From the April 2017 issue of Research Magazine • Subscribe!

Why Evidence-Based Investing Can Improve Your Practice

Scientific evidence points to where advisors can provide significant value to clients — not in short-term stock picking but in helping them achieve long-term goals

EBI aims to maximize after-tax returns while minimizing risk. EBI aims to maximize after-tax returns while minimizing risk.

The mutual fund industry is built on a web of deeply satisfying myths of superstar fund managers, benchmarks, quality fund families, quests for value and high-flying recent returns. An iconic television ad right that aired before the internet bubble burst showed Janus fund analysts inspecting underground fiber optic cables to literally dig up value for investors. Fund investors like a good story.

In academic finance, the story isn't nearly as interesting. Common mutual fund narratives are relegated to the fiction section of the bookshelf. Why do financial scientists have such a different view of investing than many in the financial services industry?

Two innovations changed the way financial economists view the value of stock picking. The first was the advent of electronic computing, which allows scientists to study mountains of returns data. The second innovation was the Sharpe/Lintner capital asset pricing model (CAPM). Computers allow scientists to test whether markets efficiently priced securities based on the amount of risk that an investor couldn't get rid of through diversification.

But, arguably, the most important innovation in the science of mutual fund analysis was the movement of a young scholar named Eugene Fama from romance languages into economics. Fama's Ph.D. thesis in 1965 used the power of advanced computing to show that stock prices tended to follow a random walk. Fama also contributed to developing a new method of analyzing how stocks respond to new information that provided a window into the remarkable efficiency of financial markets.

Then in 1967 Fama's graduate student, Michael Jensen, decided to see whether returns on mutual funds could be explained by the exciting new CAPM equation. Jensen simply tested if systematic risk explained the variation in fund performance.

Could fund managers provide a higher return than would be predicted based on their risk (or beta)? Could the best funds provide a consistently higher return than an investor could achieve by just holding a market portfolio with the same amount of risk?

Jensen found that mutual funds didn't outperform the market as a whole. This wasn't entirely surprising and doesn't, on its own, endanger the mutual fund mythology. On average, fund managers don't outperform the market.

But a good advisor can still identify the talented managers who will outperform in the future, right? Unfortunately, Jensen also found no evidence of fund persistence. Yesterday's winners didn't necessarily outperform in the future.

One would think that Jensen's research debunking the myth of consistently outperforming fund managers (measured by alpha, also known as Jensen's alpha) would strike a blow in the remarkably efficient marketplace for actively managed mutual funds. Fortunately for the investment management industry, while stock pickers tend to be ruthlessly efficient, fund investors are not.

A Scientist's View of Investing

Scientists propose theories that are supposed to explain reality. The CAPM is a theory which suggests that average returns on financial assets are explained by beta, or the amount of systematic risk they exhibit compared to the market.

Scientists then test whether beta does in fact explain mutual fund returns. Generally it does, but sometimes it doesn't. When theories don't do a great job of explaining reality, then scientists propose new theories.

Maybe there is more to asset returns than just beta? Maybe investors prefer larger to smaller companies? Maybe investors tend to crowd into popular stocks and drive their prices up while leaving unpopular stocks to outperform?

These alternative theories of asset returns are also known as factors. The rise of factor-based investing stems from return anomalies observed by scientists over the years. This is the way science works. When a theory doesn't do a perfect job of explaining reality, then scientists test new theories that help refine our knowledge of causation.

The original investing factors that, when combined with beta, do a consistent job of explaining fund performance over time are the size of the firm and the price investors are willing to pay for a dollar of profit (otherwise known as value). Investors have enjoyed a higher performance from choosing stocks from small firms with cheap prices.

The so-called Fama/French three-factor model has dominated academic finance for nearly three decades. Scientists found that many of the smartest fund managers were merely the best at identifying these factors before the academics were able to figure them out. Once they controlled for factors, the excess performance of these superstars faded away.

Scientists have since identified additional factors. Today's winners also tend to outperform in the short run, a phenomenon known as momentum. Firms that trade less frequently tend to outperform, known as the liquidity effect. More profitable firms also tend to do better.

Evidence-based investing is about identifying the characteristics of stocks that have outperformed in the past, and building portfolio strategies that overweight stocks that have these particular characteristics.

It isn't about finding good companies. It's about finding companies that have the right factors. Instead of inspecting underground cables, a financial economist inspects whether a firm is small, cheap, profitable, or illiquid.

Evidence-Based Portfolios

In the recent book “The Incredible Shrinking Alpha” (an easy and essential read for any advisor), Larry Swedroe, director of research for Buckingham Strategic Wealth, and his co-author Andrew Berkin, director of research at Bridgeway Capital Management, lay out the convincing argument that the investment industry spends far too much time chasing any hint of Jensen's alpha and not enough time paying attention to science.

This point has also been made by Eugene Fama's frequent co-author Ken French, professor of finance at Dartmouth. In a 2008 presidential address to the American Finance Association, French estimated that over $100 billion is spent chasing elusive returns that cannot be explained by beta.

Swedroe and others point out that the actual alpha that can be captured by skilled investors is just a fraction of this amount. French estimates that 0.67% of the total stock market value is lost each year by investors who can't let go of the active management story.

