The Most Crowded Short in History Is Paving the Way for a Bull Market in U.S. Bonds

marsbitPublished on 2026-01-20Last updated on 2026-01-20

Abstract

An experienced macro trader presents a contrarian thesis that 2026 will be the "year of the bond," with long-duration U.S. Treasuries (TLT/TMF) poised to outperform stocks. The core argument is built on several pillars: gold's 200% rally historically signals deflationary risk, not sustained inflation; the U.S. faces a crushing $1.2 trillion annual interest bill, creating a fiscal doom loop; Treasury issuance is dangerously short-term, amplifying refinancing risk; and long bond short interest is at extreme, crowded levels. Additional factors include cooling inflation, weak economic indicators, deflationary trade war risks, and the high probability of Fed intervention (QE/Yield Curve Control) to lower long-term yields if stress emerges. The trade offers asymmetric upside: TLT yields ~4.5% while waiting, and a 200bps drop in yields could trigger a 35-45%+ price surge, accelerated by a short squeeze. The author has allocated 60% of their portfolio to this thesis, betting on a policy and macro regime shift.

Author: Common Sense Investor (CSI)

Compiled by: Deep Tide TechFlow

Deep Tide Guide: With the dramatic changes in the macroeconomic environment in 2026, market logic is undergoing a profound shift. Veteran macro trader Common Sense Investor (CSI) presents a contrarian view: 2026 will be the year bonds outperform stocks.

Based on the U.S. government's heavy interest payment pressure, the deflationary signals released by gold, the extremely crowded bond short positions, and the imminent trade conflicts, the author believes that long-duration U.S. Treasuries (such as TLT) are at an inflection point with an "asymmetric game" advantage.

At a time when the market generally considers bonds "uninvestable," this article, through rigorous macro mathematical deduction, reveals why long bonds could become the highest-returning asset in 2026.

The main text is as follows:

Why I Am Overweight TLT and TMF — and Why Stocks Will Underperform in 2026

I do not write these words lightly: 2026 is destined to be the year bonds outperform stocks. This is not because bonds are "safe," but because macro mathematics, positioning, and policy constraints are converging in an unprecedented way—and this situation rarely ends with "Higher for Longer."

I have put my money where my mouth is.

TLT (20+ Year Treasury ETF) and TMF (3x Leveraged Long 20+ Year Treasury ETF) currently make up about 60% of my investment portfolio. This article compiles data from my recent posts, adds new macro context, and outlines a bullish scenario for long-duration bonds, especially TLT.

Core Arguments at a Glance:

  • Gold's Movement: Gold's historical performance does not signal sustained inflation—it signals deflation/deflation risk.

  • Fiscal Deficit: U.S. fiscal math is collapsing: approximately $1.2 trillion in annual interest expenses, and rising.

  • Issuance Structure: Treasury bond issuance is skewed short-term, quietly increasing systemic refinancing risk.

  • Short Squeeze: Long bonds are one of the most crowded short positions in the market.

  • Economic Indicators: Inflation data is cooling, sentiment is weak, labor market pressures are rising.

  • Geopolitics: Geopolitical and trade headlines are turning "risk-off," not "reflationary."

  • Policy Intervention: When something breaks, policy always turns to lowering long-end rates.

This combination has historically been rocket fuel for TLT.

Gold Is Not Always an Inflation Warning Bell

Whenever gold rises more than 200% in a short period, it signals not runaway inflation but economic stress, recession, and falling real rates (see Chart 1 below).

Historical experience shows:

  • The gold surge in the 1970s was followed by recession + disinflation.

  • The early 1980s surge was followed by a double-dip recession, breaking inflation.

  • The early 2000s gold rise foreshadowed the 2001 recession.

  • The 2008 breakout was followed by a deflationary shock.

Since 2020, gold has risen about 200% again. This pattern has never ended in lasting inflation.

When growth flips, gold acts more like a safe-haven asset.

U.S. Interest Expenses Are Exploding Compounded

The U.S. currently has annual interest expenses of about $1.2 trillion, roughly 4% of GDP (see Chart 2 below).

This is no longer a theoretical issue. This is real money flowing out—and interest compounds rapidly when long-term yields stay high.

This is so-called "Fiscal Dominance":

  • High rates mean higher deficits

  • Higher deficits mean more debt issuance

  • More debt issuance leads to higher term premium

  • Higher term premium leads to higher interest expenses!

This doom loop won't resolve itself with "Higher for Longer." It must be resolved through policy intervention!

The Treasury's Short-Term Trap

To ease immediate pain, the Treasury has drastically cut long-bond issuance:

  • 20/30-year bonds now make up only about 1.7% of total issuance (see Chart 3 below).

  • The rest is all pushed into short-term T-bills.

This doesn't solve the problem—it just kicks the can down the road:

  • Short-term debt constantly rolls over.

  • Refinancing will happen at future rates.

  • The market sees the risk and demands a higher term premium.

Ironically, this is why long-end yields stay high... and why they will collapse violently if growth cracks.

The Fed's Trump Card: Yield Curve Control

The Fed controls the short end, not the long end. When long-end yields:

  • Threaten economic growth

  • Trigger exploding fiscal costs

  • <极="ltr" role="presentation">Disrupt asset markets

...the Fed has historically only done two things:

  • Buy long bonds (QE)

  • Cap yields (Yield Curve Control)

They won't act preemptively. They only act after stress appears.

Historical references:

  • 2008–2014: 30-year yield fell from ~4.5% to ~2.2% → TLT surged +70%

  • 2020: 30-year yield fell from ~2.4% to ~1.2% → TLT surged +40% in under 12 months

This isn't just theory—this has happened before!

