Discussion of Treasury Futures Positions 

Across Different Investor Types

Treasury Borrowing Advisory Committee

January 30th, 2024

1

“According to Treasury futures positioning data, asset manager long positions and leveraged fund

short positions have increased significantly. Please discuss the factors that could be driving this

dynamic. What are the reasons for asset managers to prefer the Treasury futures market over the

cash market for their duration needs? What type of activity does the leveraged short positioning

reflect; for example, to what extent could this be cash-futures basis trading activity? What are

important factors to consider when monitoring changes in cash-futures basis positions?"
Summary

➢ In this presentation, we examine the large increases in asset manager longs and

leveraged fund shorts in Treasury futures and propose potential structural factors that

may be contributing to the persistent increases over time.

➢ We discuss specific reasons why asset managers use Treasury futures and find that

their strategic asset allocation has resulted in lower Treasury allocations and a potential

structural need for Treasury futures.

➢ We also discuss how leveraged funds use Treasury futures, and what types of levered

strategies might result in consistently opposing positions relative to asset managers.

➢ We conclude that relative-value trading strategies are the most likely driver of structural

leveraged fund shorts in Treasury futures and propose some relevant relationships for

Treasury to monitor on the Treasury futures basis trade.

➢ We suggest that a mutually beneficial relationship exists between asset managers and

leveraged fund positioning in Treasury futures.

➢ We conclude with a brief discussion of potential interactions between asset-managers

and leveraged fund positioning and possible areas of future research.

2
3

Review of CFTC Futures Data
Overview of CFTC Positioning Data

➢ The CFTC Traders in Financial Futures (TFF) report separates large traders in the

financial markets into four categories(1):

4

(1) Information sourced from CFTC Traders in Financial Futures (TFF) Explanatory Notes

Dealer / Intermediary

“Includes large banks (U.S. and non-U.S.) and dealers in 

securities, swaps and other derivatives.”

Asset Manager / Institutional

“Institutional investors, including pension funds, 

endowments, insurance companies, mutual funds and 

those portfolio/investment managers whose clients are 

predominantly institutional. “

Leveraged Funds

“Typically hedge funds and various types of money 

managers, including registered commodity trading 

advisors (CTAs); registered commodity pool operators 

(CPOs) or unregistered funds identified by CFTC.3”

Other Reportables

“Includes corporate treasuries, central banks, smaller 

banks, mortgage originators, credit unions and any other 

reportable traders not assigned to the other three 

categories.“ 

CFTC Traders in Financial Futures (TFF) Categories
Overview of CFTC Positioning Data

➢ Investor category data is available since 2006.

➢ We first show in Figure 1 total futures open interest(1) vs. the size of the Treasury market.(2)

➢ For Treasuries, we use total coupons outstanding excluding SOMA holdings.

➢ Open interest has grown with the overall size of the Treasury market.

➢ As a percentage of the market (Figure 2), open interest has been stable after a large decline

during the global financial crisis. Recently we’ve seen re-leveraging and wider range.

(1) Data on Treasury futures is sourced from the CFTC Traders in Financial Futures report as of Dec 2023 5

(2) Data on Treasury securities is sourced from US Treasury and NY Fed as of Dec 2023

Futures Open Interest (Left 

Axis, $Tr)

Treasury Coupons 

Outstanding ex. SOMA 

(Right Axis, $Tr)

0

4

8

12

16

20

0.0

0.5

1.0

1.5

2.0

2.5

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 1: Treasury Futures Open Interest (Face Amount) vs. 

Treasury Coupons Outstanding (ex. SOMA)

0%

5%

10%

15%

20%

25%

30%

35%

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 2: Treasury Futures Open Interest (Face Amount)

% of Treasury Coupons Outstanding (ex. SOMA)

Reduced Leverage / 

Contained Range Post GFC

Wider Range, Some 

Releveraging 2018 Onwards
Overview of CFTC Positioning Data

➢ Recently there have been large increases in both asset manager and leveraged fund positions in

Treasury futures.

➢ Since November 2021, asset managers (AM) have increased their net position from $100bn to over

$700bn, while leveraged funds (LF) have moved from flat to short almost $800bn.(1)

➢ When normalized by the size of the Treasury market(2) in Figure 4, recent trends look similar. One

interesting thing to note is the size of AM and LF positions is similar to 2019 peak (not larger).

➢ In the 2006-2007 period, AM and LF relative positions were flipped. This change could indicate a

structural evolution in the ecosystem and how different investors behave.

6

Leveraged 

Funds

Asset 

Managers

Dealer

Other

-1,000

-800

-600

-400

-200

0

200

400

600

800

1,000

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 3: Net Treasury Futures By Investor Type

($Bn Face)

Leveraged 

Funds

Asset 

Managers

Dealer

Other

-6%

-4%

-2%

0%

2%

4%

6%

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 4: Net Treasury Futures by Investor Type

(% Treasury Coupons ex. SOMA)

(1) Data on Treasury futures is sourced from the CFTC Traders in Financial Futures report as of Dec 2023
Overview of CFTC Positioning Data

➢ Most of the net position in futures is concentrated in shorter duration contracts (TU, FV, and

TY) likely due to larger amounts of Treasuries outstanding in these maturity buckets.

