Andy Kern, Senior Portfolio Manager, New Age Alpha Jan 18, 2021 7:00:00 AM 17 min read Academic Research

The New Age Alpha Investment Methodology

Learn to avoid the losers by taking an actuarial approach to stock selection.

Stock prices are affected by human behavior. We believe this creates a risk that investors are not compensated for taking, a risk we call the Human FactorTM. Using a probability-based approach to stock selection we seek to identify and avoid this risk. The result is outperformance over the market. We provide evidence that this outperformance is not attributable to common “risk factors” and is instead related to the ability of the company to deliver the growth implied by the stock price.

At the heart of any investment decision are both known information and information that is vague or ambiguous. We believe humans (investors) tend to interpret vague or ambiguous information in a systematically incorrect way. We believe that, as a result of this human behavior, information is being impounded into stock prices that is often based on assumptions and is unverifiable. This exposes stock prices to human behavior. These behaviors are not quantifiable through traditional asset pricing models and therefore investors assume a risk of which they are unaware and for which they are not compensated. We call this the Human FactorTM.

Our New Age AlphaTM investment methodology is designed to identify and avoid the losers by using a probability-based approach to stock selection, seeking better returns with lower total risk. New Age Alpha identifies the risk associated with human behavior and actively seeks to avoid it. The targeted result is a lower total risk and better returns.

Our approach to stock selection seeks to produce alpha that has been previously associated with active management without the same inherent and associated risks. We have replaced active stock picking with a proprietary rules-based investment methodology and combined it with the discipline of an index.

We use our investment methodology to provide investors with portfolio construction tools, indexes and investment products that help generate better returns.

Philosophy of Risk
Human Behavior – What’s eating your alpha? 
The Human Factor is not a traditional risk factor 
Market Participants’ Misinterpretation of Risk 
New Age Alpha Delivers Uncorrelated Returns 
New Age Alpha Approach and its Relation to Common Factors 

Philosophy of Risk

In an efficient market, a stock price, on average, reflects all available information about a company. Yet much of this information is vague, ambiguous, or difficult to quantify. Ideally, investors’ differing opinions or interpretations of this information will be correct on average and result in efficient prices despite the uncertainty of any single investor. However, we believe systematic human behaviors cause prices to diverge from true value as the ambiguous or vague information is interpreted by investors in a systematically incorrect way. Thus, an investor in a stock may not be exposed to merely the risks quantifiable through traditional asset pricing models. Instead, because of these behaviors, an investor is exposed to additional risks stemming from human behavior.

Much has been written about how humans make irrational financial decisions and the specific investor heuristics humans tend to rely on when making these decisions. Rarely, however, have any such human behaviors resulted in a profitable investment strategy. This is likely because it is difficult or impossible to disentangle the effects of any single behavior that may be at work on stock prices.

Human Behavior – What’s eating your alpha?

Vague and ambiguous information, when interpreted by investors in a systematically incorrect way, is impounded into stock prices. As a result, human behaviors may make it more difficult for the company to deliver the growth implied by the stock price. If the company does not deliver the growth, then the stock price will go down and investors will lose money. It’s that simple.

The higher the risk stemming from human behavior the higher the probability of a loss. Our methodology identifies stocks with risk resulting from human behavior. Avoiding stocks that exhibit exposure to this human behavior when constructing investment portfolios enables us to seek the remarkable result of earning higher returns with lower total risk.

Investors, because of their susceptibility to heuristics, in many instances work against the efficiency of stock prices when attempting to quantify and value ambiguous information. For example, suppose the CEO of a prominent company called XYZ announced that his firm is working on a ground-breaking product that is still in its early stages. Clearly, this information is relevant to the value of the firm, but the way it should be priced into the stock is less obvious.

If investors are systematically overconfident, XYZ stock will reflect future cash flows that are overestimated and are beyond the company’s ability to deliver the financial performance because investors have extrapolated past growth rates too far into the future. The risk that the company will not deliver the growth to support its new stock price is caused by The Human Factor. This is the result of investors’ overly optimistic behavior when interpreting information related to XYZ CEO’s new product discussion.