Inflation Is Cooling, Economic Cracks Appearing

Recent data shows core inflation falling back to 2021 levels (see Chart 4).

  • CPI momentum is fading.

  • Consumer confidence is at a decade low.

  • Credit stress is building.

    Labor market is starting to crack.

Markets are forward-looking. The bond market is already starting to smell this.

Extremely Crowded Short Positions

TLT's short interest is very high:

  • Approximately 144 million shares sold short.

  • Days to cover exceeds 4 days.

Crowded trades don't unwind slowly. They reverse violently—especially when the market narrative shifts.

And importantly:

"Shorts piled in AFTER the move, not before."

This is classic late-cycle behavior!

Smart Money Is Moving In

Recently, widely circulated 13F institutional holding reports showed a large fund's top quarterly additions included a significant number of TLT call options.

Regardless of who gets the credit, the message is simple: Sophisticated capital is starting to reposition for duration. Even George Soros's fund held TLT call options in the latest 13F disclosure.

Deflationary Shock from Tariff Frictions

The latest news is reinforcing the "risk-off" logic. President Trump announced new tariff threats targeting the Denmark/Greenland dispute, and European officials are now openly discussing freezing or suspending participation in the EU-US tariff agreement in response.

Trade friction will:

  • Hurt growth

  • Squeeze margins

  • Reduce demand

  • Push capital into bonds over stocks

This is not an inflationary impulse; it is a deflationary shock.

Valuation Mismatch: Stocks vs. Bonds

Today's stock pricing reflects:

  • Strong growth

  • Stable margins

  • Benign financing conditions

While bond pricing reflects:

  • Fiscal stress

  • Sticky inflation fears

  • Permanently high yields

If just one of these narratives is wrong, returns will diverge violently.

Long-duration bonds have "convexity"; stocks do not.

Upside Case Analysis for $TLT

TLT has:

  • An effective duration of ~15.5 years

  • You earn ~4.4–4.7% yield while you wait

Scenario Analysis:

  • If long-end yields fall 100 basis points (bps), TLT price return is +15–18%.

  • Fall 150 bps, TLT return is +25–30%.

  • Fall 200 bps (not extreme historically),意味着 it could surge +35–45% or more!

This doesn't include interest income, convexity bonuses, or the acceleration effect of short covering. This is why I see "asymmetric upside."

Conclusion

Honestly: After the carnage of 2022, I swore I'd never touch long bonds again. Watching duration assets get crushed was a deeply frustrating experience.

But the market doesn't care about your psychological trauma—it only cares about probabilities and prices.

When everyone agrees bonds are "uninvestable," when sentiment bottoms, when shorts pile up, when yields are high and growth risks are rising...

That's when I start buying!

  • TLT + TMF currently make up ~60% of my portfolio. I made 75% returns in the 2025 stock market and redeployed most of it into bond ETFs in November 2025.

  • I am "getting paid to wait" (earning over 4% yield).

  • My position is based on policy and growth shifts, not flimsy narratives.

2026 will finally be the "Year of the Bond."

Related Questions

QAccording to the article, why does the author believe that 2026 will be the year bonds outperform stocks?

AThe author believes 2026 will be the year bonds outperform stocks due to a convergence of macro mathematics, positioning, and policy constraints. Key reasons include the U.S. government's exploding interest expense burden, gold signaling deflationary risks, extremely crowded short positions in long bonds, cooling inflation, weakening economic indicators, and imminent policy intervention to lower long-end yields.

QWhat historical pattern does the author cite regarding gold's performance and what it signals for the economy?

AThe author cites a historical pattern where whenever gold rallies over 200% in a short period, it has not signaled runaway inflation but instead foreshadowed economic stress, recession, and falling real rates. Examples given are the 1970s (followed by recession/disinflation), early 1980s (double-dip recession), early 2000s (2001 recession), and 2008 (deflationary shock).

QWhat is 'Fiscal Dominance' as described in the article, and why is it a problem for the U.S.?

A'Fiscal Dominance' is described as a vicious cycle where high interest rates lead to higher deficits, which require more debt issuance. This increased issuance leads to a higher term premium, which in turn causes even higher interest expenses. This is a problem because the U.S. is already spending ~$1.2 trillion annually on interest, creating a compounding fiscal burden that cannot be solved by 'higher for longer' rates and necessitates policy intervention.

QHow does the extremely crowded short interest in long-term bonds (like TLT) create a potential opportunity?

AThe extremely crowded short interest in TLT (approx. 144 million shares short) creates a potential for a violent short squeeze. Crowded trades like this do not unwind slowly; they reverse sharply, especially when the market narrative shifts. This positioning provides 'rocket fuel' for a rapid price increase in long bonds as shorts are forced to cover their positions.

QWhat specific policy tools does the author suggest the Federal Reserve will use if long-end yields threaten the economy, and what historical examples are given?

AThe author suggests the Federal Reserve will use Quantitative Easing (QE - buying long bonds) and Yield Curve Control (YCC - capping yields) if long-end yields threaten growth, cause fiscal costs to explode, or disrupt asset markets. Historical examples given are from 2008-2014 (30-year yield fell from ~4.5% to ~2.2%, TLT surged +70%) and 2020 (30-year yield fell from ~2.4% to ~1.2%, TLT surged +40% in under 12 months).

Related Reads

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit11h ago

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit11h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit13h ago

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit13h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit13h ago

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit13h ago

Trading

Spot
Futures
活动图片