Our Value Proposition: Affordable Alpha

Our Value Proposition: Affordable Alpha

September 16, 2014 Key Research
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(Last Updated On: June 20, 2017)

Our mission is to empower investors through education. This mission is our passion and what drives us to go to work everyday.

But this mission is not our product.

Our product is Affordable Alpha: We seek to delivers alpha (highly differentiated risk/reward profiles) at low costs, thereby giving sophisticated (taxable) investors a higher chance of winning net of fees and taxes.

Note: Here are some high-level background documents on our firm

Why Affordable Alpha?

We are based outside of Philadelphia, roughly 15 minutes from Vanguard’s campus.

Vanguard is a monster in the region and we have a keen understanding of their business model and vision for financial services.  We love their vision of the future: transparency, affordability, and client-focus.

We are also smart enough to know we can’t eat Vanguard when it comes to delivering cheap access to non-differentiated uber-scalable investment products. Firms we respect, such as DFA, AQR, and Blackrock, are learning this lesson the hard way and watching their margins erode away.

So, with the benefit of hindsight, we’ve chose a different tack: go where the profit margins are fat and Vanguard can’t easily compete — highly differentiated, limited capacity, active management. Think concentrated mutual funds and traditional hedge fund managers.(1)

We looked at the boutique active management industry and channeled our inner Jeff Bezos:

Your margin is my opportunity.

But after assessing the boutique active management industry, we quickly realized why the management fees were so high on these products: distribution costs. These products are all sold, not bought. And sales people are extremely expensive. We decided to invert the problem. Let’s make our products be bought, not sold. We’ll leverage our background as researchers and educators to inform the public about our strategies and they’ll come to us. We’ll minimize traditional distribution costs and have an opportunity to deliverable more affordable alpha-focused active management products.

A firm was born.

We think active management can work for the investor, not just the fund manager and the fund salesmen! We can make active investing affordable, transparent, and intellectually honest.

We can deliver Affordable Alpha:

  • Affordable: Non-scalable active strategies are scarce and expensive to produce. These products can never be priced like a Vanguard fund, but they also don’t need to be “two and twenty.”
  • Alpha: Portfolios need to be different to be differentiated. We are not closet-indexers (e.g., “smart beta”) and we build portfolios that seek to deliver unique risk and reward profiles.


Important to note: Our products will be delivered in the context of a broader mission to empower investors via education and we will adhere to our four core beliefs of 1) transparency, 2) systematic decision-making, 3) evidence-based investing, and 4) win-wins.

Understanding the Asset Management Landscape

Our hope is that the framework we outline below will allow investors to differentiate among investment management products based on a few key characteristics.

First, let’s define a few concepts that are central to understanding the investments industry:

  • Alpha: Formally, alpha represents the intercept estimate from a regression of an investment strategy against various risk-factors. In practice, alpha is an exposure to a differentiated risk/return profile (which is highly valuable for a diversified portfolio).
  • Tracking Error: Tracking error is defined as the standard deviation of the difference between a strategy’s returns and a benchmark’s returns. In other words, tracking error is a measure of how closely a portfolio follows, or “tracks,” an index. One can also think of tracking error as the level of benchmarking risk. To the extent one cares about being close to a benchmark, tracking error is important.
  • Active Share: This measure quantifies the extent to which a manager reshapes a portfolio with respect to a benchmark. Active Share is a formal calculation developed by Cremers and Petajisto (2009), but a good proxy is simply the number of securities in a portfolio. For example, a manager that holds 50 equally-weighted stocks will likely have a much higher Active Share than a manager that holds 500 market-weighted stocks.(2) Active Share is related to Tracking Error and both of these concepts are useful depending on an investor’s investment objective.
  • Passive Index: By construction, passive index portfolios are designed to have no differentiation. A good example of an index strategy is the Vanguard S&P 500 Index Fund. This fund does not attempt to add Alpha, but seeks to match the performance of the S&P 500 index with minimal tracking error. Here is a post on the subject.

With some basic concepts under our belt, we can now explore the asset management industry. We break the industry into three main categories:

  • Passive Index Products: Index (“Passive”) products offer no alpha, no tracking error, and no Active Share.
    • These funds, typified by Vanguard’s products, have a high number of securities, low expense ratios (<20bps), and low marketing costs.
  • “Closet Index” or “Smart Beta” Products: Closet Index products, sometimes referred to as “smart beta,” offer little differentiation, little tracking error, and little Active Share.
    • These funds typically have a large number of securities, low to high-level expense ratios (25-100bps), and high marketing costs.
  • Active Products: Active products, often delivered via mutual fund or hedge fund vehicles, are characterized by high expected alpha, high tracking error, and high Active Share.
    • These funds have a low number of securities (<50), high expense ratios (75bps – 200bps+), and extremely high marketing costs.

