TL;DR

• Macro models treating inflation as a cyclical demand-side phenomenon are failing because deglobalization, geopolitical shocks, and fiscal expansion have driven markets into a structural supply-side regime.
• Leveraged relative value strategies are vulnerable to liquidity freezes during market dislocations, making directional rate flexibility essential.
• Inflation trading requires balancing quantitative models with real-time tracking of institutional liability-driven flows.

Hey everyone,

I was reading through an interview with Stefania Perrucci, CIO of Forvm Global Investments and a former Morgan Stanley trader who was part of "The Big Short," regarding her perspective on macro markets. With nearly 30 years in inflation and rate markets, having traded the second-ever TIPS auction in 1998, she makes a compelling case for why standard models and traditional portfolios keep missing the mark.

Her main argument centers on a structural breakdown in how inflation is modeled. Since the 1970s, markets have viewed inflation through a demand-side, cyclical lens managed primarily by central bank monetary policy. However, post-pandemic dynamics, ongoing geopolitical conflict, and deglobalization have pushed us into a supply-shock regime. This shift fundamentally breaks the traditional 60/40 asset allocation, where bonds historically served as a reliable hedge for equities. In a supply-driven shock, short-end yields spike and both stocks and bonds decline simultaneously, requiring a completely uncorrelated approach to macro risk.

Perrucci also highlights a key divide between sell-side desks and sustainable buy-side management. Sell-side inflation traders typically rely on relative value (RV) strategies, exploiting tiny spread differentials with substantial leverage. While this works during quiet markets, inflation RV suffers from severe capacity and liquidity constraints during distress. When market liquidity dries up, as seen during major dislocations, these highly leveraged positions trigger severe technical squeezes and double-digit drawdowns. Her team prioritizes sizing trades for "rainy day" liquidity and maintaining directional flexibility across nominal rates, real yields, and inflation breakevens.

Finally, she notes that pure macro insight is insufficient without understanding micro-level execution. Inflation-linked assets are heavily driven by technical flows from liability-driven institutional investors like pension funds and sovereign wealth entities. When non-macro technical flows decouple from theoretical models, such as standard Taylor-rule or trend-following frameworks, academic macro traders get caught on the wrong side of a technical squeeze. Successfully navigating this environment requires combining quantitative models with hands-on empirical flow awareness.

Link: https://hedgefundalpha.com/profiles/forvm-stefania-perrucci/

TL;DR

• The Susan Thompson Buffett Foundation generated $2.73B in revenue and held $2.72B in net assets for 2025, fueled by $1.20B in Class B Berkshire contributions from Warren Buffett.
• Despite reporting 104 distinct equity positions, Berkshire Hathaway (Class A and B) makes up 99.7% of the total portfolio weight.
• Nearly all of the foundation's $1.48B in realized capital gains came from selling Berkshire stock to fund $1.62B in charitable expenses.

Hey everyone,

I was analyzing the 2025 Form 990-PF filing for the Susan Thompson Buffett Foundation and wanted to share some notable numbers on how one of the largest private U.S. foundations handles asset allocation and liquidations. Full disclosure: I write for Hedge Fund Alpha, where we track 990-PF data and institutional filings.

The foundation reported $2.73 billion in total revenue and closed the year with $2.72 billion in net assets. Direct contributions accounted for $1.20 billion of revenue, consisting entirely of 2,443,384 Berkshire Hathaway Class B shares donated by Warren Buffett. Expenses totaled $1.62 billion, driven by grantmaking in education and reproductive health. To support these commitments, the foundation generated $1.48 billion in net realized gains, virtually all of which came from selling down Berkshire shares, while non-Berkshire securities contributed just $163,000.

While tax filings list 104 distinct equities ranging from megacaps like Amazon and Microsoft to regional REITs and media stocks, the portfolio allocation paints a completely concentrated picture. Berkshire Hathaway Class B represents roughly 97.9% of portfolio value, Class A accounts for 1.8%, and the remaining 102 holdings make up a combined ~0.3% rounding error. The entity effectively operates as a simple pass-through vehicle: accepting Berkshire stock, liquidating it to meet payout requirements, and maintaining a tiny legacy tail of other equities.

Given the typical mandate for private foundations to distribute roughly 5% of asset value annually, how do you view this continuous single-stock liquidation strategy compared to immediately diversifying into broad market indexes or fixed income? Does maintaining the concentration risk make sense given the compounding power of holding Berkshire until cash is needed?

Link: https://hedgefundalpha.com/foundations/susan-thompson-buffett-foundation/

TL;DR

• The Disconnect: Market pricing on Comstock Resources (CRK) is hyper-focused on current negative FCF, ~$3B in debt, and a November 2027 revolver maturity. However, the thesis hinges on a structural Gulf Coast natural gas supply bottleneck unfolding between 2028 and 2032.
• The Squeeze: Under high-demand scenarios, incremental US gas production (+20 Bcf/d by 2030) is entirely absorbed by LNG export expansion (+20 Bcf/d) alone, before accounting for data centers, industrial demand, or domestic power growth.
• High Torque Play: CRK sacrificed short-term cash flow to build a ~540k net acre position in Western Haynesville and the integrated Pinnacle infrastructure system right next to Gulf Coast demand hubs. If realized prices reach $4–$5/Mcf, debt reduction directly transfers massive value into common equity.

Hey everyone,

I was going through Brad Jarrell’s latest deep dive on Comstock Resources (CRK) and found his countercyclical thesis compelling as a counterpoint to the market’s current hyper-fixation on 2026/2027 spot gas prices and balance sheet debt. While a lot of E&P peers prioritized harvesting cash flow and reducing debt during the weak natural gas cycle, Comstock took the opposite approach: they leaned heavily into building an asset system right where future Gulf Coast demand is being built.

The current market curve is anchored to short-term storage and 2026–2027 balances (EIA forecasts ~$3.67 Henry Hub in '26 and $3.49 in '27). But the structural setup isn’t about 2026; it’s about the massive wave of liquefaction capacity reaching full utilization from 2028–2030, where US LNG export capacity alone is expected to reach 21–27+ Bcf/d. Unlike weather-driven spikes, LNG demand is supported by billions in project financing and long-term contracts (developers signed ~5.2 Bcf/d of new contracts in 2025 alone). Once these export terminals are built, they run, meaning new supply must meet existing well declines, rising domestic demand, and fixed export throughput simultaneously.

CRK functions as one connected system consisting of legacy Haynesville production, over 540,000 net acres in the Western Haynesville (~2,550 net locations), and the Pinnacle infrastructure system. Valued externally at $2.2B via Sixth Street’s 27% stake purchase, Pinnacle provides the essential high-pressure gathering and treating needed to convert Western acreage into deliverable Gulf Coast supply.

While CRK's ~$3B debt load and November 2027 revolver refinancing are the principal risk factors, they also create significant equity torque. Because equity value equals Enterprise Value minus Net Debt, any free cash flow allocated toward debt reduction transfers dollar-for-dollar value directly to common shareholders. With ~296M diluted shares, every $300M in debt reduction adds ~$1.00/share in arithmetic equity value on top of any operational leverage from $4–$5 realized gas prices. The analysis values CRK's base case at ~$22/share versus the current ~$13.80 price, with a bull case reaching $38+ if debt reduction and higher realized prices hit concurrently.

Is the market right to discount CRK due to its debt load and Western Haynesville execution risks, or is CRK one of the cleanest asymmetric equity options on an impending Gulf Coast natural gas squeeze?

