Expected Returns for Alternative Asset Classes (plus Reading Habits w/ David Senra) (EP.219)

Episode Summary

Executive Summary: The episode centers on estimating expected returns for alternative asset classes for financial planning, arguing that fees, illiquidity, manager selection, and skewed outcomes materially reduce the appeal of many “alternatives.” Private equity and venture capital may offer modest premiums only for top access and top managers; hedge funds, private credit, and direct real estate often look closer to public-market exposures after costs; cryptocurrencies are modeled as low-return, extremely high-volatility lottery-like assets. The later segments add a Canadian investor literacy study, conference reflections, and an in-depth interview with David Senra on reading, founders, and learning by rereading.

Main Topics: Expected returns framework for alternative assets (Priority: 5/5): Benjamin Felix explains why alternatives need explicit return assumptions in financial planning and why they are harder to model than public markets because of no true index beta, manager dependence, and extreme skewness. Private equity, venture capital, and angel investing (Priority: 5/5): The discussion compares buyouts, VC, and angel deals using PMEs, valuation gaps, and manager persistence; returns are highly dispersed and access to top funds matters more than average historical data. Private credit and hedge funds (Priority: 4/5): Both asset classes are shown to have limited evidence of meaningful excess returns after fees, with hedge funds especially burdened by hidden fee drag and investor behavior gaps. Direct real estate and cryptocurrencies (Priority: 4/5): Private real estate appears to replicate public real estate risk factors, while crypto is treated as speculative, lottery-like exposure with very high volatility and low expected return. Canadian investor financial literacy study (Priority: 3/5): A follow-up on financial literacy reports average investor scores, weak understanding of costs and protections, and lower literacy among robo-advisor users. Future Proof conference reflections (Priority: 2/5): Cameron describes a high-energy industry conference format, noting strong engagement but also unbalanced crypto presentations and many takeaways for the business and podcast. Interview with David Senra on reading and founders (Priority: 4/5): A long-form conversation explores how Senra built a career around reading biographies, extracting lessons from founders, and using rereading as a learning system.

Key Arguments: Alternative assets require explicit expected-return assumptions in planning because client portfolios may include them, but their unpredictability means conservative assumptions are usually warranted. Private equity buyouts historically outperformed public markets modestly, but recent valuation convergence, higher capital inflows, and fee drag imply lower forward returns. Top-quartile private equity and venture funds can produce dramatic outperformance, but there is little persistence in top buyouts and access to elite VC funds is highly constrained. Angel investing has huge upside skew, but most deals lose money and outcomes depend heavily on due diligence, experience, and active coaching by the investor. Private credit may offer diversification or duration differences, but PME results often cluster near public-market benchmarks and public credit may now look relatively attractive. Hedge fund sticker fees understate true cost; empirical investor fee drag and behavior gaps can turn a nominal 2 and 20 structure into much worse realized performance. Private real estate largely appears to be explained by public real-estate/factor exposures, weakening the case for a unique illiquidity premium. Crypto is best modeled as a speculative asset class with lottery-like payoffs, which implies low expected return and high volatility despite occasional massive upside. Financial literacy gaps are especially concerning around costs and protections, suggesting many investors do not understand the products they are using. Senra argues that sustained reading, rereading, and historical comparison are essential to understanding founders, innovation, and the role of randomness/luck.

