A while back I examined a number of different ways to measure market breadth, with the intention of finding something that might give a good indication of market health. You can read the series here. Since then, I’ve started using one particular indicator that shows a decent predictive value. It was optimized on one set of data, and then evaluated on an ‘out of sample’ data set.
This indicator would have allowed you to miss the plunge of August 2015 for example. You would have gotten out of the market before the V-shaped dip of October 2014. It also would have gotten you out before the dips of the summer of 2012, November 2012, and the craziness of the summer of 2011. And it sent a red flag on August 6th, 2007, and kept you out of the market until April 22, 2009.
One event it missed was May of 2010. It’s not perfect.
Some might argue that this breadth indicator is too conservative. It is possible to make money in less-than-ideal conditions. Look at 2014 for example: the indicator had you out of the market most of the year, but it was a profitable year none the less. If you’re doing short-term trades, you might not care so much about this indicator. But for long-term trades, this seems like a pretty decent indicator.
So how does it work? You count up all the stocks that are current members of the Russell 3000 and that are up >30% in the last 60 trading days. You also count the number that are more than 30% down. You do a breadth diffusion calculation like this:
up30 / (up30 + down30 ) * 100
The magic threshold is 75. If the last ten days have a value greater than 75, it’s a ‘green’ day and ok to trade. If the last ten days have a value less than 75, it’s a ‘red’ day and you should exit long-term trades immediately. If the last ten days are neither all above or below the line, then you continue the status quo with no change.
On my site, I publish the value every day after the close of the US markets. I indicate red if there are “get out!” conditions, green if it’s time to get in, and “yellow” if it’s a “status quo” condition.