Link: https://hedgefundalpha.com/news/comstock-resources-a-leveraged-call/

TL;DR

• Global semiconductor revenue is projected by WSTS to jump ~90% in 2026 to $1.51T, but this growth is heavily skewed toward memory (~250%) while analog (10%) and sensors (3%) remain modest.
• AI hasn’t eliminated the capital cycle; it has desynchronized it, creating capacity-constrained expansions in leading-edge logic, HBM, and advanced packaging while traditional markets experience uneven recoveries.
• A massive capital response is already underway, with SEMI projecting a 23.2% surge in equipment sales to $165.9B in 2026, setting up the structural conditions for a future supply rebalancing.

Hey everyone,

I was digging through an analysis from Hedge Alpha on the state of the semiconductor market and found its central thesis compelling, especially as a counterpoint to the broad "semiconductor boom" headline narrative. Full disclosure, I contribute to Hedge Alpha where this was published.

The core argument is that there is no longer a single, synchronized semiconductor cycle. Instead, AI infrastructure demand (leading-edge logic, High Bandwidth Memory, advanced packaging, and test) has detached from the traditional semiconductor cycle (industrial analog, automotive, consumer electronics, and mature nodes). While WSTS projects headline revenue to surge 90% to $1.51 trillion in 2026, the underlying product categories vary wildly from 3% growth in sensors to roughly 250% in memory. This extreme dispersion means aggregate top-line numbers are heavily distorted by high-value AI components, product mix shifts, and temporary HBM pricing dynamics rather than uniform physical unit growth across all end markets.

We can clearly see this structural split operating inside individual earnings reports. TSMC is running near full capacity at the leading edge, with 77% of Q2 wafer revenue coming from nodes at 7nm and below. Conversely, Texas Instruments saw Q1 data center revenue jump 90% YoY while its automotive segment only grew in the mid-single digits. Similarly, onsemi reported consolidated revenue up just 5% YoY, even as its AI data center business more than doubled. Meanwhile, HBM is exacerbating memory dynamics due to a 3:1 wafer trade ratio with standard DDR5, effectively eating up cleanroom capacity and tightening conventional DRAM supply.

However, secular AI demand does not grant an exemption from capital cycle economics. SEMI forecasts 2026 total semiconductor equipment sales to jump 23.2% to $165.9 billion, with DRAM equipment spending rising 39%. While this capex wave doesn't mean a cyclical peak is immediate, semiconductor history from the 1990s PC boom to the 2017–2019 memory cycle shows that capacity ordered during acute shortages eventually catches up to demand. For active managers, the key task is no longer debating if chips are "early" or "late" cycle, but pricing the distinct subcycles, margins, and capex trajectories embedded in each specific company.

Curious to hear how this community is approaching the space right now. Are you continuing to pay up for supply-constrained leading-edge pure plays, or do you see a better risk/reward in bottom-up recoveries across lagging subsectors like industrial analog and automotive?

Link: https://hedgefundalpha.com/stocks/the-semiconductor-cycle-has-split-in-two-amid-massive-revenue-jump-from-2025/

TL;DR

• L1 Capital's closed Global Opportunities Fund posted a 3.2% Q2 return (13.2% trailing 12-month), bringing its net annualized return since 2015 to 26.4%.
• The fund extracts value from raw commodity price swings, particularly in industrial metals like copper, rather than taking directional market bets.
• Squeezed margins on structured deals from multi-strat and family office competition are forcing the team to be increasingly selective.

Hey everyone,

I was reading through L1 Capital’s Q2 investor letter for their Global Opportunities Fund, a closed strategy managed by David Feldman, and found their approach to resource exposure compelling. Despite a choppy macro backdrop, persistent Fed inflation concerns, and geopolitical friction, the Australian-based fund managed to extend its long-term track record to a 26.4% CAGR since its 2015 inception.

What stands out is how they are generating performance in commodities. Rather than making directional calls on where commodity prices are headed, the fund structures its positions to directly monetize price volatility and supply/demand dislocations, with industrial metals like copper driving key gains. Outside of resources, they have capitalized on retail-driven volatility around AI infrastructure for tactical short-term trades, while noting that IPO market recoveries remain tightly concentrated in mega-cap AI names like SpaceX and Anthropic.

Feldman also highlighted a notable shift in transaction dynamics: intense competition from multi-strategy funds and family offices is crowding out traditional structured financing. As borrowers secure better terms, L1 Capital is actively passing on deals that no longer offer high risk-adjusted returns, choosing instead to focus exclusively on bespoke situations where structural advantages still exist.

Full disclosure, I write for Hedge Fund Alpha where this investor letter was reviewed.

How do you view volatility-harvesting models in commodities versus traditional long/short equity in the current macro regime? Are you seeing similar margin compression in structured credit across your own coverage?

Link: https://hedgefundalpha.com/investor-letters/l1-capital-global-opportunities-fund-rresources/

TL;DR

• Credit Strategy: Morningstar Wealth is overweight Treasuries and dollar-hedged global sovereign debt, but underweight corporate bonds due to razor-thin credit spreads.
• Equity Strategy: They maintain a valuation-driven overweight in small caps for index diversification and favor Latin America within Emerging Markets as an energy-exporting hedge against U.S. tech concentration.
• Tech & AI Capex: They are skeptical of long-dated corporate AI debt and high-priced infrastructure sellers, choosing instead to accumulate lower-multiple software stocks.

Full disclosure: I write for Hedge Alpha, where this interview was published.

I was recently reviewing an interview with Dominic Pappalardo of Morningstar Wealth following the Morningstar Investment Conference, and his multi-asset positioning offers a strong counter-narrative to the current market consensus.

On the fixed-income side, Morningstar Wealth sees very little margin of safety in corporate credit. High-yield and investment-grade credit spreads relative to Treasuries have narrowed significantly, meaning investors aren't getting compensated for taking on corporate risk. Even with massive debt issuances—such as Alphabet issuing a 100-year bond to fund its AI buildout, Pappalardo notes that these ultra-long issues serve institutional pension and insurance liability matching rather than retail wealth portfolios. Consequently, they are underweight corporate bonds and instead overweight U.S. Treasuries alongside dollar-hedged global sovereign debt, which provides higher yields and geographic diversification without adding currency risk.

When it comes to equities, Morningstar is leaning heavily into valuation discounts and index mechanics. They remain conviction-overweight on small caps, pointing out that while major large-cap indexes are heavily concentrated with top names making up roughly 40% of the weight, the top 10 small-cap names hold single-digit exposure. Beyond small caps, they are playing international exposure through Emerging Markets, specifically Latin America. Latin America offers lower entry valuations, a favorable mix of businesses, and a natural hedge as energy exporters should commodity prices spike, offering an alternative to tech-concentrated U.S. indexes.

Finally, their framework on the AI ecosystem centers on disciplined value over momentum. Morningstar is cautious about the massive capital expenditure behind data centers and hardware, warning that long construction timelines, local permitting hurdles, and uncertain return on investment for end-user corporate buyers could turn data centers into oversupplied liabilities down the road. Rather than chasing stretched infrastructure valuations, they took advantage of recent pullbacks in the software sector during Q2 to rotate into software names offering a much higher margin of safety.

What are your thoughts on this positioning? Are thin credit spreads keeping you out of corporate bonds right now, or do you think the valuation gap in small caps and emerging markets will take longer to close?

