Evidence-Based Investing in Brief

What Is Evidence-Based Investing?

Evidence-based investors build and manage their portfolios based on what is expected to enhance future returns and dampen related risk exposures, according to the most robust evidence available. This also means sticking with your evidence-based strategy once it’s in place for the long term, regardless of market uncertainties and self-doubts you’ll experience along the way.

 

Do you (1) hope investors can come out ahead by finding mispriced stocks, bonds, and other trading opportunities; and by dodging in and out of rising and falling markets?

Or do you (2) accept all investors' investment insights create relatively efficient market pricing that is too random to predict consistently?

An overwhelming body of evidence suggests investors should skip the first approach and adopt the second assumption. This has been the case since at least 1952 when Harry Markowitz published Portfolio Selection in The Journal of Finance. In their book, “In Pursuit of the Perfect Portfolio,” Professors Andrew Lo and Stephen Foerster describe:

“While it’s commonplace now to think of creating a diversified portfolio rather than investing in a collection of securities that each on their own look promising, that wasn’t always the case. It was Harry Markowitz who provided a theory and a process to the notion of diversification. He helped to create the industry of portfolio management.”

Markowitz’s work became known as Modern Portfolio Theory (MPT), academics and practitioners have been building on it ever since. His initial work and others’ subsequent findings strongly support ignoring all the near-term noise and taking a long-view approach. This involves creating a unified investment portfolio and focusing on more manageable details, such as:

• Tilting toward or away from entire asset classes to tailor your risks and expected returns
• Minimizing avoidable risks by diversifying globally
• Reducing unnecessary costs
• Controlling your own damaging behavioral biases

At first blush, nearly every investment recommendation may seem “evidence-based.” After all, few forecasters peer into actual crystal balls to make their predictions. And no market guru would admit their stock-picking track record has been no better than a dart-throwing monkey’s (even though that’s usually the case).

Instead, stock-picking and market-timing enthusiasts tend to argue their cases by turning to articulate analyses, clever charts, and convincing investment briefs. They use these props to explain the late-breaking news and recommend what you should supposedly be doing about it.

There’s nothing wrong with facts and figures. The critical difference is how we apply them as evidence-based investors. As financial author Larry Swedroe describes it:

“In investing, there is a major difference between information and knowledge. Information is a fact, data, or an opinion held by someone. Knowledge, on the other hand, is information that is of value.”

— Larry Swedroe, ETF.com

No matter how compelling a call to action may be, we discourage frequent reactions to the never-ending onslaught of information. Before acting, we must ask ourselves:

Which current information might add substantive value to our decisions by refuting or adding to the existing evidence? Or is this “new” information just more of the same old noise, already factored into our evidence-based investment strategy?

Because there is much more noise than valuable knowledge available to investors, the basic recipe for evidence-based investing begins with academic rigor. It should always be a key ingredient in separating likely fact from probable fiction:

• It requires robust data sets that are large enough, representative enough, and free from other typical data analysis flaws.
• Authors should be impartial, lacking incentives to “torture” the data to make a point.
• Other studies should be able to reproduce the same findings under different scenarios, suggesting the results are more likely to persist upon discovery.
• The data, method, and results should be published in reputable, peer-reviewed forums where informed colleagues can comment on the findings.
• Enough time must pass to make all the above possible.

 

After that, we also must be able to apply the results in the real world. In other words, even if a theoretical strategy is expected to enhance your returns, it must do so after considering all practical costs and portfolio-wide tradeoffs involved. For example, sometimes, one source of expected returns may offset another, even more significant, source. Occasionally, we can combine them for even stronger results; other times, it’s best to favor one over the other.

So, which factors appear to explain different outcomes among different portfolios best? What combinations of these factors are expected to create the strongest, risk-adjusted portfolios? What explains each factor’s return-generating powers, and can we expect those powers to persist?

Academic research has found several factors that point to differences in expected returns. Analytical scholars have thoroughly documented the differences in expected returns generated by the various factors in markets around the world and across different time periods.

Based on the academic answers to the practical questions posed above, we typically mix and match the following factors in our evidence-based portfolios, varying specific exposures based on each investor’s personal goals and risk tolerances:

• The Market: Stocks (equities) vs. bonds (fixed income)
• Company Size: Small vs. large company stocks
• Relative Price: Value vs. growth company stocks
• Profitability: High-profit vs. low-profit company stocks
• Term: Long-term vs. short-term bonds (based on maturity date)
• Credit: “Safer” vs. “riskier” bonds (based on credit quality)