➢ Currently, these three contracts represent 80% of the net asset manager notional position and

55% of the net TY equivalent position.

➢ For purposes of the analysis we have focused on notional exposure, as opposed to DV01

exposure, because it is most consistent with quantities of repo/funding needs.

• That said, there are likely important things to consider around DV01 exposure, since it would more

accurately reflect interest rate risk concentration in longer duration securities.

7

(1) Data on Treasury futures is sourced from the CFTC Traders in Financial Futures report as of Dec 2023

Leveraged 

Funds

Asset 

Managers

-400

-300

-200

-100

0

100

200

300

400

06 08 10 12 14 16 18 20 22

Figure 5: Net TU Position 

($Bn Face)

Leveraged 

Funds

Asset 

Managers

-400

-300

-200

-100

0

100

200

300

400

06 08 10 12 14 16 18 20 22

Figure 6: Net FV Position 

($Bn Face)

Leveraged 

Funds

Asset 

Managers

-400

-300

-200

-100

0

100

200

300

400

06 08 10 12 14 16 18 20 22

Figure 7: Net TY Position 

($Bn Face)
Overview of CFTC Positioning Data

➢ We also show data for US and WN contracts (note the axis change) as well as all contracts in

TY equivalent terms as of the end of 2023.

➢ While the contours are not all the same, the broad trends recently (expansion of AM longs and

LF shorts) are consistent across all Treasury futures contracts.

8

(1) Data on Treasury futures is sourced from the CFTC Traders in Financial Futures report as of Dec 2023

Leveraged 

Funds

Asset 

Managers

-80

-60

-40

-20

0

20

40

60

80

06 08 10 12 14 16 18 20 22

Figure 8: Net US Position 

($Bn Face)

Leveraged 

Funds

Asset 

Managers

-80

-60

-40

-20

0

20

40

60

80

06 08 10 12 14 16 18 20 22

Figure 9: Net WN Position 

($Bn Face)

TU

TU

FV

FV

TY

TY

UXY

UXY

US

US

WN WN

0

100

200

300

400

500

600

700

800

Face ($Bn) TY Equiv Face ($Bn)

Figure 10: Asset Manager 

Current Face Amount & TY 

Equivalent Breakdown

79%

55%
9

Asset Manager Discussion
How do Asset Managers Use Futures?

➢ Active asset managers likely use Treasury futures for the following reasons:

1. Expressing directional views on duration and yield curve.

2. Hedging and managing interest rate risk across different sectors & curve points.

3. Obtaining financing / leverage to implement active views vs. benchmark.

➢ Why might asset managers use Treasury futures instead of Treasuries?

1. Could simplify execution and operations (negates need for cash / repo trades).

2. Eliminates reporting repo interest expense.

3. Guidelines might not allow repo leverage (mostly separate accounts).

4. Likely more leverage flexibility compared to 40-Act repo limits.

10
How do Asset Managers Use Futures?

➢ The CFTC data shows that in recent years, asset managers have had a net long bias in Treasury futures,

even with large swings in Treasury yields (10y yield of 0.5% in ‘21 to 5.0% in ’23). Why would this be?

➢ First, what types of positions might cause asset managers to be net long Treasury futures?

1. Active rate views (either long duration or curve steepener)

• Based on an empirical analysis of 20 large mutual funds, asset managers appeared to trade short duration

after the large drop in yields during the COVID pandemic. During this period, there was a large drop in the

asset manager net futures long position, but it remained net long.

• The empirical results(1) in Figure 12 show that asset managers have since moved closer to neutral, and yet the

net futures positions now stand at an all-time high.

2. Financing certain active and/or non-index portfolio allocations

• We view this as the most likely explanation for why asset managers might have a structural position in

futures and will expand on that view in the coming slides

11

Asset Managers Net 

Futures ($bn Face, 

Left Axis)

10Y Yield 

(Right Axis) 0.0

1.0

2.0

3.0

4.0

5.0

6.0

-400

-200

0

200

400

600

800

1,000

06 08 10 12 14 16 18 20 22 24

Figure 11: Asset Manager Net Futures 

vs. 10Y Yield 

Average of 20 

Large Active Core 

Plus Managers

Index 

Fund

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

17 18 19 20 21 22 23

Figure 12: Asset Manager Empirical 

Duration Using Three Factor 

Regression(1)

Average “Active” 

Duration

(1) Sourced from Bloomberg and the presenter’s firm’s calculations. Fund returns are regressed on US 10Y, DXY, and IG Corporate OAS. Data as of 01/17/2024
Asset Managers: Product Mix Tends to Favor Futures 

Relative to Treasury Repo

➢ Below, we show in Table 1 a broad overview of different asset management products

with associated regulatory requirements for repo and futures usage.

➢ We focus on active fixed-income, since passive strategies, which largely track cash

indices, are probably less likely to use Treasury futures.

➢ Based on industry estimates(1), we conclude that most of CFTC asset manager data

represents mutual funds and actively-managed separate accounts.

12

Product Type Governance Guidelines Allow Economic 

Leverage?

