Because all investment is burdened with it, investors must all and always reckon with risk, its implications and its consequences. However, risk is an elusive concept. Risk is anything but tame, benign, entirely predictable or fully controllable. It takes on different guises in different situations or contexts and is not susceptible to precise definition.
If we are going to be good investors (and traders), we need to reckon with risk. We need to study it, try to quantify it and analyze it. We need to ponder it, and I’ll be doing so intermittently for a while.
Risk has an unknown outcome, but we know what the underlying outcome distribution looks like. Uncertainty also implies an unknown outcome, but we don’t know what the underlying distribution looks like. So games of chance like roulette or blackjack are risky, while the outcome of a war is uncertain. Knight said that objective probability is the basis for risk, while subjective probability underlies uncertainty.
I think this makes great sense (even though many quants would suggest that both risk and uncertainty can be quantified – I think it’s far less tame than they do; see below).
In the probabilistic sphere, where risk isn’t necessarily bad or good, we have a number of issues to work through.
1. As with Katniss in The Hunger Games, may the odds be ever in your favor. If you are likely to lose, you shouldn’t play. Of course, “losing” and “winning” have broader meanings in this context than people typically assume. For example, if I lose the bet and $10 60 percent of the time and win $20 40 percent of the time, that’s a winning bet overall (which leads directly to #2).
2. Size matters. As in the example above, the size of your bets should relate to both the likelihood of winning and the stakes. Pocket aces are worth a significant investment; a two and a three are not (unless you’re bluffing, which is outside the scope of a discussion of investing – trading is another matter). In On the Waterfront, Marlon Brando as the boxer Terry Malloy offers his famous lament.
Had he not taken the sure-thing “short-end” money – a relative pittance – to throw the fight, his upside potential was enormous, he “coulda been another Billy Conn.”
3. The markets can stay irrational longer than you can stay solvent (Keynes). Because of general randomness, even when the odds are in your favor, you need a lot of bets for the results to have reasonable confidence that things will pan out as expected. Phrases like “small sample size” explain why a bet can make great sense but still not work out.
4. Avoid déjà vu all over again. When your goal is many different kinds of bets for diversification purposes, you need to make sure you’re not essentially making the same bet over and over. That’s the 2008 problem writ large. What were presumed to be different bets then weren’t so different after all. That’s a recipe for getting rolled when the market turns against you.
5. Be extra careful where the wild things are. Most economic models assume a “mild randomness” of market fluctuations. However, and especially at the extremes, what visionary mathematician Benoît Mandelbrot called “wild randomness” prevails. Risk tends to be concentrated in a few rare, hard-to-predict, but extreme, market events.
6. Once you have won, stop playing. Why risk damage and perhaps screwing up everything you’ve accomplished? When you have met your goal(s) it’s time not just to take risk off the table but to get out of the game entirely.
Risk analysis essentially boils down to a set of fairly straightforward considerations overall, even if it remains maddeningly difficult to deal with and impossible to control. When reckoning with risk, begin by considering the following.
- What can go wrong and why.
- How much being wrong (or right) matters.
- What can be done about it.
- How much being wrong (or right) costs.
Despite what many salespeople in our industry would have people believe, every investment entails risk. Risk and reward are inherently connected. Risk is always risky.