Interpreting ambiguous information does not necessarily make stock prices inefficient. It is simply impossible to know whether such information is impounded into prices correctly or whether investors have interpreted the information incorrectly. Our methodology actively seeks to avoid stocks with potential mispricing because our methodology identifies those stocks with prices that are subject to vague and ambiguous information. In doing so, we can focus on avoiding the stocks that are most likely to be losers. We refer to this risk as the Human Factor.

A widely popular school of thought is that higher portfolio returns require accepting more risk. We disagree with this concept – our approach is to avoid risk, and by doing so, increase the return.

The Human Factor is not a traditional risk factor

We believe that when investors use factors to assess risk and price a stock, they create an opportunity for us. Utilizing risk factors such as beta, size, value, and momentum to price a stock impounds irrelevant information into the price. This has the same effect as market participants interpreting any other information in a systematically incorrect way. Specifically, stock prices move out of line with the company’s ability to deliver the growth implied by the stock price.

The research we present in this paper suggests these widely applied factors have little power to predict and/or mitigate loss, yet investors still rely on them to assess risk. We believe this is a fundamental flaw in stock investing. Our methodology simply focuses on the probability of loss and attempts to minimize that probability. To us, the only relevant risk is the risk of loss.

It is possible that investors’ reliance on factors is a perfectly logical response to their inability to properly mitigate loss. That is, they have no better way to assess risk, so they resort to factors. As a result, stock prices become a mere reflection of investors’ uncertainty about the future.

This creates an opportunity for us because, we believe, factors should never have been priced into a stock to begin with, because doing so simply causes stock prices to move out of line with the company’s ability to deliver the growth implied by the stock price.

The aggregate impact of investors interpreting vague and ambiguous information in an overly optimistic way and erroneously pricing factors into the stock price, is measured by what we call the Human Factor. It answers the question, “What is the probability the company will fail to deliver the growth implied by the stock price?”

The Human Factor is not a traditional risk factor. While our system measures risk quantitatively, it is entirely focused on the risk of human behavior. This makes the Human Factor potentially different, it tells investors what stocks come with risk for which they’re not paid for taking and therefore should avoid when constructing a portfolio.

On the other hand, beta, size, value, and momentum are priced. These four factors are easily observable, and investors are willing to pay less (or more) for stocks with (or without) these characteristics. Thus, they are “priced.” We believe what is not priced are systematic human behaviors that cause prices to diverge from the intrinsic value when ambiguous or vague information is interpreted in a systematically incorrect way. When this happens, it can be more or less difficult to answer a fundamental question: Can management deliver the growth implied by the stock price?

We believe we can answer this question because, while other active managers are trying to subjectively interpret vague or ambiguous information, we use the Human Factor to measure the impact their interpretations have on the price of the stock, and therefore on the company’s ability to deliver.

Market Participants’ Misinterpretation of Risk

Risk is a contentious topic evoking at least two opposing viewpoints. Some view risk merely as uncertainty concerning future outcomes, while others view risk as the probability of losing. We take the second viewpoint. Our belief is that risk is best captured by the company’s ability (or inability) to deliver the growth implied by the stock price. That is, we view risk as the probability that investors have priced the stock too high given the company’s ability to deliver. We do not concern ourselves with individual factors, but rather look at the company holistically.

We further believe that what the market typically considers to be risk, need not be viewed as such. Namely, beta. Many investors use beta as a measure of risk simply because it is a rough proxy for the uncertainty that surrounds a stock’s relative performance, and because, after decades of effort, researchers have not found any better measure of this uncertainty. However, by identifying the Human Factor, it is our belief we have resolved much of the uncertainty that beta reflects, allowing us to provide the investor with a level of certainty previously unavailable.

This is a huge advantage because beta gets priced anyway. It is easily observable, leading investors to discount stock prices to reflect a stock’s beta. This doesn’t mean beta actually measures risk. It only means that holding all else equal, investors find higher betas undesirable, and thus demand higher expected returns for accepting them. However, we believe that such an approach causes losses for investors because beta is applied in a broad-based manner across broad categories of stocks.