To win in the Passive Index game one needs to be Vanguard. To win in Closet Index / Smart Beta or Active an asset manager needs to be a marketing machine. Alpha Architect is not Vanguard and is not a marketing machine. So we are creating our own category: Affordable Alpha.

  • Affordable Alpha Products: Alpha Architect products are characterized by limited scalability, high expected alpha, high tracking error, and high Active Share.
    • These funds are backed by intense research efforts, mid-level expense ratios, and limited marketing costs.

The 4 different categories of asset management products are summarized in the table below:


All 4 categories can serve the investor, with varying costs/benefits to each. We are not competing with Passive Indexers, or Closet Indexers / Smart Beta. So we will not directly comment on the validity of these approaches. Our competitive angle is squarely targeted on expensive active strategies and our mission is to make these high expected performance strategies more affordable.

What We Seek to Deliver: Affordable Alpha

Two words define what we seek to deliver: Affordable, Alpha. We will briefly describe what we mean by each of these terms. First we discuss the most important aspect of what we do: generate alpha. Next we will discuss affordability and why costs matter.

Our goal is to highlight Alpha Architect’s product goal, which is to deliver higher net returns for long-term investors in active products.


Condition #1: Be Different

Charlie Munger, at the 2004 Berkshire Hathaway Annual Meeting, is quoted as saying, “The idea of excessive diversification is madness…almost all good investments will involve relatively low diversification.” An underlying assumption of Munger’s quote is that the investor who does not diversify must possess investment skill. Another word for Munger’s issue with diversification for a skilled manager is “diworsification.”

Here is a high level summary of the diworsification problem:

  • Owning more stocks can lower a portfolio’s risk profile (i.e. beneficial).
  • Owning more stocks can dilute performance (i.e. costly).

Munger’s remarks are backed by evidence: We have posts on value and momentum strategies and highlight the direct relationship between portfolio concentration and past performance.

But what is the optimal trade-off between performance and idiosyncratic risk?

Let’s first tackle idiosyncratic risk. Idiosyncratic risk is the risk we can eliminate via diversification. Idiosyncratic risks are risks that are uncorrelated with other risks. Examples include a building catching on fire, a hurricane, or a CEO death. But idiosyncratic risk cuts both ways: a company can benefit from, say, a favorable lawsuit outcome, or a positive FDA ruling. When investors hold a large portfolio of stocks, these idiosyncratic risks–which are unrelated–cancel each other out, on average.

Systematic risks, unlike idiosyncratic risks, are risks we can’t easily diversify away. An example might be the risk that the general economy goes into a depression. If people in the economy aren’t spending money, this affects all companies–we can’t hold a bunch of companies and eliminate this risk since they are all affected by the economy.

To get a better sense of how increasing portfolio size affects portfolio volatility in the context of stocks we simply look to the academic literature. Elton and Gruber have multiple papers and books on the subject. (3)

The figure below, built with data from the original Elton and Gruber paper, highlights the relationship between portfolio size and risk. Notice that the portfolio risk goes down as the portfolio size increases; however, risk never goes to zero and the benefits to holding a bigger portfolio decline rapidly after the portfolio grows beyond 50 securities. So while we are protected by some diversification, we may not want too much.

30 to 50 stocks is a sweet-spot where an investor eliminates portfolio idiosyncratic volatility. Additional diversification beyond this point does not help reduce volatility in any dramatic way. By diversifying beyond 30 to 50 stocks, we prevent our portfolio from concentrating on stocks we feel are “undervalued.” For example, we probably want Warren Buffett to hold at least a small portfolio of stocks–to ensure he doesn’t completely blow up–but we don’t want to force him to hold more stocks, because it is unlikely he has more than 50 good ideas. If we forced him to diversify beyond 50 positions, we would dilute his alpha.

To explore the relationship between the number of portfolio holdings and alpha, we conduct an experiment. We examine a simple high-performance value factor: EBIT/TEV (a version of enterprise multiple). There is a clear historical relationship between EBIT/TEV and future stock returns. High EBIT/TEV stocks earn higher returns than low EBIT/TEV stocks. We will not argue whether this extra return earned by high EBIT/TEV stocks (value stocks) is due to mispricing or fundamental risk, but for exposition purposes, we can agree that this is an empirical fact.