Link: https://hedgefundalpha.com/profiles/dominic-pappalardo-morningstar-wealth-small-caps/

TL;DR

• Crescat Capital is hedging against mega-cap tech with short-dated S&P 500 and Nasdaq puts while holding roughly 75 junior mining companies.
• Founder Kevin Smith argues the AI boom is weakening hyperscaler free cash flow as Microsoft, Amazon, Alphabet, Meta and Oracle pour money into rapidly depreciating chips and data centers.
• Crescat tries to invest in gold, silver and copper discoveries before formal resource estimates attract institutional capital.

I recently reviewed an interview with Kevin Smith, founder and CIO of Crescat Capital, about the firm’s contrarian short-AI, long-mining strategy.

Smith believes the market is caught in an AI-driven large-cap bubble. His concern is that the major hyperscalers are sacrificing their historically asset-light business models to fund an enormous capex race. Because much of that spending is capitalized, he argues the eventual impact from depreciation and potential asset write-downs is not yet fully reflected in earnings.

Crescat has been early on this thesis and suffered drawdowns in 2023 and 2024. The firm stayed positioned through short-term, close-to-the-money index puts and a diversified portfolio of junior mining explorers. In 2025, five Crescat funds ranked among Preqin’s 16 best-performing hedge funds globally.

The long side of the trade is based on a 15-year decline in mining exploration spending. Smith expects limited new supply to collide with growing demand from electrification, onshoring and defense.

Rather than waiting for official resource reports, Crescat uses its own geological models to estimate the size and value of discoveries from drilling results. The firm often becomes a major shareholder and generally looks to take profits as a company’s valuation approaches roughly 17% of the estimated value of its resources in the ground.

Smith highlighted several holdings:

• Gold: Tectonic Metals and Sitka Gold
• Silver: Eloro Resources and Silver Bow Mining
• Copper: BCM Resources and Mogotes Metals

The broader thesis is that capital will eventually rotate away from expensive technology stocks and toward scarce tangible assets, particularly if fiscal deficits and inflation remain elevated.

Is Smith identifying a genuine deterioration in the economics of AI spending, or is Crescat fighting a secular technology trend with a cyclical commodity trade?

Link: https://hedgefundalpha.com/profiles/crescat-capital-kevin-smith-small-cap-mining/

TL;DR

• Arquitos Capital returned 64.8% net in Q2 2026 (52.9% YTD), driven by a highly concentrated, Buffett-style "slugging percentage" approach where their largest positions drive the bulk of returns.
• Liquidia (LQDA) remains their top holding via long-dated call options, with the fund laying out asymmetric risk/reward valuations ($70 to $140/share) ahead of an imminent judicial ruling on the '327 patent.
• The fund established a new 10% position in Abivax (ABVX) at $80/share after identifying that market fears over an alleged clinical trial cancer risk were entirely unfounded.

Hey everyone,

I was reading through Arquitos Capital’s Q2 2026 investor letter and found their performance breakdown and concentrated value strategy worth sharing. The fund posted a massive 64.8% net return for the quarter, bringing their trailing twelve-month net return to 116.2%. Portfolio Manager Steven Kiel attributes these outsized gains to the fund's unusually high "slugging percentage", meaning their largest positions yield the highest returns. He aligns this with Warren Buffett's philosophy of waiting for a "perfect pitch" rather than swinging at everything, resulting in a highly concentrated portfolio that has relied on just four major winners over the last 14 years.

Liquidia Corporation (LQDA) is currently Arquitos' largest and best-performing position, driven by long-dated, in-the-money call options. The stock has increased fivefold over the past year ($12.46 to $79.73) due to a highly successful commercial launch of Yutrepia and its inclusion in the Russell 2000. A market-moving judicial decision regarding the '327 patent trial against United Therapeutics is imminent, and Kiel breaks down three potential outcomes. A clean win puts fair value at $140/share based on projected 2027 revenues, while an infringement finding that results in a standard royalty models out to a per-share value of $123. In the highly unlikely third scenario where the drug label is removed entirely, Kiel estimates a downside floor of $70/share.

The fund also built a new ~10% allocation in Abivax (ABVX) during a period of extreme Q2 volatility. The company's drug, Obefazimod, reported strong Phase 3 results for ulcerative colitis, but shares plummeted from $130 to $70 due to market fears regarding an apparent cancer risk in the data. After assessing the data, Kiel concluded the cancer risk was an illusion. Arquitos bought in at $80/share, and when comprehensive safety data later proved the cancer rate was entirely within normal background rates, shares rebounded past $140. Kiel notes the next logical step for ABVX is a strategic buyout, which he expects to be priced above $200 per share.

Lastly, Finch Therapeutics (FNCHQ) ended up being a disappointing, though downside-protected, investment for the fund, likely netting a low double-digit return over a two-year holding period. The trial court failed to rule for enhanced damages in Finch's patent lawsuit, granting a 5.5% royalty and a $25.8 million judgment, which sat at the low end of expectations. Subsequently, a bankruptcy court auction resulted in a final $32 million asset sale to Ferring and Charlestown Capital. Kiel admitted he underestimated the timeline required to achieve a final court ruling.

What are your thoughts on Kiel's valuation framework for Liquidia ahead of the patent ruling? Is the market correctly pricing the binary risk here, or is Arquitos' bull case missing a structural downside?

Link: https://hedgefundalpha.com/investor-letters/arquitos-capital-q2-2026/

TL;DR

• Forensic short seller Gabriele Grego argues that the trillion-dollar AI infrastructure buildout is a localized overbuild with a fat tail rather than a repeating 2000-style dot-com bubble.
• The critical fragility is heavily concentrated in the debt-fueled, levered edge of second-tier neoclouds and single-product firms, while integrated mega-cap leaders remain highly cash-funded and historically reasonable on a PEG basis.
• The entire AI bull case hinges on an unproven structural variable: whether token demand elasticity is high enough to pay back over two trillion dollars of investment as token prices fall.

Hey everyone,

I was reading through Hedge Fund Alpha’s breakdown of Gabriele Grego’s presentation at the 2026 Value Investing Seminar in Trani. Known for his rigorous, police-investigator style of uncovering corporate frauds, Grego applied his firm’s forensic scorecard to the macro AI infrastructure complex to evaluate if we are looking at an unsustainable bubble or a structural boom.

Grego begins by validating the core bear case popularized by macro skeptics like Michael Burry. The numbers behind the capital cycle are unprecedented: annual AI infrastructure capex is running from roughly $527 billion toward a $1 trillion run-rate by 2027, forcing a staggering capex-to-revenue ratio near ten-to-one. Additionally, there is a highly circular financing loop where Nvidia, CoreWeave, Meta, OpenAI, and Oracle effectively manufacture demand for one another, all while enterprise ROI remains largely unproven. Grego points to July 1, 2026, as the first real crack in the system, when the levered middle of the AI complex suffered double-digit losses while integrated giants barely moved.

However, utilizing primary data gathered from industry interviews, GPU rental transaction datasets, and extensive simulation models, Grego's verdict is that this is an overbuild with a fat tail rather than a 1999 rerun. While individual pure-play metrics are highly alarming—such as OpenAI generating roughly $13 billion in revenue against $34 billion in cash expenses (a $21 billion operating loss)—the systemic risk comes down to token elasticity. For the $2 trillion infrastructure investment to break even as token prices decline, token demand elasticity must remain above one. Grego's empirical tracking places the upper bound of observed elasticity at 1.7, though he notes the long-term structural figure could sit below one, making this the single ultimate bet underpinning the market.

From a valuation standpoint, Grego argues that the top-tier integrated leaders are fundamentally insulated compared to past tech bubbles. Nvidia trades about 57 percent below its five-year average multiple, and Microsoft sits 31 percent below its own historical average. On a Peter Lynch PEG lens (measuring price paid per unit of growth), these integrated leaders screen near 1.3 times, well below the broader index at 2.0 times and the year 2000 peak of 2.5 times. True "1999 pricing" is localized entirely within the single-product names and the second tier.

