Key Research

Our Value Proposition: Affordable Alpha

By | 2018-03-25T17:13:17+00:00 September 16th, 2014|Key Research|

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.

The Sustainable Active Investing Framework: Simple, But Not Easy

By | 2017-08-18T16:55:10+00:00 August 17th, 2015|Key Research, Behavioral Finance|

We cannot overemphasize that identifying sustainable alpha in the market is no cakewalk. More importantly, being smart, having superior stock-picking skills, or amassing an army of PhDs to crunch data is only half of the equation. Even with those tools, you are still only one shark in a tank filled with other sharks. All sharks are smart, all sharks have a MBA or PhD from a fancy school, and all the sharks know how to analyze a company. Maintaining an edge in these shark infested waters is no small feat, and one that only a handful of investors has accomplished. In order to achieve sustainable success as an active investor, one needs not only skill, but also an understanding of human psychology, and an appreciation of market incentives (behavioral finance). We start our journey where mine began: as an aspiring PhD student studying at the University of Chicago. Let the adventure begin... This post is not meant to convert a passive investor into an active investor; however, we do explain why we believe active investing can sustainably beat passive strategies in the long run. Plus, we bring to bear many years of cumulative research and experience to support our arguments. We cannot overemphasize that alpha in the market is no cakewalk. More importantly, being smart, having superior stockpicking skills, or amassing an army of PhDs to crunch data is only half of the equation. Even with those tools, you are still only one shark in a tank filled with other sharks. All sharks are smart, all sharks have a MBA or PhD from a fancy school, and all the sharks know how to analyze a company. Maintaining an edge in these shark infested waters is no small feat, and one that only a handful (e.g., we can count them in one hand) of investors has successfully accomplished. In order too achieve sustainable success as an active investing, one needs both skill and an understanding of human psychology and market incentives (behavioral finance). We start our journey where mine began: as an aspiring PhD student studying under Eugene Fama at the University of Chicago. Let the adventure begin...

Behavioral Finance and Investing: Are you Trying Too Hard?

By | 2018-01-17T15:28:08+00:00 May 13th, 2014|Key Research, Behavioral Finance|

Everyone makes mistakes. It’s part of what makes us human. Because humans understand their actions are sometimes flawed, it was perhaps inevitable that the field of psychology would develop a rich body of academic literature to analyze why it is that human beings often make poor decisions. Although insights from academia can be highly theoretical, our everyday life experiences corroborate many of these findings at a basic level: “I know I shouldn’t eat the McDonalds BigMac, but it tastes so good.” Because we recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied, for more than 60 years, the assumption that experts make unbias decisions. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts. This essay summarizes research related to the “models versus experts” debate and highlights its application in the context of investment decision-making. Based on the evidence, investors should de-emphasize their reliance on discretionary experts, and should instead approach investment decisions with systematic models. To quote Paul Meehl, an eminent scholar in the field, “There is no controversy in social science that shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one [models outperform experts].”

Value Investing: Never Buy Expensive Stocks. Period.

By | 2017-08-18T16:53:45+00:00 July 1st, 2014|Research Insights, Key Research, Value Investing Research|

We did a recent internal simulation study on the performance of cheap and expensive stocks based on a variety of valuation metrics. We looked at all our favorites from our Journal of Portfolio Management paper, [...]

The Quantitative Value Investing Philosophy

By | 2018-04-13T15:05:10+00:00 October 7th, 2014|Research Insights, Key Research, Value Investing Research, Introduction Course|

Benjamin Graham, who first established the idea of purchasing stocks at a discount to their intrinsic value more than 80 years ago, is known today as the father of value investing. Since Graham’s time, academic research has shown that low price to fundamentals stocks have historically outperformed the market. In the investing world, Graham’s most famous student, Warren Buffett, has inspired legions of investors to adopt the value philosophy. Despite the widespread knowledge that value investing generates higher returns over the long-haul, value-based strategies continue to outperform the market. How is this possible? The answer relates to a fundamental truth: human beings behave irrationally. We are influenced by an evolutionary history that preserved traits fitted for keeping us alive in the jungle, not for optimizing our portfolio decision-making ability. While we will never eliminate our subconscious biases, we can minimize their effects by employing quantitative tools.

Momentum Investing: Ride Winners and Cut Losers. Period.

By | 2017-08-18T17:00:14+00:00 July 16th, 2014|Research Insights, Key Research, Momentum Investing Research|

Momentum has historically been a great strategy. Although counter-intuitive to many value investors, buying stocks with rising prices has been a great investment approach--arguably better than value investing. Moreover, the approach is robust between the 2 samples analyzed. The lesson is clear: Let your winners ride and cut your losers short.

