Has buying losers this year worked?
This year is probably the first time in a very long time that buying losers failed to generate any meaningful return. It used to be that when leaders topped out, one could safely get into laggards for value and they were good for a technical bounce or two. While the year started out with laggard names like SMC and PCOR rebounding strongly after a terrible 2015 performance, one would have been better off sticking with the really strong ones like SECB, SMPH, AEV, and MPI if you wanted to make money trading index names. You see, trying to bottom pick laggard names like TEL, GLO, AGI, MER, and EMP has been the wrong strategy.
We computed the average percentage change of the leaders and laggards YTD and we noted that the spread was around 3990 basis points (even wider when the market was trading near all-time bubble highs). So not only have leaders done remarkably well during upswing to some extent the same leaders have been able to preserve gains better while the sell-off in laggards even accelerated while the market corrected the past three months. It’s hard to see if this trend will persist in 2017 but if we go by first principles of technical analysis this trend will likely persist.
The story is a bit different in the non-index space where we saw a complete reversal in fortune for this year’s darlings DD, X, MRSGI, and IS. It is also ironic that dogs that like WEB, LIHC, DIZ, STI, and PPC are the ones trading near highs going into the end of the year and are the ones expected to continue to trend higher when we start all of this all over again next year.
So to answer the question about buying losers, it doesn’t pay to buy index laggards but it is worth looking at dogs in small and micro space given their tendency to mean revert and surprise. Our own non-consensus, high conviction call on mining this year provides us with proof of concept of mean reversion in non-index names.