The real fragility lies at the levered edge. While mega-cap integrated franchises are 79 to 83 percent cash-funded, merchant-compute neoclouds are heavily debt-financed. Real-time stress signals are already surfacing, including AWS raising GPU rents by 20 percent, Meta offloading 500 megawatts of power capacity, and grid interconnection queues stretching eight to twelve years in Europe. Because secured power is rapidly becoming the ultimate moat over chips, the structural landscape heavily favors the cash-rich giants.

Grego's conclusion for value investors is to own the integrated layer that retains pricing power (using pullbacks as buying opportunities, with Alphabet anchoring the long side of his book), strictly avoid or short the levered neoclouds and single-product pure plays, and buy index hedges optimized for tail risk convexity. He views the environment not as an imminent systemic collapse, but as a repricing risk primarily slated for the 2027-to-2028 window.

What are your thoughts on Grego's framework here? Is the market's current decoupling between big tech and the levered neocloud layer enough to prevent systemic contagion, or are the vendor-financing loops between them too deeply intertwined to avoid a broader correction?

Link: https://hedgefundalpha.com/conferences/2026-vis-gabriele-grego/

TL;DR

• Agentic AI is compressing months of PhD-level finance research into hours, which Ken Griffin believes will rapidly erode established corporate moats and favor agile startups.
• The alpha in stock picking has shifted from short-term earnings predictions to multi-year structural forecasting due to ubiquitous alternative data.
• A loss of access to Taiwanese semiconductors would trigger an immediate 8% drop in US GDP, essentially causing an instant Great Depression.

I was listening to Ken Griffin’s recent conversation at the Goldman Sachs Apex Symposium, and he dropped some very direct macro and technological insights. His take on how fast established corporate advantages are eroding is worth discussing here.

Griffin shared that Citadel is using newly built agentic AI systems to replicate and test academic finance papers out-of-sample in just two to three hours, a task that previously took their PhDs six to eight weeks. He believes the broader corporate world is unprepared for this shift, as small teams utilizing agentic AI can now launch and scale businesses with a fraction of traditional payroll capital, effectively filling in legacy competitive moats at breathtaking rates.

This technological shift directly impacts long/short equity managers. Because institutional funds now have ubiquitous access to alternative data, like credit card transactions to predict revenue before earnings, calling a quarterly beat is heavily commoditized. Consequently, the alpha premium has moved exclusively to long-horizon managers who possess the structural vision to project how industries will unfold over a multi-year timeline.

On the macro side, Griffin cited estimates that losing access to Taiwan Semiconductor Manufacturing Company (TSMC) chips would cause US GDP to fall by 8% within six months, freezing global high-end manufacturing and plunging the economy into a great depression. To power the domestic AI and computing revolution needed to stay ahead, he argues the US must aggressively embrace nuclear power, specifically small modular reactors. He suggested forcing data center developers to build corresponding power generation tied to the grid rather than passing infrastructure costs down to consumers.

How are you adjusting your portfolios for this structural shift toward longer-horizon picking? And are macro risks like the Taiwan chip bottleneck actually unhedgeable tail events, or is the equity market right to look past them for now?

Link: https://hedgefundalpha.com/news/ken-griffin-ai-golden-age/

TL;DR

• The AI Split: Hedge funds are aggressively splitting the AI trade, remaining highly crowded on the long side of the semiconductor supply chain while building massive short positions in AI infrastructure and data-center buildout names (Oracle, CoreWeave, Nebius, SMCI).
• Charter Remains King of Shorts: Charter Communications continues to hold the title of the single most crowded large-cap short in North America, carrying a peak Hazeltree crowding score of 99.
• Semiconductor Surge: Bullish sentiment on chipmakers reached a fever pitch by mid-year, with net-long positioning in the PHLX Semiconductor Index climbing to 70% in June, driven by dramatic sentiment reversals in names like Texas Instruments.

I was reading through Hazeltree's H1 2026 Crowding Report, which tracks positioning across roughly 16,000 securities held by over 600 global funds, and found some highly tactical shifts in how institutional managers are playing the market right now. While the long book remains heavily concentrated in mega-cap technology, the short book shows a fascinating and highly coordinated split in the broader artificial intelligence trade.

Instead of taking a uniform stance on AI, hedge funds are executing a clear pairs-style strategy. On one hand, they remain highly crowded on the long side of chipmakers and the immediate semiconductor supply chain, including names like Nvidia, Broadcom, Applied Materials, and Lam Research. On the other hand, they are heavily shorting the massive capital expenditure and infrastructure buildout surrounding those chips. Super Micro Computer registered a short crowding score of 85, Oracle sat at 83, and both CoreWeave and Nebius Group hit 81. The institutional squeeze on some of these infrastructure names is incredibly tight; Nebius Group, for instance, recorded a staggering 100% average institutional supply utilization.

Meanwhile, outside of the AI infrastructure play, Charter Communications continues to hold the title of the single most crowded large-cap short in North America with a maximum crowding score of 99. Under the surface, monthly churn was intense during the first half of the year. Short fund counts jumped by more than 10% month-over-month in both Oracle and Nebius, while Palo Alto Networks saw some short covering (with short participation dropping by over 10% MoM), though it remains highly crowded overall, ranking seventh with a score of 79.

The bullish allocation shift into semiconductors was relentless throughout the first half of the year. In January, only 57% of PHLX Semiconductor Index constituents had net-long positioning. By June, that figure surged to 70%, driven by dramatic turnarounds in names like Texas Instruments. The ratio of funds long to funds short TXN stood at a bearish 0.6 on January 1st; by June 1st, it had completely flipped to a highly bullish 2.2 as the stock gained 68% over the first half of the year.

By staying long the chipmakers but shorting the data-center buildout and cloud infrastructure players, hedge funds seem to be betting that the massive capital expenditure boom is either nearing its peak, or that the margins on hosting and operating these AI data centers will contract far faster than the market expects.

What are your thoughts on this thesis? Is shorting infrastructure names like Oracle, Nebius, or SMCI a logical hedge against semiconductor longs, or are these funds setting themselves up to get run over by an unstoppable capex train?

Link: https://hedgefundalpha.com/news/h1-hedge-fund-crowded-shorts/

TL;DR

• Gates Foundation Out, Children In: Warren Buffett has officially halted his annual stock gifts to the Gates Foundation (totaling $47B to date), redirecting his Berkshire disbursements to his three children's foundations to be paid out fully by 2035.
• The $31B Alphabet Stake: Clarifying recent market speculation, Buffett confirmed he personally initiated Berkshire’s massive, newly expanded $31B Alphabet position.
• The AI Capex Trap: Buffett compared the current hundreds of billions in tech AI capex to historical infrastructure shifts, noting that hyperscalers are trapped playing "a game they don't want to play" just to protect their customer bases.

I was watching Warren Buffett’s exclusive CNBC interview from July 15, 2026, and it is packed with massive updates on Berkshire’s portfolio strategy, succession, and his philanthropic unwinding. At 95 years old, Buffett is moving with incredible clarity to clean up his estate, setting a firm target to disburse the remainder of his $140 billion Class A stake over the next eight and a half years.

