August 14, 2026
Hedge Funds: Are We Situationally Aware?
Hedge funds are among the financial market’s most mythologized institutions, shaped by the reputations of legendary investors such as Ken Griffin, Ray Dalio, and George Soros.
The hedge fund industry has repeatedly been shaped by episodes in which compelling narratives attract enormous amounts of capital, turning investment themes into crowded trades that can unwind violently when expectations change.
The collapse of Situational Awareness underscores how quickly extraordinary capital inflows can trans-form a promising investment theme into a fragile port-folio when growth outpaces risk management, governance, and portfolio discipline.
Despite recent underperformance, the current market environment of tighter liquidity and greater earnings dispersion may create a more favorable backdrop for hedge funds, where stock selection and fundamental analysis can once again become meaningful sources of alpha.
To understand the significance of that event, it is useful to start at the beginning. Hedge funds are a relatively young investment strategy. They were created in New York in 1949 by Alfred Winslow Jones, a sociologist and financial journalist who wanted to profit from stock selection rather than market direction. The industry expanded rapidly during the 1970s and 1980s as new approaches emerged, including global macro, arbitrage, and event-driven investing. Since then, hedge funds have stood at the center of some of the most important financial episodes of modern history. These episodes range from George Soros’s famous 1992 bet against the British pound, to the collapse of Long-Term Capital Management during the 1998 Russian bond crisis, and more recently to the downfall of Melvin Capital during the 2022 meme-stock frenzy. Despite their differences, all of these stories share a common element: leverage.
Leverage is central to the hedge fund business model. As stock selection alone often does not generate the returns demanded by investors, many hedge funds amplify their positions through borrowed capital. On average, hedge funds operate with roughly 2.5x to 3.0x the capital entrusted to them by investors, with some funds operating well above those levels. According to JPMorgan, by the end of 2025, quantitative funds that rely on high-frequency and algorithmic trading strategies employed an average gross leverage of around 6.0x investor capital. In that context, the recent collapse of a USD 45 billion hedge fund has become less surprising.
So, what happened? In late July, the hedge fund Situational Awareness managed by Leopold Aschenbrenner, a 24-year-old former OpenAI employee, was forced to liquidate its public equity portfolio because of liquidity constraints. The fund was heavily concentrated on AI infrastructure companies, including SK Hynix, CoreWeave, Micron, SanDisk, and Bloom Energy, among other beneficiaries of the global data-center and computing buildout. When several of these stocks corrected sharply during July, the fund reportedly faced substantial margin calls from brokers including Goldman Sachs, JPMorgan, and Bank of America. Aschenbrenner, once described by some as an “AI Nostradamus,” ultimately had to sell the fund’s liquid portfolio to Citadel, Ken Griffin’s investment firm.
We would think that such high levels of leverage would consistently produce superior returns; however, during the last ten years, evidence suggests otherwise. Using the PivotalPath Composite Index, which tracks more than 3,000 institutional hedge funds representing over USD 3 trillion in assets and comparing it with a traditional 60/40 portfolio (60% S&P 500 and 40% Bloomberg U.S. Aggregate Total Return Index), hedge funds have generally underperformed traditional balanced portfolios over the past decade. Relative to other alternative asset classes, they have only outperformed real estate and timberland.
July also served as a powerful reminder of the risks embedded in leveraged portfolios. Preliminary data indicate that TMT Equity Sector hedge funds (Technology, Media, and Telecom) lost approximately 10.2% during July’s technology selloff, while multi-strategy hedge funds declined roughly 2.3%. The TMT figure excludes the full impact of the Situational Awareness collapse, yet it still represents the worst month on record for that strategy. For multi-strategy funds, we must look back to the pandemic or the 2008 Global Financial Crisis to find worse monthly performances.
Ordinarily, persistent underperformance combined with a high-profile collapse would suggest a difficult fund-raising environment. Yet the industry has been moving in the opposite direction. During 1Q26, hedge fund assets under management reached a record USD 5.22 trillion. During the first half of 2026, assets increased by approximately USD 473 billion, with investment gains accounting for roughly 81% of that growth.
Paradoxically, July’s turmoil may prove to be the catalyst the industry needed to regain relevance. For much of the 2010–2021 period, abundant liquidity and near-zero interest rates allowed many stocks to rise simultaneously through multiple expansion, meaning investors were willing to pay higher price-to-earnings or price-to-sales multiples even when underlying fundamentals did not improve proportionally. Today, that regime appears to have changed. Expectations are exceptionally high, particularly for AI-related companies, and stock prices are reacting far more sharply to earnings surprises and guidance revisions. Meta (META) provides a clear example. Despite reporting strong revenue growth, the stock fell roughly 10% after earnings as investors focused on rising AI capital expenditures and weaker free-cash-flow trends. Alphabet (GOOGL) also delivered solid top-line growth, yet its shares declined about 3% after management raised its capital expenditure outlook. In contrast, Microsoft (MSFT) rallied roughly 8% after earnings following stronger-than-expected Azure growth and a more convincing AI monetization story. These sharply different reactions among companies operating within the same technology ecosystem illustrate that stock selection matters far more today than it did during the era of broad multiple expansion.
This shift in market behavior becomes even more important if the Federal Reserve maintains a relatively restrictive policy stance. In such an environment, companies with strong near-term cash generation are likely to be rewarded more than long-duration growth companies
whose valuations depend heavily on distant future earnings. As a result, earnings dispersion should continue to widen, creating the type of market backdrop in which many long/short and event-driven hedge fund strategies have historically performed best. In other words, after years in which abundant liquidity made it difficult for active managers to differentiate themselves, hedge funds may finally be operating in an environment where fundamental analysis, relative-value investing, and stock selection can once again become meaningful sources of alpha.
Ironically, Situational Awareness gave the industry genuine situational awareness. The episode exposed the vulnerabilities of managers with weak risk frameworks and insufficient portfolio oversight. Over time, the market is likely to depurate some of those managers, potentially leaving behind a stronger group of firms better positioned to benefit from the more selective environment now emerging. Ultimately, the story of Leopold Aschenbrenner captures both the risk and the opportunity embedded in today’s hedge fund landscape. After publishing a 165-page manifesto on artificial intelligence, Leopold grew his hedge fund from roughly USD 225 million to USD 45 billion in just two years, only to lose nearly everything within a single month. That extraordinary rise and collapse may become part of the hedge fund industry’s enduring mythology, where bold ideas, rapid capital inflows, leverage, and market euphoria can create fortunes and destroy them just as quickly.
While writing this piece, I attended a lecture by Aswath Damodaran, who remarked that he could understand the mistakes of a 24-year-old entrepreneur as a matter of inexperience, but not the mistakes of major Wall Street institutions that chose to finance the strategy. More than an AI story, this episode is a reminder that manager due diligence and risk discipline matter far more than compelling narratives or fear of missing out.
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