Is risk “volatility vs. a benchmark” or is risk “the potential permanent loss of capital”?

There are many smart folks who will die on the hill that risk is the latter, and plenty other smart folks will die on the former.

We’ll die on the former, but we don’t think that either side is as far apart as the other side thinks. 

Most of the publicly-listed equity securities in which we all invest or trade are marked every millisecond; and when something we buy goes higher, we actually make money. When it goes lower, we actually lose money. That happens whether we bail or hang on, whether it is realised or unrealised.  In a liquid market with continuous pricing, all losses are permanent. There may be subsequent, permanent gains from that point forward, or there may not.

And, oh, the guy who watches me buy the stock, sits on his cash, and then waits a few months to buy it after it plummets 20% (whether from me or from someone else) is going to have a better year than I have, in any scenario.  Yet these "risk is permanent loss" guys are implying that it somehow matters if a loss is realized or unrealized - as if we haven't really lost money if we can sit through the storm.   This makes very little sense to us. 

I'm Volatility.png

I'm Volatility?

Admittedly this is a quanty view, and maybe I should blame the University of Chicago for that; but quants aren’t just steeped in calling everything volatility, they also care about expected returns.  And I think this is at the crux of the debate.  It’s mostly just a difference in terminology.    

We can illuminate the issue if you assume that both the quants and the permanent loss guys are sharing the same, perfectly accurate, crystal ball.  If that crystal ball divines that stock XYZ has very little downside, and a great deal of upside, the permanent loss guys will say the idea is low risk.  The quants, on the other hand, will say it has high expected returns. That’s it.  That’s the difference.  The quant may furthermore wonder what the likelihood of missing or beating that expected return target is (and by how much), and he will call that the risk (aka “volatility”), thereby causing the dissention and hardened stances between both camps.  They both like stock XYZ, and they actually like it for the same reason, they just call that reason something different – and confounding things one side calls it something for which the other side has reserved a different definition.

Cliff Asness at AQR did a great piece[1] a few years back, and when discussing this same topic, he mentioned: 

“Although I clearly favor the quant approach of considering expected return and risk separately, I still think this argument is mostly a case of smart people talking in different languages and not disagreeing as much as it sometimes seems.”

And this leads us to a more nuanced discussion about time-horizons, investor alignment, and behavioural finance.

As we discussed in a previous piece[2], even using the quants’ definition of volatility, there is a potentially counterintuitive notion that “volatility” may be higher or lower depending on the periodicity of our analysis (aka depending on how often we look at the portfolio) and our sample size. 

If we have something, for example, that ends up mean-reverting over a very long time horizon, volatility that consists of annualising shorter terms can potentially be misleading.  Take, for example, the number of rainy days in London per year.  The average is about 106 days a year, and the monthly average moves between 13 and 19 days.  If we look at annual samples over time, we may get a slightly (or very) different measure of volatility than if we annualise monthly samples.  Which itself might be very different from annualised weekly samples, which again may be very different to annualised daily samples.  And then if we use too few datapoints in those samples, say after a dry-spell or a wet-spell, we can get some optically crazy estimates for annualised volatility.

This is why it can be poisonous to stock-pickers to look at their returns every day, or every week, or even every month. Obviously, agency issues make it almost impossible to never look, but we should do whatever we can to retain our objectivity when we do so. 

Losing that objectivity is a sure-fire way to negatively impact returns.  When we all start caring about where we bought a stock, or what people might think of us knowing where we bought a stock, it introduces bias.  And it is this bias that renders the “what is volatility” debate somewhat moot.  As we discussed in the piece footnoted below:

“(The answer to the ‘what is volatility’) question might not matter as much as we think, because when we throw in the whole loss-aversion phenomenon of Kahneman and Tversky, the importance of semantics dwindles.  When the pain from intermittent drawdowns can exceed the pleasure of intermittent gains, even if those gains are greater than the losses cumulatively, it hurts.  It hurts whether you are suffering the move that creates higher “expected returns” and it hurts if your “volatility” increases vs. a benchmark, and no matter where things end up, that journey – emotionally – feels more important than the destination.”

And this may be one of the rare cases where the destination is more important than the journey.

Or maybe it isn’t.  Do you have short-term requirements for your personal portfolio? Do you need to make a downpayment on a house?  Do you manage money for others and do they expect the journey to last as long as you do?  Is the pain from a drawdown going to be more than they can bear?  In either of these cases, the journey is more important than the destination.

Why?  Because you don’t get to finish the trip.  You never get there.

[1] My Top Ten Peeves, Clifford S. Asness, Financial Analysts Journal, 2014, Volume 70, Number 1,


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