New Age Alpha Delivers Uncorrelated Returns

To exemplify how avoiding the Human Factor can contribute to outperformance, we construct a variable for the Human Factor outperformance, nicknamed “HFO,” which represents the outperformance of the lowest Human Factor quintile over the return of the universe from which the stocks are drawn (S&P 500). We adopt this approach to construct a hypothetical portfolio that systematically avoids those stocks with the most Human Factor risk. The results, displayed in Table 1, are striking.


Table 1 Hypothetical Out Performance of The H-Factor-1

This chart shows it is apparent that the methodology can outperform but is this merely an artifact of some underlying “riskiness?” We believe that this answer is a resounding no and the reasoning for this conclusion is discussed below.

In recent years, there has been an explosion of interest in “smart beta.” (See, for example, Towers Watson, “A Smarter Way to Invest,” 2013.) The underlying theory of smart beta is that, by reweighting cap-weighted indexes using a factor such as momentum, a portfolio can outperform its cap-weighted counterpart. But is smart beta really that smart? Does it make sense to expose oneself to the risks associated with certain factors? Said differently, does the return of these factors adequately reward the investor for risk it exposes the investor to?

The answer may disappoint a lot of investors. At least one factor, value, we believe, doesn’t even make sense from a risk/reward perspective. The value factor suggests that “value” outperforms “glamour” as measured by the book-to-market ratio. So, shouldn’t it follow that value stocks are riskier than glamour stocks? It should, but we know value stocks are fundamentally less risky. If prices are lower relative to book value (holding all else equal) the stock should be less risky, not more. There is little theory explaining why these factors should perform well. Rather, it is merely an empirical observation that they do.

Adding support to this assertion, we can observe that while factor returns may be positive over a very long history of the stock market, during shorter periods the factors have been shown to underperform substantially. For instance, our research found that, in 2015, the momentum factor was up 21.5% while the value factor was down 8.7%. The following year, momentum was down 17.6% while value was up 8.4%. This suggests that, at a minimum, factor performance is inconsistent.

However, we believe that the performance of the Human Factor is positively correlated with beta, size, value, and momentum when these factors work well and negatively correlated with them when they work poorly. We contend that because classic (Fama French) factors fail to even consider a firm’s fundamentals, the Human Factor works because it can identify when stock prices are not in line with fundamentals.

Table 2 presents the hypothetical correlations of the Human Factor score’s outperformance with the performance of six common factors. We again use HFO to find the correlations of this variable with each factor over the period January 2002 - June 2020. It is apparent from these simulated data that HFO tends to be positively correlated with factor returns when the factor performs well, and that it tends to be negatively correlated with factor returns when the factor does poorly.

Simulated Correlations of HFO With FAMA French Factors and Momentum Factor

In this table, positive correlations with positive factor returns and negative correlations with negative factor returns are highlighted in blue. These are the relationships that suggest HFO is performing well. If the factor is correlated in the wrong direction, for instance, a positive correlation with a negative factor return, the cell is not highlighted. This gives a visual depiction of how frequently HFO may perform well, whereas the factors themselves have performance that is more sporadic.

Why might HFO behave in this way? We believe it is because it is the only variable that balances performance against price. Factors such as size, value, and momentum have little or no relationship to company fundamentals, nor do they capture the risk of investors misinterpreting vague or ambiguous information. This creates a great opportunity to identify and benefit from a methodology that avoids this risk, rather than relying on the inconsistent and theoretically dubious performance of factors.

Despite its popularity, smart beta has not completely displaced active managers. Many money managers still try to outperform the market by simply predicting how individual stocks will perform. We welcome this behavior. It is this approach that we believe causes the distortions in the market that create the Human Factor risk that we avoid. Thus, by neglecting that portion of the investing universe that is fraught with danger – by avoiding the Human Factor – we seek to outperform.

We call this New Age Alpha because by combining this proprietary risk measure with the advantages of rules-based portfolios, we can provide the outperformance potential of active management while taking less total risk.

