The Case Against the Emergence of Passive Indexing Robo-Advisors

Aug 17 · 6 min

TL;DR — Current robo-advisors are based on Modern Portfolio Theory (MPT) and passive index management, both flawed academic ideas based on a misconception of risk and a mistaken belief in market efficiency (the Efficient Market Hypothesis).

If you are reading this post, you most likely know or have heard of so-called robo-advisors: automated financial planning systems with zero or minimal human intervention. The first robo-advisors began operating in 2008 and have seen exponential growth since then. By 2020, they are expected to have an AUM of $20 billion.

Gradement is not exactly a robo-advisor if we literally stick to the previous definition. Gradement evaluates publicly traded companies in an automated way and selects portfolios formed by those with the highest score in different categories. What it does not do is offer personalized financial advice, as other robo-advisors do, because as we will see later, personalized advice, as it is practiced today, is based on simplistic questionnaires and a flawed concept of risk.

Before turning to the critical part of this post, let's first take a look at the positive side that robo-advisors have for the retail investor.

It's always difficult for the average retail investor, without extensive knowledge of accounting and/or finance, to know how and where to allocate their savings. Among other options, they can:

• Follow the recommendations of the financial media—whose objective is to generate an audience, not to watch over the profitability and security of their viewers' portfolios.
• Follow the recommendations of their bank—which tends to recommend its own funds, ETFs, and stocks.
• Follow the recommendations of their securities broker—who tends to recommend the use of technical analysis because it means higher commission income for the broker.
• Engage in intraday trading and/or use technical analysis. Technical analysis is to investment what astrology is to astrophysics. We will delve into this in another post.
• Entrust their savings to a passive indexing robo-advisor.

Among the investment platform options above, there is no doubt that the best that can be recommended to the small investor is the use of robo-advisors. If the underlying index used is sufficiently diversified, the investor will tend to obtain the average market return, especially if they use dollar-cost-averaging. Among other advantages, and thanks to the automation of the investment process, the use of robo-advisors means a reduction in management costs, an expansion of the potential number of analyzable companies, and the elimination/reduction of behavioral bias.

Notwithstanding the foregoing, current robo-advisors are based on Modern Portfolio Theory (MPT) and on passive indexing management, both flawed academic ideas based on a misconception of risk and a mistaken belief in market efficiency (the Efficient Market Hypothesis). The main problems are:

• The "personalized" advice
• A flawed measure of risk using variance
• Asset allocation based on the mean-variance optimization of MPT
• And passive indexing management

Advice personalization

The alleged advice personalization is based on a short and simple questionnaire used to calculate the risk that the investor can assume (objective and subjective risk), which will later be used as an input parameter in the asset allocation phase. Assuming that the investor's objective risk (what they can assume) and subjective risk (what they can tolerate) can be estimated through a simple questionnaire, that estimate only leads to a risk measurement based on the mistaken belief that the variance/volatility of returns can be used as a proxy for investment risk.

Flawed measure of risk

Regarding the use of variance as a measure of risk, Markowitz himself (author of MPT) acknowledges in his book Portfolio Selection that semi-variance is a better indicator of risk that tends to select better portfolios than variance does. His reasoning is that variance penalizes upside volatility just as much as downside volatility. For example, it would assign more risk to a company with returns growing at 10% annually than to one with returns growing at only 5%, simply because the former has higher volatility. Although it makes no sense to consider a company riskier than another simply because it generates more returns, variance is still considered the proxy for risk and therefore the pillar that sustains the entire modern academic theory of investment. If variance were discarded as a measure of risk, the entire academic theory of investment (MPT, EMH, CAPM, Sharpe model, etc.) would collapse like a house of cards.

Neither should semi-variance be considered a risk proxy and the basis of all financial theory because: (1) it would still be necessary, as with variance, to assume a normal distribution of returns (a strong assumption), and (2) in our view, the price of an asset should be separated from the risk measurement. Price is just a historical exchange relation between the marginal buyer and seller based on their subjective valuations of the exchanged good. Following the famous analogy of Benjamin Graham, you should not pay too much attention to the daily price offered by Mr. Market. The real risk to consider is the deterioration of the conditions under which you have made the decision to invest in a certain company.