First, a quick description of the study we conduct from 1964-2013. We identify firms above the NYSE 40th percentile for market capitalization that have information to calculate enterprise multiples. In 2013 terms, this equates to a universe that looks at stocks with a market capitalization of ~$2B and up. With our universe of mid to large cap firms, we split firms into three differently sized portfolios based on EBIT/TEV measures: Top third EBIT/TEV (~279 stocks), Top quintile EBIT/TEV (~167 stocks), and Top decile EBIT/TEV (~83 stocks).

In the table below we display the summary statistics for the following three portfolios (here is the source):

  • EBIT Cheap Decile = Value-Weight, monthly re-balanced portfolio of cheapest 10% of EBIT/TEV stocks
  • EBIT Cheap Quintile = Value-Weight, monthly re-balanced portfolio of cheapest 20% of EBIT/TEV stocks
  • EBIT Cheap Tercile = Value-Weight, monthly re-balanced portfolio of cheapest 33% of EBIT/TEV stocks
Summary Statistics Cheap Decile Cheap Quintile Cheap Tercile
CAGR 15.72% 14.42% 13.43%
Standard Deviation 17.64% 16.02% 15.25%
Sharpe Ratio (RF=T-Bills) 0.64 0.61 0.58

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The results in the table highlight that more concentration increases compound annual growth rates, but also increases volatility. The increase in volatility is expected, because the smaller portfolios are less diversified. But what is the tradeoff between returns and volatility? The Sharpe ratio is one commonly used measures to calculate the tradeoff between returns and volatility. Based on Sharpe ratios, the evidence suggests that concentration is a better risk-adjusted bet. You get a net performance boost by concentrating your holdings in strategies that earn higher risk-adjusted returns. Munger is right: to the extent you believe you have a reliable method of constructing a high alpha “active” portfolio, less diversification is desirable and often cheaper.

Condition #2: Have an Edge

Formally, alpha, or “edge,” represents a result from a regression analysis. Specifically, alpha is the intercept estimate associated with a factor regression using an investor’s favorite factor model (see here for an in-depth discussion). Informally, “alpha” can be interpreted as skill, luck, and everything in between. We use the term with apprehension because alpha is a loaded term that evokes knee-jerk reactions from investors that have been trained to think in a particular way. We take no strong stance of whether alpha reflects unique risk exposure, systematic mispricing, or a blend of both effects. To us, alpha simply represents an attractive investment opportunity that is difficult to exploit for behavioral reasons.

In order to counteract our behavioral urges, we believe in extreme investor education and following systematic processes. But why do we even care about beating behavioral bias? The answer lies within the academic research underlying the field of behavioral finance. The central premise of behavioral finance is that human behavior can influence investment decisions, sometimes in ways that hurt investors. For most of you, this idea is probably not surprising. Warren Buffett is attributed as saying that investing is simple, but not easy. Similarly, integrating our understanding of human behavior into an investment process is simple, but not easy.

How, specifically, does our behavior impact stock prices?

Despite our best intentions, human behavior is not always governed exclusively by rationality. In particular, our judgment and decision-making can be significantly affected by intuition, a form of abstract, automatic thinking that can override our reason. Faulty intuition and other forms of investor irrationality can cause us to do the wrong thing and can also create mispricings in the market. One example of behavioral bias affecting stock prices is representative bias, or the human tendency to extrapolate short-term patterns and ignore long-term trends. Academic research shows that representative bias likely explains part of the “value premium,” which is the descriptive term for the large spread in realized returns between value stocks and growth stocks.(4)

But behavioral finance is not solely focused on understanding the complex psychology behind decision-making. Bias is a necessary, but not a sufficient condition, to provide smart investors with an opportunity to profit using behavioral finance. The second building block of behavioral finance requires an understanding of market frictions, often referred to as the “Limits of Arbitrage.”(5)

This multi-element behavioral finance opportunity process is depicted in the figure below:

For illustration purposes only.

The two building blocks of behavioral finance–understanding bias (bad poker players) and arbitrage restrictions (good poker player restrictions)–combine to create opportunities for savvy long-term investors. To understand why both building blocks are important we need to understand the Efficient Market Hypothesis (the “EMH”). EMH claims that market prices reflect all publicly available information about securities. When mispricings occur in markets, they will immediately be eliminated by smart investors, who exploit these opportunities for a profit. Therefore, in the EMH view, prices will always reflect fundamental value–even when some market participants suffer from extreme behavioral bias. But we feel a strict interpretation of EMH is flawed, since it assumes arbitrage costs are zero. In reality, exploiting investment opportunities created by irrational investors is not easy, and the ability of smart investors to “arbitrage” profitable opportunities can be limited in the short-run. Our investment strategies systematically exploit these opportunities when professional investors, or “smart money,” are unable to exploit long-duration investment opportunities because they are hamstrung by their short-horizon investors. We explain this philosophy in great detail in our sustainable active investing piece. We also like to emphasize why our two biggest focus areas — concentrated value and momentum — can have terrible bouts of relative underperformance.(6)