Allow 

Repo?

Allow 

Futures?

Active Mutual Fund SEC / 1940 Act Prospectus/SAI Yes Yes(2), 50% Yes

Active ETF SEC / 1940 Act Prospectus/SAI Yes Yes(2), 50% Yes

Collective Trust ERISA Prospectus/SAI Yes No Yes

UCITS ESMA / UCITS Prospectus/SAI Yes Yes Yes

Separate Account Client IMA Depends Depends Depends

(1) When looking at eVestment data for several large asset managers, we found that nearly 90% of AUM was in mutual funds and separate accounts as of Q3 2023

(2) 40-Act limit depends on the mutual fund’s approach to repo under SEC rule 18f-4. Prior to 2020 introduction of 18f-4, repo was typically limited to 50%.

Table 1: Asset Management Products Regulatory Requirements for Repo and Futures Usage 
Asset Managers: Product Mix Tends to Favor Futures 

Relative to Treasury Repo

➢ Mutual funds are regulated by the Investment Company Act of 1940 (“40-Act”)

➢ While established in 1940, various rules and amendments to the 40-Act have been adopted over time.

➢ For many years prior to 2020, the applicable rules created incentives for mutual funds to favor derivatives like futures

over repo in certain cases, including limitations on the size of repo borrowing.

➢ Rule 18f-4 adopted in 2020 established a new option for mutual funds to treat repo like other derivatives (which are

subject to a “VaR test”), though some funds may not have updated their documentation or practices to utilize it. Given

the change was relatively recent, its potential impacts warrant further investigation.

➢ If not using this new option, mutual funds must limit their repo borrowing to 50% of NAV to meet the applicable asset

coverage requirements.

➢ In our view, many mutual funds are still limiting the size of their repo borrowing and achieving leverage through futures.

➢ Separate accounts are typically governed by the client investment management agreement (IMA)

and associated investment guidelines.

➢ Partial but representative data(1) suggests that most institutional accounts do not permit repo.

➢ Futures therefore are in many cases the only way to obtain leverage in a separate account.

13

Core / Core Plus Short Duration Inflation Credit

% SMA AUM that allows economic leverage 74% 98% 77% 84%

% SMA AUM that allows usage of repo 54% 12% 25% 25%

% SMA AUM that allows usage of Tsy futures 78% 27% 85% 97%

Table 2: Separately Managed Accounts Investment Guidelines for Repo/Futures (1)

(1) Sourced from presenter firm’s data and may not correlate with aggregate industry level
Asset Managers: 40-Act Mutual Fund Investment Expense 

Accounting Also Favors Futures

➢ While 40-Act mutual funds can use repurchase agreements, the “interest expense” associated with

repos must be reported separately as an investment expense.

➢ In 2018, in accordance with FINRA Rule 2210(d)(5), some fund analysis providers started including

“interest expense” in their databases of total expense ratios which include management fees and

administrative fixed-costs.

➢ This change had the effect of making providers who prioritize Treasury repo over futures look more

expensive, even though the two products are similar economically and repo is often less expensive.

➢ FINRA issued clarification D.1.2. in 2019, and while efforts have been made to exclude interest

expense from published expense ratios(1), the reality is that if a fund has high interest expense, it

raises questions, even if interest expense generally associated with portfolio structures or leverage

that are expected to add value to the overall portfolio.

14

(1) One Expense Ratio to Rule Them All | Morningstar

Typical Mutual Fund Operating 

Expenses Listed in Prospectus

Management Fees

Distribution Fees

Legal Fees

Interest Expense

Acquired Fund Fees
Asset Managers: Largest Fixed-Income Categories

➢ The largest fixed-income mutual fund category is intermediate core / core plus at 39% of total

assets. Many funds are benchmarked to the Bloomberg U.S. Aggregate Index (“the Agg”),

which is a fairly good, but not complete, representation of the U.S bond market.

➢ Recently flows into short-duration products have also been substantial, where many funds are

benchmarked to 1-3Y Government/Credit and 1-3Y Corporate indices.

➢ We go into some detail on the composition of these indices in the next slide.

15

Morningstar Sub-Category Total Net Assets 

($Bn)

% Fixed-Income 

Category

Intermediate Core-Plus Bond 681 25%

Intermediate Core Bond 381 14%

Short-Term Bond 339 12%

Multisector Bond 267 10%

High Yield Bond 244 9%

Ultrashort Bond 142 5%

Nontraditional Bond 109 4%

Inflation-Protected Bond 85 3%

Intermediate Government 82 3%

Corporate Bond 75 3%

Bank Loan 75 3%

Global Bond-USD Hedged 56 2%

Global Bond 46 2%

Emerging Markets Bond 43 2%

Other 109 4%

Total 2,734 100%

Table 3: Fixed-Income Mutual Fund Sector Breakdown (1)

(1) Sourced from Morningstar as of 12/29/2023

Core + Core Plus + 

Multisector

Short 

Duration

All Other

-100

0

100

200

300

400

500

600

700

800

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 13: Cumulative Fixed-Income Strategy Flows

(2006-2023, $bn) (1)
Asset Managers: Benchmark Indices

➢ Presently, the Agg is about 42% Treasuries, and in total, about 80% government risk (1).

