Loss aversion is a well known phenomenon in economics and decision theory; people strongly prefer avoiding losses to acquiring gains.  But how strongly do we anchor our decisions to the memory of those losses?

But first, a slight, but relevant, tangent…

In Red-Blooded Risk, Aaron Brown discusses the concept of risk ignition: the optimal amount of risk that leads to explosive exponential growth.  Above this limit, we risk blowing up.  Below this limit, we doom ourselves to sub-optimal performance.  Investment premiums above the risk-free rate are paid, after all, for bearing excess risk.  It is my opinion that in the broadest view, investing is really about managing our exposure to these premiums, which in turn is really about identifying whether premiums are richly or cheaply priced.  In other words, do we think that we are being fairly compensated (or, preferably, over-compensated) for both the future probability and magnitude of impact of the risk being realized?

Now, the market doesn’t offer different premiums to different people.  So why might two people come to different conclusions?  Why would a 20 year old put 80% of his savings in the S&P 500 and an 80 year old put 20% in?  The premium the market is paying to both is identical, after all.  My answer is utility: each of us views the premium through our unique lens.  A young investor may be willing to bear greater market risk, and therefore even a low premium may be attractive, because major losses in the short-term are compensated by large premiums in the long-term.  The short-term losses, after all, are merely to savings that won’t be used for another 40 years.  The elderly investor, however, may say that the compensation is not great enough because because large near-term losses may cause permanent lifestyle changes from which he does not have time to recover.  Where the young investor sees an extra 500bp above the risk-free rate for the next forty years, the elderly investor balances the extra 500bp against a potential 50% drawdown.

Despite being nearly five years in the past, the memory of destruction that the credit crisis wrought on our portfolios weighs so heavily that the industry is still seeking innovative techniques and solutions.  That’s not a bad thing, in and of itself (after all, innovation is good for everyone), but it makes me wonder: has the pendulum now swung so far towards loss avoidance — have our risk preferences and utilities changed so dramatically and permanently — that we are potentially setting up a generation of investors to guaranteed long-term underperformance?  Are we, collectively, bearing too little risk?

My own recollection of the last five years is far less rosy than the realized results.  I remember bouts of low volatility followed by high (I think we call that “volatility”) and downside jumps that caused me to be haunted by the Ghost of Recessions Past.  But consider the following graph, showing rolling forward 252-trading-day (~1 year) returns since 7/30/2008 (five years ago, today).  Post-2009, there have only been 11 periods that resulted in a negative 252-day realized performance — and those losses were limited to 1%.

forward returns

So I ask the question: did the 2000s skew our global utility function so badly that the nearly 5 year-old memory of the credit crisis outweighs the last 4 years of realized returns?

While I consider my own biases, it re-affirms my belief in outcome-oriented, rule-driven investment strategies: a consistent process helps us avoid the potentially disastrous impact of our own behavioral biases.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients. Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn. Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University. You can connect with Corey on LinkedIn or Twitter.