Data Points: Buyout PME vs S&P 500: 1.18 - Harris et al. 2020 sample of 893 buyout funds (vintages 1987-2014) showing historical private equity outperformance vs the S&P 500 benchmark. Buyout PME vs S&P 500 (earlier sample): 1.2 - Harris et al. 2014 for vintages 1987-2014 when benchmarked to the S&P 500. Buyout PME vs Russell 2000 Value: 1.07 - Harris et al. 2014; benchmarking against smaller/value public stocks reduces the apparent private equity edge. Public equity expected return baseline: 7.09% - PWL’s multi-factor-tilted global public equity expected return used as the comparison point. AQR buyout expected real return: 5.9% - AQR estimate net of 5% fees for buyout funds based on Ilmanen-style methodology. Assumed private equity fee drag: 6% - Speaker’s rough total cost estimate for access through intermediaries, especially in Canada. Assigned PE premium over public equities: 50 bps - Final planning assumption for private equity buyouts relative to multi-factor public equities. Private equity standard deviation: 29% - Speaker’s planning assumption, aligned roughly with BlackRock’s high-volatility estimate. Top-quartile buyout PME: 1.81 - Harris 2020; top quartile PE funds show large historical outperformance. Bottom-quartile buyout PME: 0.68 - Harris 2020; bottom quartile PE funds materially underperform public markets. VC sample average PME: 1.22 - Harris 2020 sample of VC funds (vintages 1984-2014). VC sample average PME (earlier paper): 1.2 - Harris 2014 sample of vintages 1984-2008. VC median PME: 0.88 - Harris 2014; large gap between mean and median highlights skewness. VC annualized premium vs public equities: 3.7% - Derived from a mean PME of 1.2 over a typical five-year fund duration. Top-quartile VC PME: 2.6 - Harris 2020; top VC managers show very large upside. Bottom-quartile VC PME: 0.41 - Harris 2020; bottom VC managers severely underperform. Angel investing average multiple: ~2.5x - Wiltbank studies (2007/2009) with an average holding period of 3.5 years. Angel investing annualized return: >29% - Implied from average multiple and holding period in Wiltbank studies. Angel deals with negative returns: >50% - More than half of angel deals in the sample lost money. Angel exits driving returns: 7% of exits - In Wiltbank 2007, 7% of exits generated 75% of total dollar returns. Angel low-diligence return multiple: 1.1x - Angels doing less than median 20 hours of due diligence earned much lower returns. Private credit PME benchmark result: close to 1 - Munday et al. 2018; private credit strategies broadly track public benchmarks after adjustments. Private credit expected return assumption: 5% - Speaker’s planning assumption after haircutting BlackRock’s gross estimate. Private credit standard deviation: 10% - BlackRock direct lending assumption used as a guide. Hedge fund management fee: 1.51% - Ben-David et al. 2020 empirical average annual management fee paid by investors. Hedge fund incentive fee: 1.93% - Ben-David et al. 2020 annualized incentive fee paid by investors. Hedge fund incentive fee justified by excess performance: 0.74% - Ben-David et al. 2020 portion of incentive fee actually earned through outperformance. Hedge fund extra fee drag: 1.19% - Ben-David et al. 2020 incentive fees paid on gains later offset by losses. Hedge fund investor underperformance vs funds: 3% to 7% - Diecihev and Yu 2011; behavioral gap from performance chasing and timing. Hedge fund expected return assumption: 3.36% net of fees - Derived from BlackRock’s 7.8% gross estimate minus fees and behavior drag. Hedge fund standard deviation: 7.7% - BlackRock broad hedge fund estimate. Credit Suisse Hedge Fund Index return: 7.2% net - 1994 through July 2020, with annualized standard deviation of 6.7%. Private real estate expected real return: 2.6% - AQR Q3 2021 estimate. Private real estate nominal return: 4.1% gross - BlackRock U.S. real estate estimate. Canadian direct real estate adjustment: -1% - Speaker’s rough adjustment due to still-high Canadian valuations and low net rental yields. Crypto proxy stock index return: 1.07% nominal - Ken French small, low-book-to-market, low-operating-profitability index from 1963 through June 2022. Crypto proxy stock index volatility: 29% - Same Ken French index used as a proxy for lottery-like crypto payoff characteristics. U.S. market return over same period: 10.22% - Comparison for the crypto-proxy stock index. Bitcoin annualized standard deviation: 80% - 2015 to 2022 historical volatility cited as evidence of extreme risk. Crypto planning standard deviation: 60% - Speaker’s assumed forward volatility, roughly double the lottery-stock proxy and below Bitcoin history. OSC investor knowledge score: 53% correct - Average on 27 financial literacy questions for Canadian investors. SP Global FinLit score on same questions: 68% correct - The OSC study matched the earlier FinLit study exactly on those items. Investment cost knowledge: 36% correct - Lowest-scoring area in the OSC investor knowledge study. Portfolio protections knowledge: 44% correct - Second-lowest scoring area in the OSC investor knowledge study. Self-directed investor score: 59% correct - Highest literacy among the investor groups in the OSC study. Advisor-using investor score: 52% correct - Lower than self-directed investors in the OSC study. Robo-advisor investor score: 49% correct - Lowest literacy among investor channels in the OSC study. Women’s score: 50% correct - Compared to men’s 56% in the OSC investor knowledge study. Men’s score: 56% correct - Compared to women’s 50% in the OSC investor knowledge study. Participants lowering self-assessment after quiz: 31% - OSC study showed the questionnaire debiased a meaningful share of participants.

Pivotal Quotes: "smoothing as a service" — Benjamin Felix: Critiquing the illusion of lower volatility and smoother reported returns in private assets. "Actions express priority." — David Senra: Core principle behind his advice that people do what they truly value, not what they merely say they want. "Time is smarter than you." — Nassim Taleb (quoted by David Senra): Used to explain why time and historical persistence are key filters for judging founders and ideas.

Implications: Listeners should be skeptical of alternative-asset hype, fee structures, and advertised smoothing. For planners, conservative assumptions and manager-access realism matter; for investors, humility and literacy around costs, risk, and skew are essential.