It is an investment-grade only, market value weighted index. The 1-3Y Gov/Credit index

is 66% Treasuries and over 70% government risk.

➢ Notably, the main explanatory market risk factor for the Agg is the level of Treasury

yields, which generally account for over 75% of the modeled risk of the index.

(1) The term “government risk” refers to Treasury debt, Agency debt, and Agency MBS and is highlighted in red. 16

(2) Sourced from Bloomberg as of 12/29/2023. Treasury weights exclude SOMA holdings.

Table 4: Bloomberg Aggregate Index (2)

Sector Market 

Value % YTM Duration

Treasuries 42% 4.07 6.15

Government Related 5% 4.59 5.26

Agency 2% 4.44 3.42

Local Authority 1% 4.80 8.03

Sovereign 1% 5.20 8.58

Supranational 1% 4.22 3.47

IG Corporate 25% 5.09 7.10

Industrial 14% 4.97 7.85

Utility 2% 5.10 8.82

Financial Institutions 8% 5.31 5.31

Securitized 29% 4.67 5.53

Agency MBS 27% 4.63 5.66

ABS 0% 4.92 2.76

CMBS 2% 5.36 4.26

Total 100% 4.52 6.17

Table 5: Bloomberg 1-3Y Government Credit (2)

Sector Market 

Value %

Yield to 

Maturity Duration

Treasuries 66% 4.30 1.89

Government Related 8% 4.55 1.71

Agency 5% 4.58 1.68

Local Authority 0% 4.52 1.86

Sovereign 0% 4.81 1.70

Supranational 3% 4.46 1.72

IG Corporate 25% 5.13 1.78

Industrial 12% 4.91 1.74

Utility 1% 5.10 1.81

Financial Institutions 12% 5.36 1.82

Total 100% 4.53 1.85
Asset Managers: Structural Credit Overweights

➢ When managing against the Bloomberg Aggregate Index, active managers will often

allocate to higher yielding spread assets to achieve an income advantage and a more

diversified portfolio given the heavy interest rate sensitivity of the benchmark.

➢ Spread sector investment decisions are made in assets of varying durations and

maturities, and are often thought of separately from interest rate investment decisions.

➢ Although asset managers have different investment approaches, we believe it’s common

to separate decisions made on interest rate duration and credit spread duration.

➢ Futures allow asset managers to make credit allocation decisions relatively seamlessly,

without impacting interest rate risk exposures, but can introduce basis risk between the

futures allocation and the Treasury allocation in the index.

➢ While the process is more precise with Treasuries + repo, it is more cumbersome to

implement operationally.

➢ It’s likely that structural overweight positions in credit products could result in

persistently higher allocations to Treasury futures amongst asset managers.

17
Asset Managers: Structural Credit Overweights

When allocating out of Treasuries into credit sectors, we highlight two broad transaction types. We focus 

on the second type and the implications for how asset managers hedge duration and curve.

➢ Matched substitution: The manager buys a credit and can sell a Treasury of similar duration.

➢ Results in a reduction of the Treasury allocation and an increase in credit exposure. Minimal need for futures or repo.

➢ Mismatched substitution: The manager buys a credit and must sell a Treasury of different duration.

➢ To control for duration and curve risk, the manager will need to use futures or repo and reverse repo(1).

➢ This happens for several reasons, to name a few:

(1) Manager buys a floating rate credit asset with zero duration.

(2) Manager runs out of similar duration Treasuries to sell from the portfolio.

(3) Manager buys a non-USD credit asset.

18

Table 6: Ways to Hedge Duration and Curve Risk With 

Mismatched Treasury/Credit Substitution

Type Transactions Involved Cost/Benefit

Perfect Hedge with 

Repo and Borrow

(1) Buy credit

(2) Short perfect Treasury hedge

(3) Borrow perfect Treasury

(4) Repo another Treasury to fund credit 

- Most operationally complex

- Generates interest expense

Partial Hedge with 

Repo Only

(1) Buy credit

(2) Short Treasury futures hedge

(3) Repo another Treasury to fund credit

- Some operational complexity

- Generates interest expense

- Introduces some curve risk

Futures Hedge (1) Buy credit

(2) Sell Treasury

(3) Execute futures curve trade

- Less operationally complex

- Introduces basis and curve risk

(1) Note, we assume portfolio managers will typically use the cheapest form of repo with lowest haircut (Treasuries)

(2) Sourced from Bloomberg as of 12/29/2023.

10.4%

14.4%

4.7%

3.6% 3.6%

4.9%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

14.0%

16.0%

1-2y 3-5y 5-7y 7-10y 10-20y 20y+

Figure 14: Bloomberg Agg Index 

Treasury Allocation by Maturity Bucket(2)
Asset Managers: Structural Credit Overweights

➢ A separate complication, which is obscure but meaningful, is that portfolio managers will

sometimes treat credit duration differently than risk-free duration. This matters more for

lower quality credit products, where spread volatility dwarfs interest rate volatility. Bonds

that trade on dollar price, like lower rated high yield, exhibit lower “empirical duration.”(1)

➢ Therefore, an allocation out of Treasuries into lower quality credit, would typically require

a manager to buy back more duration in futures, compared to higher quality credit.