Warren Buffett obliquely references the concept of affordability in the context of stock-picking:

It’s far better to buy a wonderful company at a fair price than a fair company at a wonderful price.(7)

Most people understand the concept of affordability when they shop at the grocery store, but lose sight of it when they shop for financial services. A shopper focused on affordability weighs both the costs and the benefits of a purchase decision.(8) By contrast, a “cheap” shopper only focuses on costs, and an “expensive” shopper only focuses on benefits. The figure below highlights why being an affordable-minded consumer of financial services is a good financial decision. In this hypothetical example, we have a cheap index portfolio that earns 6% annual returns and costs 0.25% a year, an affordable active portfolio that earns 7% annual returns and costs 0.75% a year, and an expensive active portfolio that earns 7% annual returns and costs 1.50% a year.(9) The example highlights that weighing both costs (affordability) and benefits, matters for your overall investment performance. Costs matter, always.(10)

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Additional information regarding the construction of these results is available upon request.

This all sounds great, but one question remains:

How can we deliver high value services at lower costs than the competition?

We deliver affordability by reinventing the way business is done in the financial services industry.

  • We seek to minimize distribution costs. Intermediaries should add value, not extract it.
  • We leverage technology to maximize efficiency. “Computers good, people bad.”(11)
  • We maintain a culture of doing more with less.(12) In other words, you’ll find us driving Honda Civics, not Ferraris.

Over time other asset managers will evolve to embrace technology and perhaps they will give up on their high-priced overhead. At least one would hope. But the real disruption in financial services revolves around distribution and going direct to consumer (e.g., individual investor or their advisor). Distribution is currently extremely expensive in financial services and the clients pay the bill in the form of direct or indirect costs. The traditional model relies heavily on an intermediary. First, an asset manager develops an investment strategy (labeled “Strategy”), which is distributed by some means (labeled “Distribution”) to the investment public (labeled “Consumer’). A well-intentioned asset manager that wants to charge 75bps for a high-performance active product could be faced with a 75bp distribution fee, making the total product costs to the consumer 150bps, or 1.5%. Half of this fee goes to the strategy manager, and half of the fee goes to the middleman sitting in the center of the transaction. And while this example is hypothetical, it captures the spirit of the mutual fund and hedge fund industries. The consumer pays twice: once for the development of the strategy, and once for a middleman, whose role is to sell the complex product.

One thing is transparent: The asset manager and the consumer would both be better off if they could cut the middle-man from the picture. The client would save 75bps in distribution fees and the asset manager would have direct access to the client. This direct-to-consumer model is visually depicted in the figure below, and we think it represents the future of the financial services industry. A disintermediated business model is less conflicted (i.e., fewer broker/dealer incentive issues) and helps deliver affordability.

How do we go direct to consumer?

We are focused on inbound marketing, in other words, we tell people what we do, why we do it, and how we do it, and they reach out to us for further information, if desired (see our active robo example). Our products are designed to be bought, not sold. Our approach efficiently taps into a self-selected group of investors who understand and appreciate our value proposition.

Our marketing approach is antithetical to the traditional model. The common jargon in the asset management industry is that investment products are “sold, not bought.” Translation: Our sales people are going to annoy you until you succumb to the pressure and push the “buy” button.

Our marketing model is direct-to-consumer oriented and eliminates a large distribution cost associated with hiring teams of wholesalers and/or paying banks via veiled kickback schemes. We can direct these saving back to clients in the form of more education, more research and development, more affordability, and better technology. The figure below contrasts the “old model” of the financial services industry with our approach (“AA model”).

As alluded to earlier, minimizing distribution costs aren’t the only way we can minimize costs. In addition to evolving the distribution model in financial services, our dedication to a low-cost infrastructure and reliance on technology, ensures our viability as a going concern and also allows us to maintain a lower overall cost structure than our competition in the active management space. We are open to having expensive office space and a personal assistant at the disposal of every portfolio manager. Box seats at every major sporting event? Sounds like a great time! But here’s the problem: these costly events don’t add value to an investment portfolio and they impose costs on a client via higher operational costs. The money would be better spent on research and development or on technology to improve our offerings.


We believe that financial services will be more competitive, transparent, and client-friendly in the future. We want to be on the forefront of this new paradigm in investment management. Our particular focus is on the active management sector and our desire is to create a new category: Affordable Alpha. Alpha Architect seeks to generate higher net returns for long-term buy-and-hold investors in active products.

