What Do Systematic Fund Managers Actually Believe?
When it comes to investing, not all fund managers are created equal. Some believe markets are efficient and unbeatable. Others think predictable patterns — or anomalies — exist and can be exploited. These differences go well beyond marketing spin. They reflect core philosophical disagreements about how markets work and how best to invest in them.
In this post, we explore the foundational beliefs behind seven influential investment houses: RAFI, AQR, Dimensional, Avantis, Vanguard, BlackRock, and State Street. Together, they represent a spectrum of approaches — from pure indexing to rules-based strategies designed to capture long-term return premiums. But they don’t all believe the same thing. And that matters.
What Is a Market Anomaly?
In academic finance, an anomaly refers to a pattern in asset returns that appears to contradict the predictions of the efficient market hypothesis (EMH). In other words, it’s a regularity that, if real and persistent, could be used to generate above-market returns — without inside information or speculation.
Classic examples include:
Value: Cheaper stocks (by price-to-book or price-to-earnings) tend to outperform expensive ones.
Size: Smaller companies tend to outperform larger ones over the long run.
Momentum: Stocks that have gone up recently often continue to outperform in the near term.
Profitability: More profitable firms tend to earn higher risk-adjusted returns.
Low Volatility: Stocks with lower volatility sometimes produce better risk-adjusted returns than high-beta stocks.
These are not one-off occurrences — they’ve been studied and replicated across different countries, asset classes, and over decades. But not everyone agrees they can be captured in portfolios, after costs and taxes.
Market Efficiency vs Exploiting Anomalies
The efficient market hypothesis (Fama 1970) suggests that asset prices fully reflect all available information. If true, then trying to ‘beat the market’ is a fool’s errand. Instead, investors should aim to own the market at the lowest possible cost.
This view underpins the rise of passive investing, championed by the likes of Vanguard. But a large and growing body of evidence — built by academics like Eugene Fama, Kenneth French, Cliff Asness, Robert Novy-Marx, and others — suggests that certain traits or factors offer higher expected returns over time. The question is: are these inefficiencies real and exploitable? Or do they simply reflect compensation for taking on different kinds of risk?
The firms we’ll compare sit at different points along this philosophical divide.
Philosophies of Seven Systematic Managers
Passive, Factor-Based, or Quant Active?
Let’s break this down by approach:
Vanguard, BlackRock, and State Street are primarily market-cap indexers. They believe in holding the entire market and minimising costs. Although they offer smart beta and active ETFs, their philosophy is rooted in the idea that prices mostly reflect true economic value.
Dimensional and Avantis believe in systematic factor tilting — not forecasting, but adjusting portfolio weights towards parts of the market (e.g. smaller, cheaper, or more profitable companies) with higher expected returns. They don’t try to outguess the market; they simply structure portfolios to lean into known premiums.
RAFI takes a different tack. Instead of weighting portfolios by market price, they use fundamental measures like revenue, cash flow or dividends. The idea is that price signals are noisy, and anchoring to economic size can help avoid overpriced stocks.
AQR goes furthest: it uses quantitative signals to build multi-factor portfolios that are dynamically adjusted. Whilst still systematic, AQR is more active than the others, and more comfortable deviating from traditional benchmarks.
What Makes This Debate Important?
If markets are efficient, then the rational choice is low-cost market exposure. That’s what Vanguard popularised — and it works remarkably well.
If anomalies are persistent and exploitable, then structured tilts can help improve expected returns. But only if they’re done systematically, tax-efficiently, and without costly guesswork.
If markets are inefficient in more complex ways, then quantitative active management may have a role — but it’s harder to do well and can be more expensive.
So, What’s the Evidence?
There’s strong evidence that factors like value, momentum, and profitability have delivered higher long-term returns — across decades, geographies, and asset classes (Fama and French 1992; Asness, Moskowitz, and Pedersen 2013). But how best to capture these effects in practice remains a subject of debate.
Dimensional and Avantis use these insights to build portfolios that favour persistent drivers of return, whilst avoiding unnecessary complexity.
RAFI argues that fundamentals — not prices — are the best anchor for portfolio weights.
AQR builds on all of the above, adding dynamic signals and sophisticated implementation. But that complexity comes with higher costs and sometimes, underwhelming returns.
Vanguard asks: why try to outsmart the market when you can just own it for as little as 0.03%?
Final Thoughts
Understanding the beliefs behind a fund manager’s process matters. Are they trying to outguess the market, tilt towards long-term factors, or simply provide the cheapest access to broad exposure?
At a glance, these firms may all look systematic, low-cost, and evidence-based. But under the hood, they operate with very different philosophies:
Vanguard is the benchmark for passive investing: minimise cost, maximise breadth, and avoid unnecessary complexity. It believes markets are mostly efficient — but offers low-cost active options for investors seeking more.
BlackRock (iShares) and State Street (SPDR) are similar in spirit, offering a broad suite of market cap-weighted ETFs, along with smart beta and factor-based products. Whilst not research innovators in the same way as AQR, Avantis or Dimensional, their scale, liquidity, and product breadth make them valuable tools for building efficient portfolios.
Dimensional and Avantis use decades of academic research to systematically tilt portfolios towards higher expected returns (value, size, profitability), without timing or forecasting.
RAFI rejects market prices as the primary input, choosing to weight portfolios based on economic fundamentals like revenue or cash flow — a contrarian view that seeks to avoid valuation-driven distortions.
AQR goes furthest, using quantitative models and dynamic factor exposures to pursue return premiums across equities, bonds, and alternative strategies — with more active decisions and complexity than the others.
None of them promise to beat the market every year. But they do offer diverse and thoughtful ways to structure portfolios based on how they interpret market behaviour.
References
Arnott, Robert D., Jason Hsu, and Philip Moore. 2005. ‘Fundamental Indexation.’ Financial Analysts Journal 61 (2): 83–99.
Asness, Clifford S., Tobias J. Moskowitz, and Lasse Heje Pedersen. 2013. ‘Value and Momentum Everywhere.’ Journal of Finance 68 (3): 929–85.
Berkin, Andrew L., and Larry E. Swedroe. 2016. The Incredible Shrinking Alpha: And What You Can Do to Escape Its Clutches. Petersfield: Harriman House.
Fama, Eugene F. 1970. ‘Efficient Capital Markets: A Review of Theory and Empirical Work.’ Journal of Finance 25 (2): 383–417.
Fama, Eugene F., and Kenneth R. French. 1992. ‘The Cross‐Section of Expected Stock Returns.’ Journal of Finance 47 (2): 427–65.