19 (1) Empirical duration can be thought of as a statistical duration as opposed to a cash flow duration

(2) Sourced from Bloomberg as well as the presenter’s firm’s calculations as of 01/10/2024

Adjusted Duration Used 

for Hedging Rate Risk

Model, or Cash 

Flow Duration

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

15 16 17 18 19 20 21 22 23 24

Figure 15: Bloomberg High Yield

Bond Index(2)
Asset Managers: Structural Credit Overweights

Four examples(1) where a mismatched substitution results in a net long position in futures:

➢ Example 1: Buying a floating rate asset

➢ Manager sells Treasuries, replaces risk with Treasury futures, buys a floating rate CLO.

➢ Since the CLO has no duration, for a 5% allocation, a +5.0% net futures position is created.

➢ Example 2: Buying an asset with duration < 2 years

➢ Manager sells Treasuries, replaces risk with Treasury futures, buys a 1y duration ABS, hedges duration with TU futures.

➢ For a 5.0% allocation to the ABS, a +1.7% net futures position is created, net duration change is zero.

20

Trade Security Notional % Cash % Duration 

Contrib Wtd Avg Life Yield OAS

Sell Treasury -5.0% -5.0% (0.31) 7.9 4.10%

Buy Treasury Futures 4.8% 0.31 

Buy CLO 5.0% 5.0% 0.00 2.0 8.00% 2.32%

Net Treasury Futures 4.8%

Net Change to Fund(2) 0.0% 0.00 0.12% 0.12%

Trade Security Notional % Cash % Duration 

Contrib Wtd Avg Life Yield OAS

Sell Treasury -5.0% -5.0% (0.31) 7.9 4.1

Buy Treasury Futures 4.8% 0.31 

Buy Short-Dated ABS 5.0% 5.0% 0.06 1.2 6.7 2.14%

Sell TU Futures Hedge -3.1% (0.06)

Net Treasury Futures 1.7%

Net Change to Fund(2) 0.0% 0.00 0.11% 0.11%

(1) Data in the examples shows the presenter’s firm’s calculations

(2) These simplified examples exclude potential yield impact of Treasury-futures basis or FX hedging cross-currency basis
Asset Managers: Structural Credit Overweights

Four examples(1) where a mismatched substitution results in a net long position in futures:

➢ Example 3: Buying a high spread credit asset

➢ Similar to previous examples, but the high-risk credit is modeled with a duration less than its cash flow weighted duration.

Because of this, the manager has to sell fewer futures to hedge the credit allocation than are bought to replace Treasuries.

➢ Example 4: Buying a Non-USD asset

➢ Also similar to previous examples. In this case, the manager buys a non-USD credit with a different base currency curve.

➢ For a 5.0% allocation to the credit, the manager ends up long 5.0% Treasury futures and short 5.0% non-USD futures.

21

Trade Security Notional % Cash % Duration 

Contrib Wtd Avg Life Yield OAS

Sell Treasury -5.0% -5.0% (0.31) 7.9 4.1

Buy Tsy Futures 4.8% 0.31 

Buy High Yield Corp 5.0% 5.0% 0.08 5.3 7.9 3.33%

Sell Tsy Futures Hedge -2.1% (0.08)

Net Treasury Futures 2.6%

Net Change to Fund(2) 0.0% 0.00 0.17% 0.17%

Trade Security Notional 

%

Cash % Duration 

Contrib Wtd Avg Life Yield OAS

Sell Treasury -5.0% -5.0% (0.31) 7.9 4.1

Buy Treasury Futures 4.8% 0.31 

Buy EUR IG Credit 5.0% 5.0% 0.22 7.2 3.9 1.40%

Sell 5Y Bobl Futures Hedge -5.0% (0.22)

Sell EUR/USD Fwd -5.0%

Net Treasury Futures 4.8%

Net Change to Fund(2) 0.0% 0.00 0.07% 0.07%

(1) Data in the examples shows the presenter’s firm’s calculations

(2) These simplified examples exclude potential yield impact of Treasury-futures basis or FX hedging cross-currency basis
Asset Managers: Structural Credit Overweights

➢ Stylized example shows what an active manager’s allocation could often look like (Figure 17)

compared to an index (Figure 16). In this example, the actively managed portfolio has a 20% out-ofindex credit allocation and a higher yield than the index but maintains the same duration and yield

curve exposure.

➢ To accomplish this, the active positions are funded by selling Treasuries, the net duration and curve

are hedged with Treasury futures (resulting in a net long futures exposure and positive net leverage).

➢ Alternatively, the manager could have repo’d Treasuries to fund the allocations which would have

generated interest expense.

