Overcoming Our Cognitive Biases

We started a series on decision-making back in June when we introduced the concept of Level 1 and Level 2 thinking from Daniel Kahneman’s book “Thinking Fast and Slow.” 

The main goal of the series (Better Thinking..., ...Better DecisionsThe Fallacy of the Formula) was to explore how cognitive biases are formed and how they influence our decision-making.

The challenge with our cognitive biases is that they tend to influence us most at the extreme ends of the spectrum. And it’s at these extreme ends of the spectrum where we may need to ignore them the most, because all risky asset classes will experience long periods of underperformance.

The S&P 500 Index has experienced three separate periods where it underperformed riskless one-month Treasury bills for more than a dozen years (1929-1943, 1966-1982, and 2000-2012).

Any student of the market knows that longer periods of underperformance by risky assets are a necessity. If these periods never occurred, there would be no risk, and the risk premium would disappear.

The periods of underperformance essentially create the equity risk premium that investors capture when they choose to take on the random and unpredictable risk of the equity markets.

If The Markets Are Random and Unpredictable, How Should That Impact Our Decision-Making?

Mean reversion is the theory that security prices return to their long-term averages over time.

In every asset class, from bonds to stock to commodities, buying what is cheap leads to better outcomes because expensive stocks revert down to their mean over time while cheap stocks revert up to their mean over time. Unfortunately, that truth only holds up over longer periods of time.  Expensive stocks can get more expensive in the short-term while cheap stocks can get even cheaper.

Using the CAPE Ratio (the Cyclically Adjusted PE ratio from Robert Shiller) for the S&P 500, we can look back at periods of time when assets were expensive and times when assets were cheap.


Source: Macrotrends, Multiple.com and Telos Asset Management Company

The CAPE ratio is a valuation measure that uses real earnings per share (EPS) over a 10-year period to smooth out fluctuations in corporate profits that occur over different periods of a business cycle. The ratio is generally applied to broad equity indices to assess whether the market is undervalued or overvalued.

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Source: Macrotrends, Multiple.com and Telos Asset Management Company

By inverting the CAPE ratio chart we can observe the direct relationship between price and future returns.  The following chart lines up the annualized 10-year forward returns of the S&P 500 with the CAPE ratio at the start of the period.

When the blue line is high, stocks are theoretically undervalued and their future return potential is high. When the blue line is low, stocks are theoretically expensive, and the potential for future returns is muted. 

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Source: Macrotrends, Multiple.com and Telos Asset Management Company

While these charts clearly prove that price matters, they do not address the value premium (the advantages of buying cheap stocks over expensive stocks). And unfortunately, there is little evidence that investors can accurately time the value premium or when the mean reversion will take place. That’s where patience and discipline come in.

And How Do We Overcome Our Cognitive Biases?

The key to overcoming our cognitive biases is to override them with a process that systematically allocates based on math and sound logic rather than human judgement.

Process-driven investing is nothing more than a long-term approach to putting capital at risk by owning a broad variety of asset classes, making periodic contributions and regularly rebalancing. The challenge with process-driven investing is that it requires an investor to focus on the investment process and not the short-term results.

That can be extremely difficult when the short-term results don’t coincide with the long-range return objectives. Over the long term, however, overcoming our cognitive biases with a good process should deliver more reliable outcomes with better results.