Episode 360 – Gerard O'Reilly: The Components of Net Returns

Episode Summary

Executive Summary: Gerard O’Reilly explained how Dimensional’s approach differs from passive indexing: both use rules, but Dimensional adds daily implementation flexibility, broader universe design, and intentional exclusions to improve net returns. The discussion emphasized that fees matter, but trading costs, taxes, securities lending, corporate actions, and market definitions also materially affect investor outcomes.

Main Topics: Dimensional’s philosophy vs. cap-weighted indexing (Priority: 5/5): O’Reilly framed Dimensional as rules-based but more dynamic than indexing, using daily prices and implementation flexibility to improve returns and manage risk rather than mechanically tracking an index. Components of net returns (Priority: 5/5): He broke net returns into four parts: two return-enhancing levers (asset allocation and implementation) and two return-dragging costs (implementation costs and expense ratio), arguing investors too often focus only on fees. Defining the market and universe construction (Priority: 5/5): The conversation covered how market definitions vary by free float, liquidity, exchange standards, and listing status, and how these choices materially affect portfolio composition and returns. Intentional exclusions and expected return tilts (Priority: 4/5): Dimensional excludes low profitability, high asset-growth, some IPOs, and often REITs in the U.S. when doing so improves expected returns, tax efficiency, or portfolio implementation. Trading, securities lending, and corporate actions (Priority: 5/5): O’Reilly described how flexibility helps capture trading advantages, securities lending revenue, and manage mergers, buybacks, and index-related turnover more efficiently than index funds. Fees, value for service, and investor outcomes (Priority: 4/5): He argued the industry over-weights expense ratio and under-weights implementation quality, noting that better execution can offset higher fees and that investors should evaluate total value delivered. Portfolio products and tracking-error trade-offs (Priority: 4/5): The discussion closed with how Dimensional builds both market-like products and higher-tilt products, allowing clients to choose the level of expected outperformance versus tracking error.

Key Arguments: Dimensional and indexing both start with rules, but Dimensional uses daily pricing and flexibility to reduce frictions and improve net returns. Focusing only on expense ratios misses major drivers of investor outcomes such as trading costs, taxes, securities lending, and corporate-action management. Market definitions are not fixed; free float, liquidity thresholds, and exchange filters can materially change what counts as the market. Low-profitability, high-price, and high-asset-growth small caps have historically underperformed, so excluding them can improve expected returns without sacrificing much diversification. REITs can be separated for tax reasons because their income is taxed differently, improving after-tax results when located correctly. Securities lending can create meaningful revenue for investors, and Dimensional passes that revenue to clients rather than keeping it. Corporate actions like mergers create hidden cash drag in portfolios, and active implementation can reduce that drag. Index reconstitution creates measurable price pressure and trading costs that are embedded in index returns even if fund expense ratios look very low. Dimensional’s goal is not traditional stock picking but engineered portfolio design based on empirical evidence and implementation skill. Higher tracking-error products can target larger expected premiums, but investors must tolerate more periods of underperformance to get that long-run benefit.

Data Points: Dimensional relationship in Canada: 23 years - PWL Capital has used Dimensional since it came to Canada 23 years ago. Gerard O’Reilly joined Dimensional: 2004 - O’Reilly joined Dimensional after moving from academia to finance. Co-CEO appointment: 2017 - He became co-CEO and works alongside Dave Butler. Academic background: Master’s in high-performance computing; PhD in aeronautics from Caltech - Described to underscore his technical background. US broad market index return gap: ~30 bps average; as high as ~1% - Difference between highest- and lowest-returning broad US indices over 20 years. Developed ex-US broad market index return gap: ~1% average; as high as ~3-4% - Index-definition differences matter more outside the US. Emerging markets broad index return gap: ~3% average; as high as ~6-7% - Return spread among broad market indices is widest in emerging markets. US small-cap index return gap: ~5% average; >10% in some years - Different small-cap index definitions can produce very different outcomes. US market eligible securities in Dimensional core: ~3,500 names at starting market; ~2,500 after exclusions - Broad US universe and excluded securities for core-style implementation. Global Dimensional portfolio universe: ~13,500 securities - Approximate number of names in a global portfolio universe. MSCI ACWI IMI comparison: ~8,000 to 8,500 stocks - Dimensional’s global universe is larger than this broad market benchmark. Market cap excluded in US broad portfolio: ~20 to 30 bps expected improvement - Estimated impact of exclusions like low-profitability growth, REITs, and IPOs. High asset growth / low profitability underperformance: ~5% to 10% per year - Historical underperformance of certain small-cap subsets Dimensional excludes. REIT tax benefit: ~5 bps after-tax - Estimated after-tax benefit from separating REITs in the US. IPO exclusion window: ~6 to 12 months - Dimensional typically waits before considering IPOs for inclusion. Securities lending revenue (overall): ~4 bps last year - Across Dimensional’s equity complex. Securities lending revenue by market: US ~2 bps; developed ex-US ~5-10 bps; emerging markets ~15 bps - Market-specific lending revenue contribution. Trading price advantage vs others: US large caps 5-10 bps; US small caps 10-20 bps; non-US developed ~20 bps; emerging markets up to ~30 bps - Estimated advantage from Dimensional’s trading implementation. Index reconstitution price effect: ~4% run-up for additions; ~4% underperformance for deletions - Measured around pure index additions/deletions, then reversing after reconstitution. Tesla S&P 500 inclusion date: December 21, 2020 - Used as a concrete example of index inclusion effects. DFUS expense ratio: 9 bps - Dimensional U.S. market ETF referenced in comparison to a 3 bp index fund. Expected outperformance for DFUS since ETF conversion: ~50 bps to ~100 bps annualized - Conversation notes performance since ETF conversion and across strategies. Core expected outperformance / tracking error: ~1% to 2% expected outperformance; ~2% to 4% tracking error - Rough quote for core products. Vector expected outperformance / tracking error: ~2% to 3% expected outperformance; ~6% tracking error - Rough quote for higher-tilt products. Small-cap strategy long-run alpha: ~1.5% annualized over 40+ years - Example of Dimensional small-cap strategy outperforming its benchmark net of fees. Institutional mandates won in 2024: ~$18 billion - New mandates from investors moving away from pure indexing. Dimensional performance metric: >80% of U.S. funds over 20 years outperformed prospectus benchmarks - Used to argue value for service versus low-cost indexing. Industry survival comparison: ~50% industry survival vs. 100% for Dimensional funds in the cited cohort - Used to highlight product persistence and survivorship. Market liquidity: >$800 billion traded daily worldwide - Explained why flexibility and participation can reduce trading costs.

Pivotal Quotes: "We consider ourselves master implementers in terms of how we can take an investment thesis and bring it to life in the real world." — Gerard O’Reilly: Describing Dimensional’s differentiation from pure index replication. "When you have a myopic focus on expense ratio and you forget about the other components of net returns, you may be leaving returns on the table that your clients could quite reasonably ensure." — Gerard O’Reilly: Arguing that fees are only one part of investor outcomes. "Practice makes progress. You can never be perfect." — Gerard O’Reilly: A personal anecdote illustrating Dimensional’s continuous-improvement mindset.

Implications: Listeners should evaluate funds on total net return, not just headline fees or index labels. For the industry, the conversation supports more attention to implementation, taxes, and hidden costs; for investors, it suggests that low-cost, rules-based active implementation may outperform plain indexing over time.