and rates

 TBAC members have been working on several different models that could be applied to the U.S. Treasury market

 All models are a work in progress at this point

 This presentation will show some preliminary results from one of those models

 Those results provides an initial look at whether we see some of the same patterns that were described above 

for the models from other countries

 This effort should complement the work by the Office of Debt Management

 ODM’s quantitative strategies group has done extensive modeling of debt dynamics (see appendix for more 

detail)

 Highly detailed models for tracking and analyzing debt characteristics, and able to do simulations to assess 

various debt management issues

 Likely to be synergy between the various modeling efforts

17
A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S Structure Of The Model: Macro Equations

 Structure of the model involves equations for the following variables:

 Unemployment rate (IS curve, expressed in terms of gap from full employment)

 Inflation (Phillips curve)

 Short -term interest rates (monetary policy rule)

 Primary deficit (equation relating to business cycle)

 This structure describes macroeconomic dynamics in order to capture their effects on the evolution of Treasury borrowing 

needs and its funding rates

 Simulations of the model can be used to measure the uncertainty about these variables

Core PCE inflation

(QoQ SAAR)

Fed funds rate

(%)

Primary budget balance 

(% of GDP)

Unemployment rate

(%)

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

201720192021202320252027

Mean

15th/85th percentile

0

1

2

3

4

5

201720192021202320252027

Mean

15th/85th percentile

-5

-4

-3

-2

-1

0

1

2

3

201720192021202320252027

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15th/85th percentile

0

1

2

3

4

5

6

7

8

201720192021202320252027

Mean

15th/85th percentile

18
A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S Structure Of The Model: Treasury Yield Equations

 Model explicitly focuses on the evolution of term premiums

 Useful given the key importance of the term premium in debt management decisions

 The current version relies on a measure of term premiums from outside the model

 Using the term premium measures from Adrian, Crump, and Moench (2013)*

 Introduces some inconsistency with the structure of the macro equations that we assume gradually dissipates

 Macro variables in the model explain some, but not all, of the variation in term premiums

 Rest of movements are assumed to be persistent but eventually mean-reverting

History of ACM Term Premium Measures 

(pp)

Distribution of Term Premium Measures in 10 Years 

(pp)

-1.0

-0.5

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1995 2000 2005 2010 2015

2-year 10-year

0.0

0.1

0.1

0.2

0.2

0.3

0.3

0.4

-1.625-1.375-1.125-0.875-0.625-0.375-0.125

0.1250.3750.6250.8751.1251.3751.6251.8752.1252.3752.6252.875

Frequency

2-year 10-year

19

* Adrian, Tobias, Crump, Richard, Moench, Emanuel, 2013. “Pricing the term structure with linear regression”, Journal of Financial Economics
A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S Structure Of The Model: Other Components

 Structure captures how yield curve and deficits evolve given economic and other shocks

 Determines the correlation of borrowing costs with deficits

 Can run simulations for the next 10 years and beyond

 Debt stock dynamics

 Track outstanding debt in terms of its maturity distribution and costs

 Primary deficit and debt cost determine total budget deficit

 Total deficit and maturing debt determine gross issuance needs

 Issuance assumptions

 Need to make assumptions about how new issuance will be allocated across maturities

 Here consider hypothetical issuance strategies where all debt issued at a single maturity point

 These strategies are not realistic, but are simply intended to demonstrate trade-offs in the model

 In running these simulations, we are ignoring constraints on issue sizes or any pressure on yields from supply

 Relevant statistics for debt management

 We compute a variety of statistics for average debt cost and the variability of the budget under these 

assumptions

 These statistics are computed for the simulated values at the end of a 10-year horizon

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A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S

