Uncapped with Jack AltmanInside the Mind of a University Endowment Manager | Dan Feder, University of Michigan | Ep. 14
CHAPTERS
From lawyer to endowment investor: accidental entry and “fast processor” hiring philosophy
Dan Feder recounts how he stumbled into endowment management after starting as a lawyer, landing at Princeton through a chain of introductions (including Dave Swensen and Andy Golden). He explains how being hired without the “perfect spec” shaped his views on talent, learning speed, and long-horizon investing.
- •Entered investing via chance lunch and networking; learned endowments on the job
- •Early mentors and the Yale/Princeton “endowment model” lineage
- •Andy Golden’s mantra: “fast processor vs full hard drive”
- •How early career path informs Dan’s approach to hiring and manager evaluation
What an endowment actually is: an endowment pool serving thousands of sub-endowments
Feder clarifies that a university endowment is typically a pooled structure—more like a mutual fund—made up of many individual endowments with specific purposes. He outlines the endowment’s core objectives: fund spending, preserve purchasing power, and generate real returns with intergenerational equity.
- •Endowment pool ≠ single pot; Michigan has ~13,000 separate endowments
- •Spending rule: typically ~4–5% with multi-year smoothing
- •Need to beat “higher ed inflation” to maintain spending power
- •Intergenerational equity: avoid excessive drawdowns and volatility
Zero-based portfolio construction: why equity orientation is the starting point
Starting from a hypothetical fully liquid portfolio, Dan explains why endowments usually need meaningful equity exposure to target roughly ~8% nominal returns over the long run. He then describes how diversification across asset classes is used to manage volatility while pursuing required returns.
- •A perpetual return target pushes portfolios toward equities
- •Begin with liquid public markets as the efficient baseline
- •Use diversification to dampen volatility while maintaining return potential
- •Illiquids become feasible because annual liquidity needs are modest
Allocation vs investing: risk-based optimization and behavioral guardrails
Feder separates asset allocation (risk-based, model-driven) from security/manager selection (active investing). He argues allocation frameworks (e.g., mean-variance optimization) are useful not only mathematically but behaviorally, preventing overconfidence and overcommitment—especially in venture.
- •Allocation uses historical risk/return/correlation to set a model portfolio
- •Risk-based models rely on “past to predict future” assumptions
- •Allocation constraints reduce behavioral errors (doing too much/too little)
- •Venture is especially prone to overconfidence, making guardrails valuable
Risk vs uncertainty: why venture’s edge lives in the “unknown unknowns”
Drawing on Frank Knight and the Rumsfeld taxonomy, Dan argues venture capital’s true power is in uncertainty—things not known or not knowable—rather than measurable risk. Durable alpha comes from accessing non-obvious founders and problems before markets can efficiently price them.
- •Knightian distinction: risk (measurable) vs uncertainty (not knowable)
- •Venture’s advantage: investing amid “unknown unknowns”
- •Example: founder insight into a problem nobody else sees yet
- •Risk-based edges get arbitraged away; uncertainty-based edges can persist
Reframing venture: “adventure capital” vs financing mature ventures
Dan challenges the idea that venture is a coherent “asset class,” suggesting it contains at least two different activities: adventure capital (ambitious, uncertain, frontier work) and capital for ventures (more conventional financing). This framing de-emphasizes stage labels and spotlights where endowments may have the strongest fit.
- •Origin story: “venture capital” as a shortening of “adventure”
- •Two categories: adventure (uncertainty) vs venture financing (capital needs)
- •Stage (seed/A/B) can be misleading; later-stage can still be adventurous
- •Endowment fit often stronger on the “adventure” side given horizon and networks
LP incentives and team design: career paths, short-term metrics, and input vs outcome focus
Feder explains how endowment management professionalized over 25 years, creating clearer career ladders—but also more short-term performance signaling. He contrasts outcome-driven behavior (marks, visible near-term wins) with input-driven compounding (patient learning, relationship-building, idea incubation).
- •Shift from “accidental” endowment careers to a defined promotion ladder
- •Career mobility increases pressure to show track record quickly
- •Outcome focus vs input focus: marks/narratives vs long-horizon learning
- •Dan’s approach: cultivate ideas and networks that can take years to pay off
Backing strategies that disagree: concentrated relationship roster and complementary exposures
As an LP, Dan describes living with constant cognitive dissonance—funds he backs can have opposing philosophies. He argues you don’t need to be right about everything; instead, a resilient endowment portfolio benefits from a constrained set of relationships chosen for distinct, complementary return drivers.