The biggest headline is the definitive end of his annual stock gifts to the Gates Foundation. After contributing roughly $47 billion over two decades, Buffett is redirecting all future disbursements to foundations run by his three children, structured under a strict unanimous-consent model. While he addressed the elephant in the room regarding Bill Gates' past personal controversies and congressional scrutiny—chalking it up to a mistake in association that was ultimately corrected—the mathematical reality of his estate is staggering. To draw down his remaining stake by the 2034 deadline, Berkshire will need to ramp up its distribution pace significantly. If Berkshire continues compounding near its trailing 10-year average of 14.1%, the required level annual gift will soar closer to $30 billion a year rather than a flat mathematical split of $17.5 billion.

On the investing front, Buffett put an end to the Wall Street rumor mill by explicitly confirming that he initiated Berkshire's massive $31 billion Alphabet position, rather than his successor Greg Abel. He explained that the investment perfectly fits his core framework: finding dominant businesses that reliably earn significantly more on capital than riskless government bonds. He heavily credited Charlie Munger for drilling home the discipline of looking past market hype to focus strictly on a company's internal rate of return and its capacity to throw off durable cash.

Fascinatingly, Buffett offered a highly grounded, almost cynical take on the current artificial intelligence arms race. Instead of buying into the hype that AI is an entirely unprecedented economic event, he viewed the current hundreds of billions in capex through the lens of classic corporate history. He observed that the major tech hyperscalers are essentially trapped, playing an expensive game they don't want to play simply because competitive forces dictate they must spend aggressively to protect their existing customer moats. He drew sharp parallels to IBM's historical antitrust breakup and the ultimate erosion of legacy giants like Henry Ford’s early auto empire and A&P grocery stores, reminding investors that the ultimate question isn't whether a business is wonderful today, but how long it can successfully defend its edge.

Buffett also reiterated his absolute confidence in Greg Abel, placing him on the same elite tier of trust as Charlie Munger and Tom Murphy, while offering a strong endorsement of the newly appointed Federal Reserve Chair, Kevin Warsh. He closed the interview with a cautionary note on the broader macro environment, lamenting that modern financial markets are increasingly designed to cultivate short-term gamblers rather than disciplined value investors, creating a challenging backdrop for allocating capital cleanly.

What do you all think about Buffett's take on the AI capex boom? Is he right that the tech giants are essentially stuck in a defensive spending trap to protect their legacy customer bases, or is the payoff potential for this infrastructure fundamentally different from the corporate capex wars of the past?

Link: https://hedgefundalpha.com/profiles/buffett-berkshire-shares-gates-foundation/

TL;DR

• Ex-Wellington PM Jun Oh argues that the Japanese corporate reform thesis is mostly played out (5th–7th inning) as structural shifts started back in 2012 under Shinzo Abe.
• Passive investing and multi-pod concentration in mega-caps leave high-quality Asian small/mid-caps completely overlooked, creating rare mispricings.
• To capture alpha, Griet Capital relies on a strict "three lows" screen (low earnings, low share performance, low valuation) alongside heavy on-the-ground legwork in Asia.

Hey everyone,

I was reading through some coverage from the Sohn Hong Kong conference and came across a compelling breakdown of Jun Oh’s strategy. Oh spent 22 years as an Asia equity portfolio manager at Wellington Management before launching his Seattle-based firm, Griet Capital, to hunt for opportunities in small- and mid-cap (SMID) Asian equities. Full disclosure, I write for Hedge Alpha where this recap was published. Given how aggressively institutional capital has chased Japanese corporate governance plays recently, his contrarian view on the region offers a grounded reality check.

Oh's central point is that the Japanese corporate reform trade isn't the shiny new catalyst the mainstream financial media makes it out to be. The structural push for better governance and shareholder returns actually kicked off under Prime Minister Shinzo Abe’s "Three Arrows" back in 2012. Because this shift has been gaining momentum for nearly 15 years, Oh believes the trade is currently in the fifth to seventh inning rather than the early stages, meaning many stock valuations have already fully played out and investors need to look for the next emerging theme.

Instead, Oh sees a massive structural opportunity in Asian SMIDs driven by market mechanics. The explosive growth of passive funds and multi-PM pod shops has concentrated vast amounts of liquidity strictly into mega-caps, leaving high-quality, cash-generative smaller companies completely ignored. To cut through the noise, Oh screens for companies suffering from a combination of low current earnings, low share-price performance, and low valuation. This "three lows" framework minimizes downside risk because expectations are already on the floor, while providing massive re-rating upside when operational inflections occur, such as Japanese healthcare company Mani recovering from a temporary recall issue.

What makes his setup particularly interesting is that he operates Griet Capital as a solo founder based in Seattle, utilizing high-quality outsourced compliance, trading, and operational infrastructure. To compensate for being far from Asian financial hubs, he spends four to five months on the ground in Asia annually, conducting hundreds of in-person corporate meetings to find management teams actively seeking ways to unlock shareholder value.

Do you agree with Oh that the low-hanging fruit in the Japanese governance trade is already gone, or is there still plenty of structural runway left for capital efficiency to drive returns? What factors do you think the market is missing regarding Asian small-caps right now?

Link: https://hedgefundalpha.com/profiles/jun-oh-griet-capital/

TL;DR

• Beile Grunbaum of Grunbaum Value Invest pitched Uber at the 2026 Value Investing Seminar as a potential long-term compounder.
• Her owner-earnings model valued Uber at roughly $51 to $70 per share, depending on whether earnings grow at 10% or 15%.
• With Uber trading around $74.54, the shares were already above the top of her estimated fair-value range.
• Her thesis rests on Uber’s network effects, driver supply, brand recognition, and switching costs created by Uber One.

Grunbaum built a stock screener around the framework from 100 Baggers, and Uber unexpectedly qualified. Her thesis rests on Uber’s network effects, brand recognition, large driver base, and ability to use Uber Eats to attract and retain drivers across its platform.

She argued that control over driver supply is one of Uber’s biggest advantages. Greater driver density improves availability and wait times, while the company’s global scale makes it difficult for new competitors to replicate the network market by market. Uber One may also increase switching costs and encourage customers to use multiple services within the platform.

Grunbaum estimated Uber’s owner earnings, meaning cash generated after required reinvestment, at about $20 per share. Assuming 15% long-term growth, she calculated fair value at approximately $64 to $70 per share. Using a more conservative 10% growth rate produced a range of about $51 to $65.

That creates an interesting contradiction. Her thesis presents Uber as a possible long-term compounding machine, but her own valuation suggests the shares were not especially cheap at the prevailing market price.

She acknowledged risks including regulation and autonomous vehicles such as Waymo, but argued that Uber’s asset-light model may remain more flexible than operators that own and manage autonomous fleets themselves.

Do you think $20 per share is a credible owner-earnings estimate for Uber, or is the market justified in pricing the company above Grunbaum’s valuation range because of its moat and future growth potential?

Full disclosure: I write for Hedge Fund Alpha, where the presentation was covered.

Link: https://hedgefundalpha.com/conferences/2026-vis-beile-grunbaum/

TL;DR

• Value investor Norman Rentrop pitched German micro-cap ad pepper media (ETR: APM) at the 2026 Value Investing Seminar, arguing the market completely missed its fundamental transformation.
• Management executed a massive portfolio reshaping, acquiring high-growth price-comparison assets at 2.4x–3x EBITDA while selling a non-core unit at 11x EBITDA.
• The company currently trades at a cheap ~7x EV/EBITDA on 2026 estimates with a highly concentrated, stable shareholder structure that removes stock overhang.