For instance, deterioration due to a decline in customers, income decrease, increased costs, increased competition, country risk, unfavorable legislative changes, credit risk in its cyclical liabilities, counterparty risk in its financial assets, among others.

Asset allocation

Regarding asset allocation, robo-advisors usually define between 10 and 20 asset classes (some of them even more) among which to distribute the capital contributed by the user, based on the objective and subjective risk level estimated for each of them. Each asset class is assigned a minimum and maximum percentage within the customized portfolio. The minimum is usually not too low, so that the performance of each asset type has a significant weight within the portfolio. The problem with these minimum and maximum values is that they reduce the flexibility of the portfolio composition and may even force investment in certain assets when economic conditions discourage it. For instance, all robo-advisors include an asset class for sovereign debt. The existence of this asset class "forces" all customers, with a portfolio weight depending on their estimated risk level, to hold sovereign debt now, when we are experiencing a historical period of negative nominal and real interest rates in the debt markets, with sovereign debt prices clearly inflated by the balance sheet expansion policies of central banks. The simplistic measure of historical variance as a risk proxy is unable to capture the real risk that the bursting of the sovereign debt bubble will entail.

This asset allocation is done using Markowitz's mean-variance optimization, which presents the following main problems:

• It assumes a normal distribution of returns.
• The standard implementation of mean-variance optimization assumes only a one-year time horizon. The efficient frontier of MPT is a function of the holding period, so you must fix the holding period. This fixed holding period may differ from the real future holding period of the investor.
• And the most serious error, already considered above: assuming that variance of returns is a proxy for risk.

Index investing

Investor John Bogle (founder of The Vanguard Group), in his 1951 graduation thesis, mentioned a fact that remains true today: as a group, the returns obtained by fund managers do not exceed the average market return. Based on this fact, and in the belief that stock prices already reflect all available information (EMH), several economists, including Burton G. Malkiel, recommend that small investors do not pay for personalized advice and should instead invest directly in an index through the many existing indexed investment funds or ETFs.

Among the economists most critical of the EMH is Frank Shostak, who in his article "In Defense of Fundamental Analysis: A Critique of the EMH" wrote that:

The EMH gives the impression that there is a difference between investing in the stock market and investing in a business. However, the stock market doesn't have a life of its own. The success or failure of investment in stocks depends ultimately on the same factors that determine the success or failure of any business. Statistical tests that supposedly validate the EMH framework are based on a flawed method and a failure to understand that the main cause behind the instability in financial markets is the monetary policies of the central bank.

On the other hand, economists who recommend passive investment in indexes because of the impossibility of fund managers as a whole to outperform the market fail by lumping all managers together indiscriminately.

There are many styles and ways to invest. Each fund manager uses the one that they believe to be the most successful, and so many of them end up with lower returns than the market average, but in the same way, many others end up systematically beating the market. Especially those who use value-investing as a reference framework: Warren Buffett (Berkshire Hathaway), Martin Whitman (Third Avenue Value Fund), García Paramés (Bestinver, Cobas), Peter Lynch (Magellan Fund), and Seth Klarman (Baupost Group), to name just a few.

The conclusion of Bogle's thesis should therefore not be to "surrender" and buy the market, but to bet on the forms of investing that have historically worked, using value investing as a framework, which has a more solid theoretical basis than technical analysis and all academic theory on investment. Bogle's study and all subsequent studies comparing managers' returns to their benchmark indices should have clearly separated the considered fund managers by investment style.

So, in conclusion, robo-advisors are a good idea because of the reduction of management costs, the expansion of the potential number of analyzable companies, and the elimination/reduction of behavioral bias. However, they are currently implemented using flawed academic theories. Gradement is an effort to change the current trend in the robo-advisor landscape, from MPT and passive indexing to the more sound and time-tested value investing framework.