- •LP reality: specialists vs generalists, solos vs firms, large vs small—often contradictory
- •Concentrated approach: ~36 relationships (27 venture, 9 PE)
- •Goal is to “pick the one” in a segment rather than own many similar managers
- •Complementarity matters: distinct sources of return across managers
Why invest in venture at all: social pressure, narrative power, and dispersion of returns
Dan gives an unusually candid answer: many LPs invest in venture partly because they’re expected to. He emphasizes that venture can be excellent only if you access the handful of companies/managers that drive outcomes—yet overconfidence and compelling GP storytelling can seduce allocators.
- •Institutional pressure: “we’re supposed to” be in venture
- •Venture is poor if you miss the few outsized winners
- •Above-average bias: everyone thinks they’re above average at picking
- •GP-LP dynamic: LPs love stories; GPs are incentivized to tell them well
Michigan’s endowment framework: five buckets, but a shifting playbook
Feder outlines Michigan’s conventional top-level structure (cash/fixed income, public equities, absolute return, real assets, venture/PE). He argues “best practices” are changing because alternatives are no longer alternative, LP talent is deeper, and simplistic recipes no longer deliver durable advantage.
- •Five asset-class buckets structure the portfolio
- •Alternatives are now mainstream: crowded, capitalized, well-traveled
- •Allocator sophistication has increased; old “easy edges” are fading
- •Future success requires institution-specific investing, not recipe-book allocation
Endowment-specific advantages: access, time horizon, and occasional ability to influence outcomes
Dan explains how Michigan evaluates uncertain/illiquid investing through three institutional advantages: access (information/people/opportunities), long time horizon, and occasional capacity to change outcomes via relationships. He emphasizes each institution must tailor activity level (active vs passive) to its unique positioning.
- •Advantage lens: access + horizon + (sometimes) outcome influence
- •Michigan’s strengths: research engine and large, loyal alumni network
- •Not trying to be “value-add VC,” but small interventions can be high marginal impact
- •Some institutions should choose passive exposure if advantages don’t match
Individuals vs firms: maximizing exposure to the true sources of productivity
Feder argues the end goal isn’t to “own” firms but to gain exposure to exceptional underlying companies through exceptional investors. He discusses the difficulty of separating an investor’s individual edge from a firm’s franchise—and how this affects whether to back platforms or specific people.
- •True objective: exposure to the best underlying companies, efficiently
- •Hard question: where does the person end and the firm begin?
- •Some investors are great only within a firm; others are great independently
- •Portfolio design must maximize fidelity to the real alpha-generators
Big vs small funds: fund size as symptom, not cause—and the importance of being in the conversation
Dan resists simplistic “big fund bad” takes, noting size can either dilute quality or enable ambitious strategies (including leading rounds and supporting winners). He says the LP’s role is to engage deeply—help pressure-test uncomfortable but correct decisions—rather than dictate one-size-fits-all rules.
- •Fund size can be too big or too small depending on strategy
- •Small funds may lack ability to lead and build meaningful ownership
- •Large funds can lose fidelity or incentivize the wrong behaviors
- •Best LP posture: engage on strategy and tradeoffs; support hard-but-right decisions
How Michigan picks managers: referral-driven sourcing, a five-part manager job, and resisting “taste” shortcuts
Feder describes a highly filtered sourcing process based on introductions and trusted networks, not broad market coverage. He evaluates managers by whether they can source, transact, own, exit, and run the firm without harming the first four—and cautions against hand-wavy “taste” as a substitute for rigorous slow thinking.
- •Sourcing only via qualified referrals; no attempt to “see the whole market”
- •Portfolio fit matters: great managers can be rejected if redundant
- •Five-part framework: source, transact, own, exit, and operate the firm
- •“Taste” can be a cop-out; long-lived relationships require slow thinking
Herd mentality in LP land: wisdom of crowds, perimeter thinkers, and crisis vulnerability
Dan acknowledges that herds can be right, but warns that relying on the herd leaves weaker allocators exposed when regimes change. He advocates being an independent thinker near the perimeter—capable of acting decisively when the herd structure breaks—illustrated by a safari story about predators and herd dynamics.
- •Crowds can be wise; independence doesn’t require reflexive contrarianism
- •Weaker herd-followers become vulnerable when conditions shift
- •Aspirational stance: self-sufficient, perimeter-of-herd decision-making
- •Safari anecdote: herd movement creates the moment predators exploit