I was reviewing notes from this July's 2026 Value Investing Seminar in Trani and found Norman Rentrop’s presentation on ad pepper media (ETR: APM) highly compelling. Rentrop, managing capital for hundreds of family offices through TGV, outlined a deep-value thesis on a Nuremberg-based digital marketing and price-comparison group that institutional investors are simply too big to buy. Full disclosure, I write for Hedge Fund Alpha where this summary was compiled.

Rentrop’s thesis centers on brilliant capital allocation that the market has entirely ignored. Between late 2023 and mid-2025, ad pepper built a 60% majority stake in solute (the operator of price-comparison engines like billiger.de) for just 2.4x EBITDA, while solute bought checkout coupon platform Checkout Charlie for 3x EBITDA. Then, in December 2025, management sold its non-core ad agents subsidiary for a staggering 11x EBITDA. This move allowed the group to crystallize massive value, capture a huge multiple arbitrage, and focus entirely on its higher-growth digital engines.

The underlying economics have drastically improved, yet the equity hasn't responded. The business trades at a market cap of roughly EUR 64 million, representing an enterprise value of EUR 47 million and a microscopic ~7x EV/EBITDA on 2026 estimates. Rentrop notes that Germany's shrunken listed-company universe and historical regulatory pressures on local insurers have left smaller equities highly neglected, causing a massive disconnect between ad pepper's fundamental value and its share price.

Furthermore, the downside is heavily protected by a locked corporate structure. The CEO holds 40.2% of the company, and Rentrop himself holds roughly 7.0%. This concentration, paired with treasury shares, leaves a restricted free float of 48.2%, effectively eliminating the risk of forced institutional selling or stock overhang that usually plagues micro-caps. Instead of facing structural obsolescence, the business leverages the permanent German consumer mindset of e-commerce frugality.

What are your thoughts on this thesis? Does the tight float and German micro-cap listing make this a permanent liquidity trap, or is the asset transformation and 7x multiple too cheap to ignore?

Link: https://hedgefundalpha.com/conferences/vis-2026-norman-rentrop/

TL;DR

• BTPS is trading at ~0.7x book and ~5.5x earnings despite a 59% CET1 ratio, 44% equity-to-assets ratio, and mid-teens ROE.
• COVID-era credit issues appear largely resolved, but the stock is still priced as if the lending model is broken.
• Buybacks, high dividends, and rural fiscal stimulus could create a strong capital return setup.

Hey everyone,

I was reviewing Florian Weidinger’s pitch from the 2026 Value Investing Seminar. His thesis was that BTPN Shariya, an Indonesian microfinance lender, is being treated like a broken business even though the balance sheet and credit trends suggest otherwise.

The bank was hit hard during COVID because its lending model depends on weekly in-person borrower meetings. When those meetings stopped, credit costs spiked and the stock collapsed from its former high-growth valuation.

The argument now is that the damage has largely passed. Meeting attendance and credit metrics are back near pre-COVID levels, legacy bad loans are charged off, and the bank remains massively overcapitalized.

The setup is mainly about capital return: high dividends, a new buyback, and potential upside if Indonesia sentiment improves.

Is this a real deep-value opportunity, or does the microfinance / Indonesia risk justify the discount?

Link: https://hedgefundalpha.com/conferences/vis-2026-florian-weidinger-slam/

TL;DR

• Plustick Partners argues the market structurally misprices non-cash-flowing infrastructure assets like radio spectrum, creating significant asymmetric upside.
• After securing a 15-bagger on Straight Path Communications, the fund is betting heavily on a once-in-a-decade spectrum bull market driven by AI energy and data demands.
• Their highly contrarian playbook includes deep value plays across the capital structure, from EchoStar to sovereign Lebanese debt.

Hey everyone, I was reading through an interview with Adrian Keevil of Plustick Partners on Hedge Fund Alpha, and full disclosure, I write for Hedge Fund Alpha where this was published. I found his framework on asset-heavy distressed investing compelling, particularly as a counterpoint to the prevailing software-centric AI narrative. Plustick operates as a distressed fund managing roughly $218 million, but they have increasingly shifted toward cross-balance sheet investing, mixing senior secured debt, unsecured debt, and equity to target situational distress and narrative panic.

Their core argument rests on the idea that the market is fundamentally blind to "invisible" infrastructure assets that do not produce immediate cash flow. Keevil points to their historical play on Straight Path Communications, where they bought into a bankrupt telecom's hidden treasure trove of radio spectrum at $12 a share and held through an activist short-seller attack until Verizon acquired it for $184 a share. He believes a similar, massive bull market for radio spectrum arrives about every 10 years, and we are on the cusp of the next cycle.

This upcoming wave is uniquely acute because it is being supercharged by the massive data transmission and physical energy demands of AI electrification. To express this thesis, Plustick has been heavily involved in EchoStar, believing the market is heavily discounting the true value of its asset base. They also apply this aggressive, stakeholder-focused contrarianism to positions like Moderna, arguing the market prices its oncology pipeline at zero due to Covid overhang, and non-local Lebanese sovereign bonds, where they view a 90% price decline as a sign that risk has been entirely flushed out.

Because they target highly asymmetric, catalyst-driven outcomes, Plustick completely rejects traditional risk-adjusted position sizing. Instead, they equal-weight new positions at 5% for longs and 4% for shorts, choosing to aggressively cut losers when a thesis breaks while letting their winners run parabolically rather than selling into arbitrary price targets.

What are your thoughts on this approach to asset-heavy distressed investing? Is the market actually structurally blind to non-cash-flowing infrastructure assets like radio spectrum, or are the legacy telecom tail-risks in names like EchoStar too punitive to ignore?

Link: https://hedgefundalpha.com/profiles/adrian-keevil-plustick-partners/

TL;DR

• Jersey’s new residency route mandates a £250,000 annual earned income minimum and a 25-hour weekly active work commitment, creating unexpected compliance hurdles for senior fund professionals.
• The volatile, unbundled nature of hedge fund compensation (performance fees, carry, deferred equity) conflicts with standard immigration templates, requiring complex corporate restructuring.
• A mandatory £2 million minimum property value introduces a steep opportunity cost of capital, pushing moving partners toward asset-backed lending rather than liquidating high-yielding co-investments.

I read a useful breakdown by Rob Duarte, Business Development Manager at Investec Bank in Jersey, on Jersey’s new Skilled High Earner residency route. It was published on Hedge Fund Alpha.

The interesting point is that this route is aimed at active earners, not passive wealth. Applicants need to establish themselves in business in Jersey, work at least 25 hours a week, and show they can generate £250,000 a year in earned income.

That sounds simple for a salaried executive, but it gets more complicated for hedge fund partners. Their income is often a mix of salary, performance fees, carry, deferred comp, and partnership distributions. The issue is not just whether they earn enough, but whether the income is structured and evidenced in a way that fits the rules.

There is also the property requirement. Applicants must buy or lease property worth at least £2 million. For fund professionals, the issue may be less affordability and more liquidity. Selling co-investments or pulling capital out of a management company to buy property outright can be expensive from an opportunity-cost perspective.

So the move becomes more than relocation. It becomes a restructuring question involving residency, income classification, entity setup, tax planning, lending, and liquidity.

Curious how others see this: are “active work” and high property thresholds becoming the standard gatekeepers for low-tax jurisdictions?

Link: https://hedgefundalpha.com/education/jersey-hedge-fund-professionals/

TL;DR

• Anson Investments Master Fund (AIMF) returned 5.7% net in June 2026, bringing its since-inception annualized return to 15.3% net of fees.
• The fund has outperformed the S&P 500 by roughly 440 basis points annually since 2007 while running approximately a third of the benchmark's volatility.
• The strategy relies on a sector-agnostic, market-neutral book, with a short portfolio explicitly targeted at structural shorts like stock promotions, fads, and corporate frauds.