New Age Alpha Approach and its Relation to Common Factors

One implication of the concept pioneered by New Age Alpha is that we can deliver alpha by selecting stocks in such a way as to not increase our exposure to the five Fama French and Momentum factors through time. We don’t deliberately take on market, size, value, investment, profitability or momentum “risk” and are still positioned to outperform, even on a “risk-adjusted” basis. To demonstrate this, we performed a six-factor regression of HFO. The results are shown in Table 3 below.


Table 3 Regression of HFO on FAMA French Factors and Momentum Factor

The coefficients on each factor represent how much each factor affected the outperformance of HFO in each year. The large positive coefficients indicate the factor helped explain HFO in that year. For example, we can conclude that in 2002 the outperformance of the Human Factor was impacted by the size and value characteristics of stocks with low risk because the coefficients on these factors are large and positive.

From these data, it is clear that there is no consistency in the way the Human Factor is affected by the factors. In fact, the inconsistency in both the direction of the coefficients (positive or negative) and their magnitude suggest that the Human Factor is capturing something entirely different than exposure to factors.

We believe New Age Alpha is the ability to both reduce risk and outperform. The Human Factor does precisely this. The process of using both company fundamentals and stock price – both unambiguous pieces of information – is designed so we repeatedly and consistently identify stocks likely to underperform. Our research suggests alpha at that point involves eliminating those high Human Factor stocks from our portfolios.

In this environment, investors should focus on New Age Alpha and not smart beta. The reason is twofold. First, the factors smart beta is based on are unreliable. Exposure to the factors may help in some years and not others. Second, smart beta strategies ignore the fundamentals of a company and the most fundamental question in investing: Will management deliver the results that the stock price implies? This leads to investors in smart-beta funds taking risks they do not realize exist, and which they are not paid for accepting. We insist that an investor must be paid for the risk they take, and we use the Human Factor to identify the stocks to buy and the stocks to avoid.


The New Age Alpha approach and the Human Factor Methodology are able to produce outperformance because we believe investors often push stocks to prices out of line with the company’s ability to deliver. We believe this creates a risk which the investor is not compensated for taking. Identifying this risk allows us to avoid stocks that are most likely to have been priced too high as the result of human behavior. We are positioned to outperform without taking on additional beta risk. The targeted result is lower overall risk and outperformance.


The information, data, opinions, and disclosures in this commentary are as of 12/31/2020 unless otherwise noted, and subject to change. This material is provided for informational purposes only and should not be construed as investment advice or an offer or solicitation to buy or sell securities. This information discusses general market activity, industry or sector trends, or other broad-based economic, market or political conditions and should not be construed as research or investment advice. Investors are urged to consult with their financial advisors before buying or selling any securities. Although certain information has been obtained from sources believed to be reliable, we do not guarantee its accuracy, completeness or fairness. These forecasts are subject to high levels of uncertainty that may affect actual performance. Accordingly, these forecasts should be viewed as merely representative of a broad range of possible outcomes. Past performance is no guarantee of future results. Hypothetical or simulated examples including tables herein are for illustrative purposes only, are subject to limitations and do not reflect actual trading or investment results or market risks associated therewith. Information related to projections, returns, estimated additional re- turns, outperformance, increases in portfolio values and performance and risk forecasts are estimates only and are not a guarantee. Estimated returns are a combination of current returns, historical or simulated returns and projections on future return trends. Investments entail the acceptance of risk of a loss of capital invested. Such losses are not reflected in simulated performance or returns.

Past performance is not indicative of future returns. Estimated returns are derived from simulated models or historical backtests and scenario analysis when sufficient historical data is unavailable. Any hypothetical returns do not reflect actual trading and therefore do not account for market risks, economic conditions, taxes, fees or expenses.

Any performance or projections discussed are not guaranteed in any way. This document is intended for viewing only by the intended recipient and not for general distribution. This document may not be reproduced or distributed to any person in whole or in part without the prior written consent of New Age Alpha Advisors, LLC and New Age Alpha LLC.