22

42%

5%

25%

29%

Treasuries

Treasury Futures

Government Related

Corporates

Agency MBS

Floating Rate Credit

High Yield

Securitized Products

Non-US Credit

Non-US Rate Futures

0% 20% 40% 60%

Figure 16: Bloomberg Agg Index

Aggregate Index Active Manager

Yield Duration Avg. OAS Yield Duration Avg. OAS

4.52 6.17 0.38 5.36 6.17 1.07

22%

14%

5%

25%

29%

5%

5%

5%

5%

-4%

Treasuries

Treasury Futures

Government Related

Corporates

Agency MBS

Floating Rate Credit

High Yield

Securitized Products

Non-US Credit

Non-US Rate Futures

-20% 0% 20% 40%

Figure 17: Hypothetical Active Manager

(1) Sourced from Bloomberg as of 12/29/2023 and the presenter’s firm’s calculations

(2) Sourced from Bank of America as of Dec 2023

Compared to the AGG ex. 

Treasury Market Value

Compared to the 

AGG Market Value

3%

4%

5%

6%

7%

8%

9%

10%

14 15 16 17 18 19 20 21 22 23

Figure 18: Recent Growth in Floating 

Securitized Assets(2)
Asset Managers: Structural Credit Overweights

Looking deeper at index and industry data, two observations are worth investigating further:

(1) There appears to be a positive relationship between the Treasury allocation in the Aggregate Index(1),

and the CFTC asset manager net futures position (as a % of the Treasury market), shown in Figure 19

➢ It’s not obvious why this relationship exists. One possible explanation is that as Treasury allocations have risen over time, asset

managers chose to increase their overweights to higher returning credit sectors relative to Treasuries.

(2) Using eVestment data(2) and looking at rough sector positioning for 14 large core and core plus active

management platforms ($900bn AUM), there does appear to be a correlation between the AUM

weighted active credit sector exposure and the CFTC asset manger net futures position

➢ This relationship lends some support to the hypothesis that Treasury futures are used to fund active credit sector positions

➢ It does not prove the point definitively, however. More investigation into the types of credit assets owned is required.

(1) Sourced from Bloomberg, CFTC, and the presenter’s firm’s calculations as of 12/29/2023 23

(2) Sourced from eVestment as of Q3 2023

Treasury Weight in 

Aggregate Index 

(%,Left Axis)

CFTC Asset Manager 

Net Futures Position 

(%Tsy Mkt ex. SOMA, 

Right Axis)

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

20%

25%

30%

35%

40%

45%

06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Figure 19: Treasury Index Weight vs. 

Asset Manager Net Futures Position % of Tsy Mkt

Active NonGovernment 

Exposure 

(%NAV, Left 

Axis)

CFTC Asset 

Manager Net 

Futures ($Bn 

Face, Right 

Axis)

0

100

200

300

400

500

600

700

800

14%

16%

18%

20%

22%

24%

26%

28%

30%

15 16 17 18 19 20 21 22 23

Figure 20: eVestment Active Non-Govt Allocation

AUM Weighted Avg of 14 Large Asset Managers
Illustration of Futures Replication Costs

➢ In Figure 21 we show the cumulative performance costs from replicating the Bloomberg

Treasury Index with the 6 available Treasury futures contracts.

➢ The methodology assumes a key-rate duration hedged portfolio and subtracts the cash

return using the overnight SOFR rate.

➢ Importantly, the return shown here is not the same as a pure basis trade (long CTD,

short Treasury future), it includes the performance of the whole Treasury market.

➢ From 2018-2023, futures replication had an average annual cost of 0.45%. Most fixedincome spread products have hurdled that carry cost (Figure 23).

24

-3.0%

-2.5%

-2.0%

-1.5%

-1.0%

-0.5%

0.0%

0.5%

Apr-18

Oct-18

Apr-19

Oct-19

Apr-20

Oct-20

Apr-21

Oct-21

Apr-22

Oct-22

Apr-23

Oct-23

Figure 21: Cost of Replicating 

Bloomberg Treasury Index with 

Futures(1)

Average Annual 

Return = -0.45%

0.0%

0.1%

0.2%

0.3%

0.4%

0.5%

0.6%

0.7%

0.8%

Apr-18Oct-18Apr-19Oct-19Apr-20Oct-20Apr-21Oct-21Apr-22Oct-22Apr-23Oct-23

Figure 22: Trough to Peak 

Changes in Futures Replication 

Performance(1)

0.45%

1.00%

1.21%

3.68%

4.03%

0.0% 2.5% 5.0%

Futures Replication

Agency MBS

IG Credit

EM External Debt

HY Credit

Figure 23: Credit Spreads vs. 

Cost of Tsy Futures (2018-2023 

Avg)

(1) Data shows the presenter’s firm’s calculations as of 12/29/2023
25

Leveraged Fund Discussion
How Do Leveraged Funds Use Treasury Futures?

➢ Leveraged funds typically use futures for some of the same reasons asset managers do:

1. Taking directional views on duration and yield curve

2. Hedging and managing interest rate risk across different sectors

➢ One important difference, however, is that leveraged funds employ relative-value strategies with

greater size relative to their assets under management (more leverage).

➢ These relative-value strategies seem likely to reside mostly within the multimanager community, and

potentially within some single strategy relative-value or quantitative hedge funds.

➢ As shown in Figure 24, because of strong performance, multimanager strategies have grown faster

than the rest of the industry. With this may have come a growth in dedicated relative value AUM.

26

Strategy Typical Use of 

Futures?