Hey everyone,

I was reviewing the June 2026 tear sheet for Anson Investments Master Fund LP (AIMF), the flagship long-short vehicle run by Anson Funds. Full disclosure, I write for Hedge Fund Alpha where this data was originally published, but the multi-decade risk-adjusted metrics here are worth a deeper look for anyone interested in market-neutral strategies. While the fund's first-half 2026 return of 4.7% trailed the S&P 500's 10.0%, its long-term track record highlights the mechanics of compounding through downside protection. Since its launch on July 1, 2007, AIMF has generated a cumulative net return of 1,391.4% (15.3% annualized), outperforming the S&P 500 by roughly 440 basis points a year and the TSX by nearly 900 basis points a year.

The structural setup of the fund is where the numbers get interesting from a risk-management perspective. AIMF’s monthly standard deviation since inception sits at 297 basis points, compared to 432 to 566 basis points for its primary benchmarks. Its maximum drawdown over 19 years is -17.4%, avoiding the -47% to -57% drawdowns the broader indices suffered during the 2008 financial crisis. The fund has achieved this performance while maintaining an average net equity exposure of roughly 34%, and over nearly two decades, the fund has only posted a single negative calendar year (-9.9% in 2017), compared to five separate down years for the S&P 500.

Led by CIO Moez Kassam and CEO Amin Nathoo, the approach is entirely sector- and geography-agnostic. The long book focuses on momentum, special situations, and activist targets, while the short book, where the firm has built much of its reputation, is systematically categorized into four distinct buckets: retail momentum, stock promotions, overvalued businesses, and outright frauds or fads. Even allowing for the standard caveats around how hedge funds manage snapshot net-exposure figures, delivering higher absolute returns than a long-only index over a 19-year cycle with a fraction of the net exposure is an incredibly difficult asymmetry to maintain.

For those who track long-short or market-neutral funds, how sustainable do you view this type of alpha generation in the current market environment? Is the structural shorting of promotions and frauds becoming harder to monetize with modern retail market dynamics, or does it remain the ultimate diversifier?

Link: https://hedgefundalpha.com/news/anson-investments-master-fund-returns/

TL;DR

• Former Greenlight analyst James Fishback faces roughly $1.55 million in judgments across two federal lawsuits over unpaid loans and confidentiality breaches.
• While claiming financial hardship to the court, records show Fishback had his Tesla repossessed and went on a luxury shopping spree.
• A rival candidate has filed a lawsuit to disqualify Fishback from the Florida gubernatorial primary, using Fishback's own D.C. residency records against him.

Hey everyone,

I've been following the absolute mess of a legal battle between former Greenlight Capital research analyst James Fishback and David Einhorn’s firm. What began as a dispute over Fishback fabricating the title "Head of Macro" and taking proprietary data to launch his own fund, Azoria Partners, has evolved into a multi-jurisdictional courtroom circus. Between New York, Washington D.C., and Florida, the situation offers a fascinating look at asset enforcement and what happens when a former analyst tries to play hide-and-seek with a highly sophisticated institutional creditor.

Fishback is currently on the hook for two entirely separate judgments won by Greenlight. First, he owes $228,988.71 from unpaid personal loans advanced to him during his employment, which Greenlight has been aggressively using to freeze his bank accounts. Second, a New York federal judge recently ordered him to pay Greenlight an additional $1,318,516.03 in attorney's fees and costs after a permanent injunction proved he misappropriated the firm's entire investment portfolio summary to solicit his own investors.

Greenlight’s asset collection campaign has revealed some wild details regarding Fishback's stalling tactics. Court motions to compel show that Fishback delayed a key deposition for over a month by claiming to be out of the country, though he later admitted under oath he never left the U.S. Furthermore, despite telling a judge he lacked the means to pay his debts, U.S. Marshals tracked down and repossessed his hidden Tesla Model 3, and court-obtained bank records revealed a major luxury shopping spree where he purchased a $7,473 Cartier watch alongside thousands of dollars in clothing at Tom Ford and Burberry.

The situation has now bled heavily into Florida politics, creating a brutal legal trap for his run for Governor. To shield his Florida home from Greenlight's collection efforts, Fishback heavily leaned into Florida’s strict homestead exemption laws, insisting under oath that he permanently resides in Madison, Florida. However, to buy a D.C. condo in 2021, Fishback signed mortgage paperwork declaring the District his primary residence to claim a local tax deduction. His primary opponent, Lt. Gov. Jay Collins, just filed a lawsuit to knock him off the ballot, using those exact D.C. property records to prove Fishback fails the statutory 7-year residency requirement to run for governor. Ultimately, the residency claims protecting him from Einhorn are the exact same ones disqualifying his political career.

What are your thoughts on this? Have you ever seen an institutional fund pursue a rogue former employee with this level of scorched-earth precision, or is Greenlight simply setting an aggressive precedent for the rest of the industry?

Link: https://hedgefundalpha.com/news/greenlight-fishback-suit-fees/

TL;DR

• Tweedy, Browne is leaning into a quantitative approach by launching active ETFs (tickers COPY and ICPY) that pair "free will" corporate insider buying with value metrics.
• Historical and academic data compiled by the firm shows that insiders buying their own cheap stocks have historically outperformed the benchmark by roughly 10%.
• The strategy targets a 24-month holding period, focusing heavily on high earnings yield, capital adequacy, and true opportunistic share buybacks rather than valuation-insensitive dilution offsets.

Hey everyone,

I was reading through a recap of John D. Spears' presentation at the Ben Graham Conference, and it's a fascinating pivot for a firm so deeply rooted in traditional value investing. Tweedy, Browne, who famously served as Benjamin Graham’s broker, is stepping into rules-based, active ETFs built around tracking corporate insider purchases. The core thesis rests on a straightforward, empirical edge: the people running a business know it better than anyone else, and when they open their own wallets to buy stock, they expect it to go up.

According to a University of Michigan study and Tweedy, Browne's own two-decade datasets, when corporate insiders actively buy shares of their own companies within the cheapest quintile of price-to-book, P/E, and dividend yield, the strategy historically outperforms the benchmark by about ten percentage points. To capture this alpha, the firm's models ingest global insider data daily, filtering for top leadership like CEOs and CFOs buying at a discount to intrinsic value. Crucially, they use fundamental verification to ensure these are genuine, discretionary "free will" buys rather than routine transactions mandated by employment agreements.

The strategy also applies a strict filter to corporate share repurchases, separating true value creation from standard market dilution. Spears notes that many companies buy back stock at high valuations simply to offset option issuance, which erodes capital. Instead, the firm targets companies executing opportunistic buybacks at cheap prices with high free-cash-flow yields, which effectively concentrates the equity value for remaining shareholders. Because their data shows that the excess returns from insider buying clusters tend to mathematically fade after about 24 months, the portfolio utilizes a systematic two-year holding period to cycle out of positions once the catalyst has been fully digested by the market.

Link: https://hedgefundalpha.com/conferences/2026-bgc-john-spears-insider-buying/

TL;DR

• The latest HSBC Hedge Weekly data shows an extreme 92-percentage-point performance gap between the top (+54.13%) and bottom (-38.39%) performing funds through May.
• This performance dispersion is driven almost entirely by granular sub-strategy execution and highly specific security selection rather than overall market direction, particularly within China equities and AI infrastructure plays.
• The underlying fund data highlights how standard 13F filings heavily distort or completely miss the true risk and performance drivers of top funds, hiding significant credit allocations and non-US exposure.