How to Combine Value and Momentum Investing Strategies

By | 2017-08-18T17:03:25+00:00 March 26th, 2015|Key Research, Value Investing Research, Momentum Investing Research, $SPY, $mtum, $vlue, $voo|

The evidence suggests that we keep highly active exposures to value and momentum in their purest forms (assuming we are doing high-conviction non-watered down versions of the anomalies). Blending the strategy dilutes the benefit of value and momentum portfolios. The summary of the benefits of a pure value and a pure momentum approach can be summarized as follows: Easier ex-post assessment, stronger portfolio diversification benefits, and stronger expected performance.

The Robust Asset Allocation (RAA) Index

By | 2018-05-02T07:36:07+00:00 December 2nd, 2014|Research Insights, Key Research, Introduction Course, Tactical Asset Allocation Research|

Robust asset allocation solutions should be relatively simple, minimize complexity, and be robust across different market regimes. Simultaneous to these requirements, the solution must be affordable, liquid, simple, tax-efficient, and transparent, otherwise, many of the benefits of the solution will flow to the croupiers and Uncle Sam. We recommend that investors explore our robust asset allocation framework and go for the do-it-yourself solution. You'll be paying yourself 1%+ a year via saved RIA fees. Is this the only solution? No. But any solution must be robust, simple, tax-manageable, and low-cost. This is our best effort to develop a simple model. Developing a complicated model is easy; simple is difficult.

Avoiding the Big Drawdown with Trend-Following Investment Strategies

By | 2018-04-17T15:51:18+00:00 August 13th, 2015|Trend Following, Research Insights, Key Research, Tactical Asset Allocation Research|

Simple timing rules, focused on absolute and trending asset class performance, seem to be useful in a downside protection context. Our analysis of the downside protection model (DPM), applied on various market indices, indicates there is a possibility of lowering maximum drawdown risk, while also offering a chance to participate in the upside associated with a given asset class. Important to note, applying the DPM to a portfolio will not eliminate volatility and the portfolio will deviate (perhaps wildly) from standard benchmarks. For many investors, these are risky propositions and should be considered when using a DPM construct.

How to Pick Smart Beta ETFs

By | 2017-08-18T17:03:18+00:00 October 24th, 2015|Research Insights, Key Research, Tactical Asset Allocation Research, Active and Passive Investing|

Investors are probably unaware of the price they are paying for the "active" piece of Smart Beta. Using a simple framework, we show that buying a Smart Beta product at 45bps is equivalent to paying 5bps for a generic passive exposure and 138.33 bps for the active exposure! How many investors are aware that "low-cost" smart beta products might be implicitly charging fees that are equivalent to many active mutual fund fees?

How many stocks should you own? The costs and benefits of Diversification

By | 2017-12-04T10:23:03+00:00 September 9th, 2014|Research Insights, Key Research, Tactical Asset Allocation Research|

In this post we explore the trade-off between diversification and alpha generation. Here is a high level summary of the situation: Owning more stocks in a portfolio lowers "idiosyncratic" risk, or risk that can be eliminated through diversification...however...Owning more stocks dilutes performance of an "alpha" generating process. (e.g., forcing Warren Buffett to hold a 500 stock equal-weighted portfolio would dampen his alpha). In summary, fewer stocks in a portfolio imply more expected alpha and more idiosyncratic risk; more stocks in a portfolio imply less expected alpha and less idiosyncratic risk. But what is the optimal trade-off between alpha and idiosyncratic risk? Do we want to own a 1 stock portfolio? A 50 stock portfolio? A 1000 stock portfolio?

Mission Impossible: Beating the Market Forever

By | 2017-08-18T17:00:48+00:00 November 18th, 2014|Research Insights, Key Research, Value Investing Research|

A quick glance at the most recent Berkshire Hathaway annual report (PDF) highlights an amazing data point: Warren Buffett has compounded at 19.7% a year from 1965 through 2013; the S&P 500 Total Return Index has compounded at 9.8% a year from 1965 through 2013. The immediate reaction to these figures is predictable: “Warren Buffett is an investing god, so we should buy Berkshire Hathaway and throw away the keys.” The gut reaction is that Buffett can continue to beat the market forever. Unfortunately, as this post highlights, this is an impossible feat.

A Framework for Investment Manager Selection: Stick to the FACTS

By | 2018-01-17T13:52:48+00:00 September 16th, 2014|Key Research|

Used car salesmen types are everywhere, especially in the asset management business. What defines the used car salesman? Used car salesmen are often focused on selling something—anything on their lots that has four wheels—rather than identifying the right vehicle for the client. The same holds true with the asset management business. Some asset management salesmen just want to sell something—anything, regardless of its suitability. Alpha Architect’s experience working with family offices in the dual role of consultant and investment manager has given us the opportunity to see a lot of indecipherable marketing materials and esoteric investment strategies over the years, neither of which appear to be in the best interest of the investor. We’ve always sought a simple framework that would facilitate a quick evaluation of any strategy that came through the door, but nothing really existed. Necessity is indeed the mother of invention: We developed our own framework for determining strategy selection and assessment. Our method is based on a few simple concepts, which should be clearly understood within the context of any investing approach, regardless of objective. In the end, choosing investment opportunities simply comes down to the FACTS.

