We are born with some pretty good warning mechanisms and most people are pretty good at sensing when things are not right. Martin J. Dougherty makes exactly this point in his book Special Forces Unarmed Combat Guide: "Victims of assault often say afterwards that they could see it coming." He continues, "The problem, then, is not being able to spot danger but being willing to act on this information and avoid it." While this is just one manifestation of our defense network, it does highlight our natural ability to "spot danger".
It also highlights the imperative of being able to act on useful warnings. Given that volatility and risk are endemic to the exercise of investing, there is no particular reason why most market behavior should cause undue duress for a well-informed investor. And yet times of unsettled markets and high volatility can keep a lot of investors awake at night, including seasoned investment professionals. Oftentimes, concerns revolve around a sense of uncertainty - a sense that something isn't quite right or that something is being missed. Sometimes it comes from an uneasy feeling that a prescribed course just doesn't seem right.
Indeed, it may just be that one's approach to investing is the source of discomfort as much or more than market moves. Two common approaches to investing vary substantially in their assumptions and in the logic of how they aim to get you from point A to point B. If you are feeling uneasy, it may be a good time to make sure that your investment approach will allow you act so as to avoid danger.
One approach focuses on the importance of diversification and uses statistical analysis to design portfolios that maximize returns for a given level of risk. It is well entrenched in investment theory and practice. This approach is characterized by graphs that show the upper and lower bounds of growth in assets and gives assurance that if you just stick to the plan, you will have an extremely high chance of meeting your investment goals. It makes a lot of sense and is hard to refute.
Another approach is described by William Poundstone in Fortune's Formula y as being one that "offers the highest compound return consistent with no risk of going broke." It is well recognized in investment theory, though probably less so in practice. It can certainly be characterized by wide swings, but gives the assurance that if you just stick to the plan, you will maximize your wealth over your investment horizon. It makes a lot of sense and is hard to refute.
This juxtaposition of strategies highlights a common investment challenge: how can you tell which one is better and/or which one is more appropriate for you? Do you know which one your financial planner or wealth manager or consultant uses? These are exactly the types of fundamental questions that are so critical to long term investment success but are so rarely discussed thoroughly. The fact is that both approaches have merit to them, but both also rely on important assumptions.
The first approach is referred to as the mean-variance framework and is a part of a body of thinking called "modern portfolio theory". While the mean-variance approach correctly highlights the importance of diversification, it does so at the expense of some serious structural shortcomings (For an excellent, though technical discussion, see Michael Mauboussin's interview with the physicist Ole Peters [here]). One of the flaws of the approach is that it models returns using only mean and variance. Unfortunately, the reality is that return distributions have other dimensions that are extremely important to investors. Considering only mean and variance is akin to describing a three dimensional object with only two dimensions. The description will be at best incomplete and at worst, wholly unrepresentative. The implication is that all of those great graphs of wealth accumulation are at best possibilities and at worst complete fantasy.
Another important flaw of the mean-variance framework is that it relies on expectation values. In theory, according to Ole Peters, expectation values represent an "ensemble of imagined parallel universes" and can potentially serve as the "basis for sensible behavior". In practice, however, most firms simply apply averages from the past, but these past actualities fall well short of representing all imaginable future possibilities. In other words, since (arguably) most firms do not populate the model with the right information, one cannot expect it to produce useful results. Garbage in, garbage out. This common deficiency almost completely undermines the case for using mean-variance as an investment strategy.
The second approach is referred to as the Kelly criterion and gained notoriety as a betting system. Michael Mauboussin gives a nice overview in "Size Matters" [here]: "Based on information theory, the Kelly Criterion says an investor should choose the investment(s) with the highest geometric mean return. This strategy is distinct from those based on mean/variance efﬁciency." In general, Mauboussin continues, "The Kelly Criterion works well when you parlay your bets, face repeated opportunities, and know what the underlying distribution looks like." Poundstone adds, "The Kelly criterion is meaningful only when gambling profits are reinvested. A practical theory of investment must largely be a theory of reinvestment."
This is a key point: most people do think of and act on investments as discrete opportunities that change over time and not as a singular procedure that operates like a reliable machine. In this way, the Kelly approach seems to correspond with the way many people actually invest. According to Poundstone, "They [most people] buy stocks and bonds and hang on to them until they have a strong reason to sell. Market bets ride by default." It is also natural to recognize the importance of reinvestment: One good investment does not a retirement make. You need to keep it up.
Poundstone clarifies the strategy: "The Kelly formula says that you should wager this fraction of your bankroll on a favorable bet: edge/odds. The edge is how much you expect to win, on the average, assuming you could make this wager over and over with the same probabilities. It is a fraction because the profit is always in proportion to how much you wager." As Mauboussin puts it, "As an investor, maximizing wealth over time requires you to do two things: ﬁnd situations where you have an analytical edge; and allocate the appropriate amount of capital when you do have an edge." An important condition for the Kelly approach is that the system only works as long as the investor "stays in the game long enough for the law of large numbers to work."
Further, it is also natural to think of calibrating the magnitude of investments according to their attractiveness. While the Kelly approach does require one to have an edge in order to make an investment, it doesn't require one to invest when no edge exists. This all makes common sense - which ought to make it easier to adhere to even in tough times.
Conversely, investors may have trouble adhering to a mean-variance approach because it isn't that hard to perceive problems with its assumptions and logical consistency. For one, it's not an inherently bad idea to look to past returns for an indication of what future returns might be, but why should that be the only input? Other things matter a lot such as valuations and your starting point. Likewise with assessing diversification benefits. It's not bad to look at past cross correlations for starters, but why not also consider the potential for increased global interconnectedness to increase correlations and reduce diversification benefits in the future?
Arguably the biggest issue with the mean-variance approach, however, is that it understates risk. It would make sense that unprecedented levels of central bank intervention the last seven years is a factor that ought to be incorporated into one's investment approach, and yet mean-variance ignores it. It is also true that sometimes bad things do happen and it makes sense to try to avoid them. The mean-variance approach is very weak at adapting to change: it essentially says that since the vast majority of the time you don't get attacked in dark alleys, you shouldn't worry about dark alleys.
Thus, although this approach is an industry standard and used by countless wealth managers, financial planners, consultants, and other industry participants, it actually serves as a very weak foundation upon which to base one's investments. It treats the market as a utility, reliably cranking out returns, but that isn't how the market actually works - as anyone who follows it knows all too well. As a result, it may well be that much of the anxiety investors feel in regards to unsettled markets has a lot to do with the discord that they feel in regards to the mean-variance approach.
To be fair, it is not like the mean-variance framework is an obviously bad idea that never should have taken hold. The theory is over fifty years old though and a great deal has been learned during that time to improve and refine investment approaches. As one example among many, advances in behavioral economics have been a major development. Indeed it is one of the weaknesses of the investment services industry that it has been slow to disseminate many of the useful advances in investment theory and practice nearly as quickly as markets have evolved. The Kelly approach isn't the end of the line either, but it does represent progress.
Just like walking alone down a dark alley at night can intuitively seem like a bad idea, so can navigating through markets with an investment strategy that you don't really trust. Neither may seem incredibly risky at the time and you might even be able to get by unscathed a few times. Don't let anyone convince you that such actions are a good idea though. People are usually pretty good at spotting danger; make sure you are just as good at responding to it. If you don't have a good idea of where to go, ask for help.