ALO36: The Endowment Playbook for Long-Term Investing ft. Paul Chai

Core argument: Paul Chai runs the Kansas State University Foundation endowment ($1.2B) on a top-down strategic asset allocation (SAA) framework rather than a bottom-up total portfolio approach (TPA), reviewed every three to five years. The portfolio targets roughly 6% real / 8% nominal return over the long term, structured as a 60% growth bucket (equity-like risk, split ~55% public/45% private) and 40% diversifying bucket (liquidity sleeve, diversifier hedge funds, real assets like energy/infrastructure/real estate, and private credit). Chai is explicit about conviction level: running Monte Carlo analysis across 1,000 scenarios, the chosen portfolio has roughly a 51-52% probability of achieving the 8% nominal target over 10 years — "it's not going to be a high certainty, but it's better than half."

Mechanism: The framework optimizes across multiple objectives simultaneously — maximizing expected return, maximizing probability of hitting the real return target, minimizing 10-year liquidity risk, limiting spending-decline risk, and capping drawdown risk — rather than optimizing for a single "champion" outcome. The selected allocation ranks in the upper half across all dimensions rather than first in any one. Within each asset-class bucket, Chai applies what he calls a "poor man's total portfolio approach": any private allocation must clear a bar of outperforming a public-market equivalent, so niche public strategies (structured credit, credit-dislocation strategies capable of 20%+ IRRs in short windows) are used as hurdles inside the private credit and private equity sleeves.

On bonds specifically, Chai says the team is skeptical of bonds' ability to hedge equity volatility going forward and prefers to substitute illiquidity tolerance for that role via diversifier hedge funds, real assets, and private credit instead of traditional fixed income.

What has to be true / what would break the view: The 51-52% hit-probability framing is itself the guest's own hedge — he does not claim high confidence in the 8% target, only that the chosen portfolio construction maximizes the odds versus alternatives. On implementation, Chai notes SAA studies must include practical constraints (liquidity guardrails, private-market pacing, existing commitments) so new targets are achievable within two to three years before the next review — otherwise the allocation is theoretical rather than actionable. He also flags a specific case where the thesis didn't play out: the fund's private credit commitment to traditional energy "hasn't worked out too well," because financing conditions for large energy producers improved faster than expected, and disciplined capital deployment by industry players compressed the dislocation that the credit strategy was underwriting. By contrast, the equity-side energy commitment (increased two to three years ago on the view that non-economic outflows from larger institutions were creating mispricing) is treated separately and not marked as a disappointment in the conversation.

On hedge funds, Chai splits the diversifier bucket into an absolute-return sleeve targeting 8%+ regardless of cycle (funding source for the second sleeve) and a smaller convexity/insurance sleeve (long-volatility-type strategies) that is expected to cost money in normal periods, akin to a put option. He allocates to multi-strategy "pod shops" despite their higher fee load, arguing top-tier managers deliver >8% absolute return with high Sharpe ratios and low correlation — the main risk he actively monitors is market crowding and de-leveraging events, which he tracks by checking in with managers on how they're responding. He currently holds no allocation to CTA/managed futures strategies, because classic trend/momentum factors have become commoditized and replicable at lower cost, while less conventional managed-futures approaches are harder to underwrite as return drivers become more of a "black box."

On fees more broadly, Chai reports fee data annually to the investment committee and distinguishes where fee sensitivity matters (passive/treasury allocations, where active fees aren't justified by return dispersion) from where it doesn't (idiosyncratic hedge fund and private strategies, judged net-of-fees against top-quartile-versus-bottom-quartile dispersion).

On secondaries: Chai says the foundation has been a net buyer in private-market secondaries over the last two years, as larger institutions were forced to sell higher-quality private assets for non-economic reasons — anticipation of the endowment tax, government research-funding pressure creating liquidity needs, and impatient holders (including employees of late-stage private tech companies) selling at a discount.

On manager selection, Chai says he deliberately avoids using pedigree (established vs. emerging manager) as a screening factor, instead sequencing opportunity-fit, then strategy-fit, then people-fit. He assesses managers for "grit" (passion plus perseverance), distinguishing harmonious passion (purpose-driven) from obsessive passion (self-serving), the latter of which he associates with worse handling of adversity. Investment decisions on his six-person team require consensus — a single team member's strong opposition is sufficient to block an investment, a governance approach he says would likely differ on a larger team.