Macro Directional

CTA/Momentum Directional

Risk Parity Directional

Quant Directional + RV

Relative-Value RV

Multimanager Directional + RV

Hedge Fund Strategies

Multimanager AUM 

($Bn, Right Axis)

AUM % of Hedge 

Fund Industry 

(Left Axis)

0

50

100

150

200

250

300

350

4.0%

4.5%

5.0%

5.5%

6.0%

6.5%

7.0%

7.5%

8.0%

8.5%

10 11 12 13 14 15 16 17 18 19 20 21 22

Figure 24: Growth in Multimanager AUM (1)

(1) Sourced from Goldman Sachs Research as of Dec 2022
How Do Leveraged Funds Use Treasury Futures?

➢ While asset managers have shown a net long bias in futures, the opposite is true of leveraged funds,

which have showed a persistent net short bias, despite large swings in markets.

➢ Similar to the discussion about asset managers, we think it’s unlikely that directional positions are

generating a structural bias to futures positioning recently.

➢ But large hedge funds and CTA’s are likely to have influenced shorter term positions at various times.

➢ As has been discussed extensively by regulators and market participants, it seems most likely to us

that the persistent futures short by leveraged funds reflects Treasury basis relative-value positions.

➢ As we showed on the prior slides, there is a persistent risk premium to be harvested in Treasury

futures basis. It appears that asset managers are willing to pay this premium to invest in higher

yielding products, while hedge funds earn the premium.

27

R2 = 0.92

-1000

-800

-600

-400

-200

0

200

400

-200 0 200 400 600 800 1000

Leveraged Fund Net Futures ($Bn 

Face)

Asset Manager Net Futures ($Bn Face)

Figure 25: >90% R^2 Between Asset Manager 

& Leveraged Fund Net Positions Since 2015 • Asset manager and

leveraged fund positions

track each other with a 92%

R^2 since 2015

• Logically, it makes little

sense that these two

investor categories would

take opposing directional

views with such a high

frequency

• Structural factors seem

more likely to explain this

relationship, where hedge

funds facilitate structural

futures demand by asset

managers as the Treasury

market has grown

(1) Sourced from CFTC as of Dec 2023 and the presenter’s firm’s calculations
Leveraged Funds: Returns in the Treasury Basis Trade

➢ We can estimate the returns to the basis trade using the data on the cost of futures replication:

➢ We assume a leverage ratio of 20x and show cumulative performance (excess of cash return).

➢ Anecdotally, 20x appears to be a good approximation of leverage typically used in these trades. Repo and futures margins

do permit higher leverage, however. 20x leverage could generate 9-10% annualized excess returns using this framework.

➢ March 2020 would have more than wiped out equity capital in such a strategy, explaining the stress during this period. To

the extent these strategies live inside of multimanagers, other capital may have been injected during this period.

28

20X 

Leverage

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

2018 2019 2020 2021 2022 2023

Figure 26: Cumulative Excess Returns

Treasury Index vs. Futures

Peak to 

Trough 

Drawdown

"Equity" 

Capital

-16.0%

-14.0%

-12.0%

-10.0%

-8.0%

-6.0%

-4.0%

-2.0%

0.0%

2018 2019 2020 2021 2022 2023

Figure 27: Peak to Trough Drawdown 

Using 20x Leverage Multiple

(1) Data shows the presenter’s firm’s calculations as of 12/29/2023
Leveraged Funds: Returns in the Treasury Basis Trade

➢ The performance we show is an approximation and not that of a pure basis trade (future vs. CTD).

➢ That said, it’s likely that hedge funds who implement the basis trade do so in ways that involve using

Treasuries other than CTDs, with numerous other real-world complexities to consider, including:

➢ Type of repo funding (term v. daily)

➢ CTD switch option (recall volatility in USZ3 in Fall 2023)

➢ Spot vs. deferred CTD analysis

➢ Futures roll timing, optimal delivery and wildcard option

➢ Barriers to entry given balance sheet scarcity/repo capacity

➢ Usage of cheaper off-the runs

➢ In addition to expensive implied repo, looking below, we see that futures CTDs can often trade with

negative spreads to Treasury fitted curve.

➢ Similar to “on-the-run” Treasuries, it’s likely that CTDs trade this way due to a liquidity premium vs. off-the-runs.

➢ Recalling the period of March 2020, dealers reported(1) large liquidations in off-the-run sectors from the relative-value

community, suggesting that basis implementation involves more varied expressions.

29

(12)

(10)

(8)

(6)

(4)

(2)

0

2

4

6

0 5 10 15 20 25 30

OAS (bp)

Maturity (Yrs)

Figure 28: Example Treasury OAS Curve (ex. High Coupons)

2Y

3Y

5Y

7Y

10Y

20Y

30Y

OTR

CTD

(1) See page 56 of this report https://home.treasury.gov/system/files/221/CombinedChargesforArchivesQ22021.pdf
Leveraged Funds: Estimating Size of the Basis Trade

➢ Recent research from the Fed (1) suggests that the basis trade has grown in size lately, similar to

levels seen in 2018-2019. They cite the futures data, but also show some evidence from the

sponsored repo market and collateral posting data, shown below:

➢ Another piece of research(2) released in September of 2023 quantifies the basis trade at $550bn at the end of 2022.