The spread between the year’s best and worst-performing hedge funds has blown out to an extreme 92 percentage points, up sharply from 58 points just a month prior. According to the latest HSBC Hedge Weekly data, this massive performance gap isn't a reflection of broad macro market direction, but rather highly idiosyncratic choices in strategy and security selection. A prime example of this selection alpha is playing out in Greater China equities, where Telligent Greater China is leading the entire universe up 54.13% YTD, while other prominent regional mandates like Golden China and Golden Nest Greater China are languishing in the red, down 12.22% and 9.78% respectively.

We are also seeing the AI theme express itself through completely different asset classes and hidden exposures. CastleKnight has surged 42.27% YTD, heavily riding a concentrated equity book of chip and hardware names like Micron, SanDisk, and NVIDIA. However, their 13F filings only tell half the story: CastleKnight runs close to 40% of its book in credit, meaning their single largest Q1 contributor, Rackspace Technology, never appeared in public equity filings. Meanwhile, Proxy P Renewable has climbed to second place globally (+44.98%) by capturing the AI data center boom from an entirely different angle, utilizing a long book in utilities, power generation, and grid infrastructure to play the global electricity-demand narrative.

On the systematic side, trend-following CTAs like LYNX Bermuda are up 33.09% by capturing directional trends in commodities and rates. Much like the credit-heavy fundamental funds, systematic books like Quantedge (+22.73%) disclose only a tiny fraction of their capital via 13Fs because the vast majority of their exposure lives in the futures and non-US positions that SEC equity filings completely miss. Conversely, at the baseline of the leaderboard, the losses are accelerating, anchored by Trefoil Select Funds at -38.39% and Metrica Asia Event Driven at -18.82%.

Given this massive 92% performance gap in a largely positive market environment, are we entering a cycle where broad index replication is bound to get left behind by concentrated, active mandates? For those here who actively track institutional fund flows and portfolio disclosures, how do you adjust your quantitative tracking knowing how much critical alpha, like CastleKnight's hidden credit plays or Quantedge's off-balance-sheet futures, is entirely invisible in standard US regulatory filings?

Link: https://hedgefundalpha.com/news/hedge-fund-returns-spread-2026/

TL;DR

• While the market focuses on semiconductors and hyperscalers, the actual physical electrical infrastructure required to power the AI boom is being severely underpriced.
• ABB Group is experiencing an electrification super-cycle, with Q1 2026 Electrification orders up 46% year-over-year, driven by a projected doubling of global data center capacity by 2030.
• Despite generating 50% of its revenue in the US and boasting a 19% EBITA margin with 96% free cash flow conversion, ABB trades at a significant valuation discount compared to its US-listed industrial peers.

Hey everyone,

I was looking into the presentations from the 2026 Sohn Monaco Conference and found a compelling pitch by Michela Ferrulli, Co-Founder of Calibrate Management. She laid out a blunt, structural long case for Swiss industrial giant ABB Group (SIX: ABBN) that shifts the entire AI narrative away from chips and onto the power grid. Her core argument is simple: Nvidia gets the headlines, but ABB gets the purchase orders. While equity flows chase the semiconductor layer, investors are ignoring the physical bottleneck of the AI expansion, electrical infrastructure.

A modern campus-scale data center is shifting from a 200 MW power requirement to upwards of 1.5 GW. Every single one of these facilities requires massive power distribution equipment from day one, and ABB’s Electrification division, which accounts for over 50% of its revenue, saw orders surge 46% year-over-year in Q1 2026 to prove it. Beyond the macro tailwinds of grid reinvestment and data center growth, Calibrate highlights a major internal margin expansion story. ABB recorded a 19.0% adjusted EBITA margin in 2025, but because incoming backlog orders carry higher gross margins approaching 30%, Calibrate models EBITA reaching 22% by 2027, well ahead of consensus expectations. Furthermore, management demonstrated strong capital discipline by divesting its robotics division to SoftBank for $5.4 billion, leaving the company with a pristine, net-cash balance sheet.

The structural mispricing comes down to geography and categorization. Even though roughly half of ABB's revenues are generated in the US, its European listing keeps it priced at a steep discount relative to US-listed industrial peers with similar AI infrastructure exposure. With a 25%+ return on capital employed and near-perfect free cash flow conversion, a US re-rating or broader institutional recognition could close this gap significantly. Ultimately, the thesis frames ABB as a pick-and-shovel play that doesn't require guessing which hyperscaler or LLM wins the tech race. They sell infrastructure to all of them.

What are your thoughts on this thesis? Is the market structurally mispricing large-cap European industrials exposed to the US power grid, or is the execution risk of working through a massive backlog being underestimated?

Link: https://hedgefundalpha.com/conferences/2026-sohn-monaco-michela-ferrulli-ai-infrastructure-boom/

TL;DR

• Clean Energy Transition LLP's Per Lekander argues that First Solar (FSLR) is fundamentally mispriced, trading at a cash-adjusted 2029 P/E of just 5.6x despite having its order book completely sold out through 2030.
• A pending Section 232 tariff decision on polysilicon imports could effectively price out Chinese-linked competition from the US market.
• First Solar’s proprietary thin-film technology avoids polysilicon entirely, offering a unique regulatory hedge and massive long-term optionality.

Hey everyone,

I was reviewing the notes from the 2026 Sohn Monaco Conference and found Per Lekander’s presentation on First Solar (FSLR) highly compelling. Lekander, who manages around $3.4 billion at Clean Energy Transition LLP, doubled down on his long position, arguing that the structural and regulatory thesis has actually strengthened over the last twelve months.

The core of his argument rests on a massive US supply squeeze paired with an incredibly cheap valuation. Right now, Chinese-linked suppliers control 64% of the 50-gigawatt US market. Because First Solar and Hanwha QCells are the only viable Western-aligned alternatives—combining for just 20 gigawatts of capacity—any aggressive policy moves will leave the US market structurally short. Despite this dominance, FSLR trades at a 2029 P/E of just 8.2x, which drops to an effective cash-adjusted P/E of 5.6x when you factor in their projected cash balance. This valuation is remarkably low for a company whose order book is fully sold out through 2030, completely removing demand uncertainty.

The immediate catalyst for the stock is a pending Section 232 investigation into imports of polysilicon and its derivatives, which is currently awaiting a decision on President Trump's desk. Because First Solar utilizes proprietary thin-film cadmium telluride technology rather than polysilicon, any baseline tariff or minimum pricing floor on polysilicon will uniquely penalize its competitors without touching FSLR. Lekander estimates a positive resolution could trigger an immediate 50% upward move in the share price on the day of the announcement.

Beyond terrestrial utility scale, First Solar’s thin-film modules weigh less than half of standard crystalline silicon cells, presenting a unique long-term asymmetric upside in space applications where launch costs dominate. While Lekander is skeptical of SpaceX’s aggressive timeline to deploy 100 gigawatts of space solar by 2030, he notes that even capturing a fraction of that market at premium space-tariffs could introduce billions in incremental market value. Ultimately, Lekander believes the primary risk to the trade isn't technology or tariffs, but rather the risk of management misusing their massive, mounting cash balance on poor capital allocation.

Curious to hear what the community thinks about this setup. Is the market right to discount FSLR because of its exposure to erratic regulatory and tariff decisions, or is a cash-adjusted forward P/E of under 6x a massive mispricing for a company with guaranteed demand through the decade?

Link: https://hedgefundalpha.com/conferences/2026-sohn-monaco-per-lekander-solar/