Dan Rasmussen 5.2 12 ideas

The speaker states the private credit asset class is "nowhere near cheap" and that it is "too early to even consider going long these vehicles on the premise that they're cheap." He believes the sector is at the start of a major crisis with severe default risk, exacerbated by structural liquidity mismatches in fund vehicles. Historical precedent shows such periods of rapid lending growth end poorly. Avoid long exposure to the private credit segment of finance due to overvaluation relative to looming fundamental risks and the high likelihood of further price discovery and outflows. If the default wave is materially smaller and slower than forecast, the asset class may stabilize at current levels.

The speaker explicitly states he is using private credit vehicles as a hedge by "shorting it on the way down" and confirms he is shorting BDCs. He forecasts >20% default rates in private credit, driven by risky, cyclical lending to highly leveraged companies. Liquidity outflows from funds (as investors redeem at NAV) will create refinancing and liquidity issues, forcing further price declines in publicly traded BDCs. Shorting BDCs provides a hedge against the unfolding crisis in risky credit as fundamental defaults and forced selling pressure their valuations. A swift, large-scale liquidity intervention or a sudden economic rebound that drastically lowers default rates could halt the decline.

Private credit has expanded massively to fill the void left by banks, lending to risky LBOs (40% in software) at rates that imply "low single B" credit quality. Lenders are seeing a rise in "PIK interest" (borrowers not paying cash). The entire premise of this lending was based on software "recurring revenue" and high equity valuations acting as a cushion. With software equities collapsing and revenue quality questioned, the collateral backing these loans is vaporizing. In a recession, this credit tier historically sees ~30% default rates. Short the sector. While "gold standard" firms like ARES might have better underwriting, the asset class as a whole is opaque, illiquid, and facing a "race to the bottom" in lending standards. A "soft landing" where rates drop quickly, allowing borrowers to refinance before defaults cascade; the "gold standard" firms (ARES) proving resilient enough to gain market share from collapsing smaller players.

Private credit lenders lent against "recurring revenue" because software companies lack hard assets (factories/trucks) and often lack profits. As software stocks fall, the "equity cushion" supporting the credit market disappears. If private credit (the primary lender to these LBOs) faces a liquidity crunch or losses, the funding lifeline for leveraged software companies will be cut off, leading to further equity compression. Avoid or Short highly leveraged software companies dependent on private credit financing. A resurgence in tech/software valuations driven by AI speculation or rate cuts.

The median Japanese company holds ~7 years of net income in assets (vs. 1 year for US companies). Corporate governance reforms are pressuring these companies to increase payouts (dividends/buybacks). There is a massive "value unlock" potential as these unproductive assets are distributed to shareholders. The return of inflation signals nominal GDP growth, breaking the deflationary mindset. LONG. It is a deep value play with a specific catalyst (governance reform) that does not rely on massive tech innovation. Cultural resistance to rapid change (slow-moving consensus); currency volatility (Yen weakness).

US valuations are high, but the US is undergoing a "unique in history innovation wave" (Cloud, AI). Unlike other markets, US companies have actually grown into their high multiples through tangible technological revolutions. Betting against US innovation has historically been a losing trade. LONG. High valuations are a feature of high innovation, not necessarily a bubble. Mean reversion in profit margins; regulatory crackdowns on Big Tech.

Biotech is the most uncorrelated sector with the highest dispersion. 70% of unprofitable biotechs lose money, but the sector has experienced a massive drawdown (historically followed by massive recoveries). The "baby has been thrown out with the bathwater." A systematic approach filtering for "Quality" (owned by specialists) and "Value" (low Market Cap relative to R&D Spend) identifies winners in a sector where generalist capital has fled. LONG. The sector offers "lottery ticket" positive skewness after a deep cyclical bottom. High failure rate of individual clinical trials; interest rate sensitivity for unprofitable companies.