➢ The authors used data from form PF, and the size seems fairly consistent with size of futures exposure at the time.

➢ Bottom line, estimating size of relative-value AUM is hard especially as a large portion of capital pursuing these strategies

may be embedded in multimanager hedge-funds, where little public data on sub-strategy allocations is available.

30 (1) https://www.federalreserve.gov/econres/notes/feds-notes/recent-developments-in-hedge-funds-treasury-futures-and-repo-positions-20230830.html

(2) https://www.federalreserve.gov/econres/notes/feds-notes/hedge-fund-treasury-exposures-repo-and-margining-20230908.html
Leveraged Funds: Monitoring the Basis Trade

Some potential metrics to consider monitoring: 

31

Item Notes

Treasury Futures Open Interest Relative to the Size of Treasury Market • Disproportionate growth could indicate excessive

systemic leverage.

Size of Cleared Repo Market • Will be more valuable when all Treasury repo is

cleared in 2026.

Treasury-Futures Basis Valuations • Viewed in the context of changes to open interest,

valuations could be an important indicator.

• For example, if cash richens vs. futures and open

interest is growing, suggests position crowding.

Dealer Inventories of Treasury Securities • Supplement with real time flow color in off-the-run

trading activity.

Term structure of Repo Funding Levels • Monitor overnight vs. term repo spreads as an

indicator of funding pressures.

Changes in Margin Requirements • Monitor CME exchange margins and repo.

Concentration of Funding Sources in Bilateral Repo Market • Overreliance on single institutions could create

counterparty risk.
32

Potential Interactions Between Asset 

Managers & Levered Fund Positions
Potential Interactions to Consider

➢ Amidst record Treasury issuance, and procyclical fiscal stimulus, we conclude that a symbiotic

relationship has emerged between asset managers and hedge funds.

• Large procyclical deficits have driven Treasury weights higher in bond indices at a time when the economy is

relatively healthy and active bond managers prefer credit relative to Treasuries.

• This cyclical preference for credit, alongside the structural asset allocation of active bond managers, may be

resulting in lower cash Treasury demand and increased use of Treasury futures.

• This preference for futures vs. cash improves valuations and the investment opportunity for RV hedge funds.

➢ While the system seems stable to us now, it’s worth thinking through potential risks that might arise,

as asset managers have moved down in liquidity while hedge funds have increased leverage.

• A reduction in credit risk by asset managers would naturally facilitate unwinding the basis trade by hedge funds.

• However, if asset managers experience rapid outflows while market liquidity is impaired, these outflows could

initially be funded through Treasury sales. This type of behavior could pressure RV basis positions, and it’s possible

this dynamic was at play during March 2020 when everyone in the market scrambled for liquidity. We see below a

high tail risk correlation between Treasury-futures basis performance and 1-3y Corporate spreads. This period

likely also simply reflected extreme liquidity preference which would pressure secured vs. unsecured funding

spreads.

33

1-3Y Corporate

OAS (Left Axis)

Tsy Index Excess 

Return 15X Leverage 

Drawdown from 

Peak

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

0.25

0.75

1.25

1.75

2.25

2.75

3.25

3.75

4.25

2018 2019 2020 2021 2022 2023

Figure 30: Short Maturity Credit Spreads 

vs. Proxied Basis Trade Drawdowns

Deficit (%GDP, Right 

Axis)

U3 (Inverted, Left Axis)

-15

-13

-11

-9

-7

-5

-3

-20

-15

-10

-5

0

5

90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20 22 24

Figure 29: Trailing 1Y US Deficit (%GDP) vs. 

1Y Average Unemployment Rate

(1) Sourced from Bloomberg and the presenter’s firm’s calculations as of Dec 2023
Conclusions and Areas of Further Research

➢ The structural asset allocation preference of active fixed-income managers appears to

create a need to own Treasury futures persistently over time.

➢ Procyclical fiscal stimulus, which has contributed to rising Treasury allocations in bond

indices alongside a healthy economy, may be amplifying this trend.

➢ While there is a cost to using Treasury futures, this cost is easily hurdled by active

managers who are allocating out of Treasuries into more attractive sectors.

➢ Persistent demand for Treasury futures likely contributes to rich valuations when

compared to Treasury bonds. This valuation creates an investment opportunity for

relative-value strategies that can utilize leverage to exploit small price differences.

➢ There are a number of relationships that are worthwhile for Treasury to monitor when

tracking the Treasury futures basis trade over time. Treasury repo clearing may provide

an opportunity to gain greater insights in the coming years.

➢ Potential areas of future study could include the following:

➢ More granular research into asset manager quarterly holdings through time.

➢ More detailed analysis of the size of non-index credit and floating rate markets.

➢ Quantitative modeling of variables that seem to contribute to asset manager futures positions, including

the size of the Treasury allocation in the index, quarterly estimates of credit holdings, and empirical

duration exposure of major bond mutual funds.

➢ Greater study of potential interactions between asset manager and leveraged funds, particularly during

times of market stress and liquidity contraction.

34