In order to have confidence in our approach, which are often unique and highly differentiated from others in the marketplace, one must understand our investment processes and the research underpinning our entire process (our books and blog posts are a great place to get started).

We believe our approach to the markets is effective for sophisticated, long-term, and disciplined investors seeking to achieve something different than the opportunities provided by generic passive indexes or closet-indexing funds. We call these investors “sustainable clients.” The central belief behind our “edge” is that we can couple patient and discipline capital with our innovative strategies. We believe we can achieve this by educating clients and making them better investors.

Note: This site provides NO information on our value investing ETFs or our momentum investing ETFs. Please refer to this site.

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Please remember that past performance is not an indicator of future results. Please read our full disclosures. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. This material has been provided to you solely for information and educational purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and Alpha Architect to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission from Alpha Architect.

Definitions of common statistics used in our analysis are available here (towards the bottom)

References   [ + ]

1. By “active” we mean very different than the market, not human stock pickers, per se. See here for details on the difference.
2. Cremers, K.J. Martijn, and Antii Petajisto, 2009, How Active Is Your Fund Manager? A New Measure That Predicts Performance, Review of Financial Studies 22, p 3329–3365.
3. Elton, E. and Martin Gruber, 1977, Risk Reduction and Portfolio Size: An Analytical Solution, The Journal of Business 50, p 415-437.
4. Lakonishok, J., A. Shleifer, and R. Vishny. 1994. Contrarian Investment, Extrapolation, and Risk. Journal of Finance 44:1541–78.
5. Schleifer, A. and R. Vishny, 1997, “The Limits of Arbitrage,” The Journal of Finance 52, p. 35-55.
6. Here is the value version of the same story.
7. Buffett, W., “Chairman’s Letter,” Berkshire Hathaway Inc. Annual Report, 1989.
8. A non-financial example being a set of quality tools. While initially the good set of quality tools costs more, in the long-run the consumer is better off purchasing the good quality tools, as the cheap tools break and need to be purchased again.
9. We assume the active process can generate excess returns due to taking on unique risk premium and/or exploiting mispricing.
10. see this Vanguard report on making active management work
11. Quote from an old friend and early client of Alpha Architect.
12. Full credit to the United States Marine Corps for teaching me this.

About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.


    Nice work Wes. Compelling thesis. I was listening to Charley Ellis today on Capital Allocators Podcast. He’s adamant that alpha has all been arbed away by technology, MBAs, CFAs etc. There are too many smart people in the market chasing alpha; of course not saying you are not smart but with 85% US and 87% UK fund managers failing to beat their benchmark over the medium to long term, one wonders if firms can eek out any alpha net of associated costs in finding that edge/alpha in the first place? Have you read ‘Looking for Easy Games’ Jan 4 2017 by Mauboussin ? The paper recommends Active managers, ‘be active’ and invest in their best ideas; think long term; and, use quantitative methods (he must be a fan of yours!). Best of luck with the approach/strategy

  • This is something I think about all the time. The hypothesis is compelling.
    I’ve got a fairly extensive post I’m working on that will discuss this hypothesis. I think there are cracks in the assumptions.
    First, smart people chase alpha. That is debatable and the principal/agent conflicts are getting more extreme. See here: http://blog.alphaarchitect.com/2017/04/26/academic-factor-exposure-versus-fund-factor-exposure/
    Second, capital is overwhelming factors. See here: http://blog.alphaarchitect.com/2017/02/17/will-etfs-destroy-factor-investing-nope/
    Third, the set of active managers studied are representative of high active share, highly differentiated active managers doing something different.

    All that said, the mega-cap size factor fund with a beta =1 has paid the highest premiums over the past 15 years, on average. No doubt about that. Will that continue in the future? Who knows. But I’d guess that won’t be the case over the next 15-20yrs


    Thanks Wes; looking forward to the lengthy post. If the robots have their way and the ultimate aim of capitalism is to drive down costs ( greater automation, lower fixed wage costs) one wonders how the investable universe and associated capital levels might change in the future!

  • This old chart from Geczy’s/Samanov paper is pretty puzzling for the “technology/smart people are driving premiums to zero” hypothesis. One would need to argue that in the 1850’s everyone figured out momentum investing, put their super-computers in place, and decided to destroy the premium. That seems like a stretch. Perhaps the reality is these premiums are driven by risk factors and/or systematic mispricing that is really hard to arbitrage. That hypothesis seems more credible.
    Anyway, these are competing hypothesis that can and should be discussed. I’m on the ‘extra risk + tough to arb mispricing” fence. But could be wrong. Maybe the markets are perfectly efficient these days, both on a short term basis and a long-term basis.