When it comes down to it, finance is about risk and return. One of the purest measures of risk is max drawdown. This is pretty much the worst-case scenario: one bought at a peak (not necessarily the absolute peak) and a trough (not necessarily the absolute trough) such that the drawdown is maximum, i.e., you have maximum loss. I was curious, if one takes a look at the S&P 500 components from max drawdown only, what does it look like? The time period for this simple study spans 5 years from today, February 28, 2013. Choosing a 5 year period does unfortunately eliminate 25 of the S&P 500 right off the bat due to those symbols not having data running that far back.
|S&P component||Max drawdown (5 yrs)||Std Dev (daily return)|
The above table shows the 10 components with the least max drawdown over the period. An interesting variety of businesses are represented here. It isn't just a list of defensive utilities or consumer staples. We have automotive parts retail, the Golden Arches, industrial equipment, a pharmaceutical, a pharmaceutical waste disposal, healthcare IT, two utilities, and a discount retailer. Note that although these names tend to be low beta, they are hardly low PE. Note that having the least max drawdown doesn't necessarily imply having the smallest standard deviation of daily returns.
|S&P component||Max drawdown (5 yrs)|
This second table shows the 10 components with the greatest max drawdowns. This list is certainly more concentrated than the first table. All except for 3 are financials/insurers/reinsurers. We have the old guard news media represented by Gannett (GCI), aerospace/defense by Textron (TXT), and renewable energy by First Solar (FSLR). If risk averseness is the game, then drawdowns is quite an interesting measure. It shows the worst-case for a single roundtrip trade. Note that trading results may be much, much worse than the max drawdown if a strategy gets repeatedly drawn down in a losing streak. Nevertheless, max drawdown gives some insight into the amount of risk we are taking on. In particular, max drawdown should give some insight into what kind of reserves should be kept. This, of course, isn't foolproof since past drawdowns do not necessarily predict future drawdowns.
Another interesting aspect of max drawdown is that there is really no relationship between max drawdown and daily returns. A regression between the two shows an R2 of a mere 0.0027.