It appears that the ability to instantly make low-cost trades coupled with the remarkable flow of new information have further driven down opportunities for exploiting market mispricing. If it costs less than 10 basis points to fully capture beta, then fund managers needs to earn their keep if they are charging an additional 50 or 100 basis points to manage assets.

In other words, you could pay a fund manager $1,000 on a $1 million portfolio to capture beta. If you pay an additional $9,000 for something extra, is that a good investment? You’ve made a $9,000 bet on the story of managerial skill and you’re hoping for a good return on that bet.

The science says that this is a sucker's bet. A manager may have had a few lucky years where they’ve been able to justify their extra costs, but there is no evidence that even the star fund managers are able to consistently earn their keep.

Evidence (or research) does say that fund managers should follow the research and identify factors that provide return above beta. This was the philosophy of David Booth, also a student of Eugene Fama, who created an investment management company that hoped to exploit some of the newly identified factors, or dimensions, of stocks that provide a higher-than-average return. His fund company, Dimensional Fund Advisors, ended 2016 with $460 billion in assets by following the evidence-based investing philosophy.

How then do evidence-based investment portfolio managers earn their keep? First, they need to be aware of the evidence. Dimensional recently added a new factor — profitability — to capture a firm characteristic that has historically predicted higher returns.

Research is constantly unearthing potential new factors. Being skeptics, scientists test (and often reject) these factors using data from various time periods and countries outside the United States.

Evidence-based investing requires that advisors pay attention to the current state of knowledge in financial economics. Recent studies have unearthed the potential value of investing in funds that invest in low volatility securities, low-beta stocks, or even leveraged bonds.

In many cases, once a factor has been identified, its ability to predict higher performance appears to go away. The small stock effect has largely disappeared since it was identified by scientists as more traders overweighted small cap within their portfolios.

There aren't a lot of resources available for advisors who are interested in exploring the newest investing research coming out of academics. Of course, there are academic journals and conferences, but most advisors need someone to pull out the most convincing and significant studies that may be relevant to their own practice.

Ritholtz Wealth Management and the Information Management Network sponsored the first evidence-based investing conference last November with an agenda of topics that included the research on alternative investments, smart beta, and portfolio allocation strategies.

The Benchmark Problem

This brings us back to the myth of the benchmark. Imagine the famous Morningstar Style Box which fits funds into one of nine value and size categories. On the bottom left are small cap, value funds. On the top right are large cap, growth funds.

Historically, fund performance has been judged by comparing their performance to a benchmark portfolio within each of the nine fund styles. If you invest in a large-cap growth fund, you compare its performance to the large-cap growth benchmark.

To an evidence-based investor, this makes no sense. If I want to choose a fund that will likely outperform its benchmark, I’ll find one that leans to the small-cap value (bottom left) corner of the large-cap value box.

But why even choose funds in the top-right large/growth style box when historically these stocks have underperformed? Why not simply choose the lowest fee funds in the small cap/value style box?

The most damning problem related to benchmarks may be that fund managers are loathe to deviate from them. Even the smart ones who lean to the small-cap/value edge of their style box are at risk of an investor revolt (or being fired) if they underperform the benchmark with the style box for a few years in a row.

This happened in the late 1990s when value stocks got clobbered. Managers have an incentive to steer closer to the benchmark to keep investors happy.

Of course, this leads to a phenomenon known as closet indexing. Many active fund managers don't really do much to be different than a passive index benchmark.

A newly developed measure of active share quantifies the extent to which a fund's performance follows the performance of an index. A 90% share means that nearly all of the fund's investments mimic a passive index. In other words, investors are paying for active management but not getting any additional value for their investments.

A recent report by the European Securities and Markets Authority identified nearly one in seven active funds in Europe that were clearly closet indexers. But this understates the fundamental problem. Even funds that have a 60% active share must earn their excess fees from the remaining 40% of the fund that deviates from the index.

In other words, investors are paying a lot more for the passive portion of the portfolio than if they had simply selected a low-cost passively managed mutual fund or ETF for 60% of their portfolio and focused on investing in highly active funds with their remaining 40%.

Providing Value in an Evidence-Based World

A high quality evidence-based portfolio is surprisingly cheap. Low-cost fund families now offer small-cap value funds, as well as funds that take advantage of additional factors such as low volatility and profitability.

In essence, what was once alpha has now become a part of beta that any investor can capture through passive strategies at a low cost. That means that an evidence-based advisor will need to look beyond simply selecting investments to demonstrate value.

The good news is that the scientific evidence points clearly to areas in which advisors can provide significant value to their clients. For example, investors lose at least 1% per year because they don't stick with their investment policy during a recession. An advisor can help them stay the course.

Investors don't take advantage of tax-efficient strategies such as tax loss harvesting and locating investments in the right sheltered account. Advisors can move investments into the most tax-efficient areas. Avoiding behavioral allocation mistakes and taking advantage of tax-savvy strategies alone can help advisors more than earn their keep.

Most important, taking an evidence-based approach to advising moves the focus away from security selection and moves it toward helping clients achieve long-term goals. Admitting that high-performing portfolios have become a low-cost commodity can help advisors position their true value in the areas where clients need it the most.

Michael Finke, Ph.D., is dean and chief academic officer at The American College of Financial Services. He is also a contributing editor of Research on Wealth magazine.

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