Many people assert that correlations totally break down in down markets. I created a bunch of portfolios from the Russell 2000 going back to July 1962 using the prior 36 months of data up to 1999, and the prior year’s daily data from 1999 onward. I extrapolated backward the bottom market cap, relative to the SP500 index, to get a replica of this grouping back to 1962. This insured I only had real stocks that could be traded.
I then created 5 portfolios, each with 100 stocks. First, those with the highest and lowest betas. Then, those with the betas nearest 0.5, 1.0, and 1.5. These are all freely available, without any registration or any work, here.
Here are the betas in the up and down months. There’s a tendency for betas for low beta stocks do move towards one, but then, high beta stocks move away from one. In any case, the effect is not huge.
Correlations, which are measures of how linear a relationship is, are higher in down markets, but again, they aren’t game changers. Correlations certainly do not ‘go to one’, or ‘go to zero.’
A lot of quants have the very a strong opinion on the meaningless of correlations, and I hear from a lot of them via that Black Swan guy’s acolytes. These people are simply letting the perfect be the enemy of the good. Correlations, and betas, vary over time. Yet they are broadly consistent in up and down markets: stocks grouped by prior high betas have higher betas in future up and down markets, while lower beta stocks have lower betas in up and down markets. It’s all relative, but it’s very meaningful, and has powerful implications. You can design a portfolio with lower than average volatility or beta. Sure, you won’t create a portfolio that has no basis risk, no downside risk, but that’s an absurd objective.