Quiz Time! Count the Pitfalls

I recently received an email from a financial advice firm about “rational decision making” that had a promising intro: “We’ve discovered five common investor biases and emotions that can lead to below-average returns.” Biases, I don’t like those. Emotions hurting returns, those aren’t good either. I’m listening!

            It describes loss aversion (irrationally holding a losing security in hopes that it will recover) and anchoring (relying too much on an initial piece of information) before offering this description of hindsight bias…

            Hindsight bias – Many investors believe that an asset will perform well in the near future because it has performed well in the recent past. As a result, some investors are constantly chasing returns. If we reflect on this, it is actually counterintuitive. The number one rule of investing is buy low and sell high. Take a look at the S&P 500 chart above. If you have not owned the S&P 500 Index over the last nine years, is now the time to buy after it is 300 percent more expensive than it was nine years ago?

            Okay, how many problems can you find in that last sentence?

            I count three!

• “If you have not owned the S&P 500 Index …” Why mention this? It is a sunk cost fallacy to consider whether you bought something in the past. It’s either a good investment or it’s not.
• “…over the last nine years…” This is classic cherry-picking. Where did the number nine come from? You can bet it came from the last time the S&P hit a low point.
• “…is now the time to buy after it is 300 percent more expensive than it was nine years ago?” This is the gambler’s fallacy. It’s rational to expect something that’s done extremely well to do less well (regression toward the mean), but it’s not rational to imply that it’s now a bad investment due to its recent history. There is no force of nature that requires all good returns to be balanced out by bad returns. There is irony in providing this comment after explaining the anchoring bias to the reader.

Beware of people advising to “buy low and sell high” as if they know what low and high are. If it were that easy, the firm should just send out an email that says “LOW” or “HIGH” in the subject line so its customers can act accordingly and beat the market.

If you spotted the data science pitfalls in that financial advice, congratulations, you’re well on your way to becoming a skeptical and savvy consumer of data!