How to Create a Tax-Efficient Hedge Fund

By | 2017-08-18T17:03:24+00:00 December 15th, 2014|Key Research, Value Investing Research|

The number of complex, optimized, and so-called "proprietary" value long/short strategies are too numerous to list. We've seen just about everything in our role as academics as well as consultants to an enormous family office. And of course, with fancy Manhattan offices, comes high fees, no transparency, and low liquidity (lockups). You'll also get great stories that are often backed by little to no empirical evidence. As we have shown before, trying to short expensive stocks is not a great idea! We think a simple solution to an investor's long/short equity woes is to focus on buying the cheapest, highest quality value stocks, and dynamically hedging the market risk with an S&P 500 futures (both the constant and dynamic hedge). Savvy investors can implement the solution we've proposed: buy a basket of the cheapest, highest quality value stocks and negate market risk with tax-efficient low-cost equity futures. And if you are simply too overwhelmed by portfolio management, we can implement the QVAR solution at a costs that is more affordable than the average long/short hedge fund offerings--especially on an AFTER-TAX BASIS!

Understanding How ETFs Trade in the Secondary Market

By | 2017-08-18T16:54:02+00:00 December 3rd, 2014|Key Research, Investor Education, Uncategorized|

An ETF's liquidity has everything to do with the underlying liquidity of the positions the ETF holds. This has a few implications: Pay attention to the liquidity on the holdings of your ETF--this will explain the spreads in the secondary market; Trade ETFs when the underlyings are liquid--avoid trading ETFs at the open or when overall market volume is lackluster; Avoid huge market orders, and stick to limit orders; Moreover, for huge trades, communicate directly with the market maker or your ETF trading desk.

From the Frontlines to Finance: How the Marines Shaped Our Investment Philosophy

By | 2017-09-28T12:22:13+00:00 May 25th, 2015|Research Insights, Key Research, $SPY|

Serving in the Marine Corps was an unforgettable experience. Civilians often tell us “thank you for your service”; however, the real “thanks” is due to the Corps for giving us valuable life lessons. The not-so subtle teachings bestowed upon us by heavily muscled, insanely aggressive Marine Corps Drill Sergeants are still, literally, ringing in our ears: “Listen here, pond scum, you better run faster, shoot straighter, and decide quicker if you are going to win in battle!” Years later, we would test that theory in real-time, battling insurgents in Iraq. As we trade in our flak jackets for laptops and neckties, the lessons learned in combat and are not only relevant, but vital on the battlefield of high finance. Four core lessons apply to frontlines and finance: Humans Are Emotional: Systematic processes beat behavioral bias; Rambo isn't Realistic: Act based on evidence, not on stories; Complacency Kills: Focus on fundamentals and never stop learning; Integrity is Everything: Do things right and do the right thing.

Distribution Economics: Understanding Wall Street’s Conflict of Interest Problem

By | 2017-08-18T17:06:44+00:00 March 11th, 2015|Key Research, $SPY, $wfc, $jpm, $bac, $c, $usb, $gs|

The simple matter is that most clients know how to buy groceries, but few know how to purchase financial products. In the murky world of financial services, clients may be buying products for the first time. More importantly, this purchase is the driver of their long-term financial security. Years of hard work, thrift, and responsible life choices, are baked into each and every retirement portfolio that a banker must now serve. In short, the stakes are too high and the cards are stacked too favorably towards one party. Fiduciary responsibility matters in financial services more than in any other product category outside of urgent medical care. Shouldn't this fiduciary have your best interests at heart? Just as you don't want your doctor to receive kickbacks from Pfizer for overdosing you on Oxycodone, why would you want your financial advisor--or their institution--to receive kickbacks for overdosing you on inefficient, overpriced, investment product that probably won't help you achieve your investment goals? Moral of the story: Ask your banker, or bank-affiliated advisor these questions. If you get answers that sound like the ones above, it might be time to buy a car or an airline ticket, because traveling via railroad is a thing of the past.

Rise of the Machines: Predicting Winners and Losers on the Robo-Advisor Battlefield

By | 2017-08-18T16:57:52+00:00 August 27th, 2015|Key Research, Tactical Asset Allocation Research|

Robos are changing the landscape of financial services and consumers will reap the rewards. But will the computers replace humans? Unlikely. The psychology coach benefit is hard to replicate with a computer. However, robos will encourage human-based advisors to up their game. Slothosaurus will go extinct—thankfully! First iteration passive robo-advisors will create a lot of value for consumers, but capture little value for their VC investors, unless perhaps they are bought out. Finally, differentiated robo advisors and traditional advisors who embrace technology will score big wins for both consumers and their shareholders.

The World’s Longest Trend-Following Backtest

By | 2018-01-16T20:53:30+00:00 November 9th, 2015|Trend Following, Key Research, Tactical Asset Allocation Research|

Were in the middle of an academic research project and we ran a simple long-term trend-following model from January 1, 1801 to September 30, 2015. Recently, there has been some research on the performance of trend-following rules [...]