As grownups, we understand that at times stocks move lower. What terrifies us, however, are the big “drawdowns,” the exceptional not-just-another-correction market beat-downs that cause us to fear material and possibly lasting damage to our financial security. We can reduce the probability of this – but not by drawing on what the quants are doing.

Defining Risk – Really

Quants one way or another define risk in terms of volatility. Traditionally, risk has actually been defined as volatility, the statistical meaning of the word, which meant that investors should equally fear big moves up as well as down. Innovations occurred that recognized the differences in direction and sought to analyze downside volatility, value at risk, maximum drawdown, etc.

Bad idea. They had it right the first time. We do need to be equally fearful of upside volatility. That’s because risk is not a statistical phenomenon. It’s a fundamental phenomenon.

This means any risk-based model that is based on historical price data (as all of them are) is wrong (“mis-specified”) because it measures something that has nothing to do with the risks to which you are subjected when you buy stocks. Such metrics consist of nothing more than statistical report cards revealing how things just so happen to have played out over particular historic time period.  Because they don’t dig beneath the price action, they tell us nothing about why the stock did what it did and, accordingly, provide absolutely no useful information that can help us assess how the stock might behave in the future. (In a 9/1/15 post, I cited violation of the past performance does not assure future outcomes as a major indicator of sham financial research; all of the standard risk metrics violate this principal.)

I understand and I’m all for studying the past to learn things that can support reasonable assumptions about the future (assuming, of course, we are not mindlessly data mining but understand and can explain logically why we believe the past relationships we observed are likely to persist going forward). But I don’t care about metrics based on historical prices. I care about the underlying factors that caused prices to behave the way they did.