10-years ahead Bills only 2y only 5y only 10y only 30y only

Average issuance rate 2.93 2.99 3.27 3.72 4.37

Average debt service / GDP 2.60 2.63 2.92 3.22 4.00

Standard deviation debt service / GDP 1.74 1.35 0.53 0.51 0.61

Standard deviation issuance rate 2.22 1.97 1.09 0.69 0.46

Standard deviation primary deficit / GDP 2.24 2.24 2.24 2.24 2.24

Correlation of issuance rate w/ primary deficit -0.41 -0.55 -0.54 -0.15 -0.13

Standard deviation total deficit / GDP 2.37 2.48 2.50 2.52 2.59

Average WAM 1.4 2.1 3.3 5.1 23.6

Standard deviation WAM 0.1 0.1 0.1 0.3 0.4

Average WAC 2.97 3.00 3.24 3.49 4.15

Standard deviation WAC 2.04 1.61 0.61 0.26 0.17

Average debt / GDP 85 85 86 87 92

Standard deviation debt / GDP 11 12 15 16 16

*Based on simulations of 10,000 paths per issuance strategy.

Issuance strategy

Macro Debt Model Simulations*

Relevant Statistics Under Concentrated Issuance Strategies

21
A D E B T O P T I M I Z A T I O N F R A M E W

O R K F O R U S T R E A S U R I E S Preliminary Observations From The Results

 The average cost of the debt is upward sloping in maturity of issuance

 This pattern reflects the fact that the term premium in the model reverts to an average level that is upward 

sloping in maturity

 A key issue is whether to assume this type of reversion towards historical averages

 If the term premium instead stays closer to its current levels, long-term debt would be more attractive than 

suggested in the above results.

 The variation in debt cost falls notably as the maturity extends to intermediate horizons

 This finding is similar to the result from other models—that a considerable reduction in the variability of debt cost 

is realized by extending from bills out to around the 5-year sector

 The variability stabilizes and turns slightly higher at long maturities because of the variability of the term premium 

and the larger amount of debt that occurs when issuing at higher cost

 The correlation of rates and the economy makes issuing shorter-term debt more attractive

 The standard deviation of the budget could be considered a more relevant measure for debt management than 

the standard deviation of the debt cost

 The correlation of interest rates with the economy favors issuing shorter-term debt relative to longer-term debt 

under this metric

 This pattern arises because issuing shorter term debt makes interest expense pro-cyclical, offsetting the countercyclical nature of the primary deficit

22
Agenda

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T B A C C H A R G E Q U E S T I O N : O P T I M I Z A T I O N M

O D E L S F O R T R E A S U R Y D E B T

23

Appendix 23

Historical Cost of Alternative Issuance Strategies in the US 2

Debt Management Models Developed by Other Countries 8

A Debt Optimization Framework for US Treasuries 16
A P P E N D I X Debt Model Currently Used By US Treasury Office Of Debt Management

 QSG within the Office of Debt Management (ODM) has developed a number of quantitative models that are used in 

policy and market analyses

 ODM debt issuance models include the following characteristics:

 Forward portfolio simulation for either 1yr for short term and 10yr for long term

– Simulations are at the CUSIP-level and provides daily cash flows

 Rates, deficits, CPI, SOMA assumptions (POMO purchases, sells, and reinvestment policy) are inputs which 

define a scenario

– Daily fiscal flows projections provided from the Office of Fiscal Projections are used for short term model

– Primary deficit, net interest, and other transactions affecting the borrowing from the public are provided by 

OMB and CBO’s budget are used as inputs for the long term model.

 Issue sizes constraints: lower/upper bounds, bounds on size changes, number of CMBs, issue ratios, etc.

– Supply feedback effect on rates implicitly controlled by maximum size changes

 Cash balance constraints: lower/upper bounds, hard targets on specific date(s), generally sufficient to cover 

one week of outflows, etc.

 Optimize future issue sizes to minimize the present value of future debt-service costs

– Linear programming problem

– (rates, CPI, deficits, SOMA, constraints ...)  Optimal-cost issuance/metrics

 Fix market assumptions, vary constraints: see tradeoffs involved in changing policy (as embodied by 

constraints)

 Fix constraints, vary market assumptions: see risk attached to a fixed policy window

 Rate, CPI, deficit inputs may be stochastic (Monte Carlo simulation)

– ODM has developed an internal joint nominal and real term structure model with shadow rate.

– ODM has also implemented ACM term structure model for internal use.

– Able to test Fed rate hike/hold scenarios as well as highly volatile rate environment.

24