High Correlations? And what?

Sep 15, 2011

This is getting silly.  Portfolio managers around the world are complaining about high correlations.   The truth is that things that are somewhat correlated to start with (stocks) will see their correlations go higher when volatility rises -- it's not a mystery, its mathematical.   This has happened many times and while people are now saying ‘all-time high correlations’ – this misses the much more important point.

Crises cause securities to have larger than normal moves --- and correlation is a measure of how far one security moves in relation to the movement in another. Essentially, when one security has a big move vs its history, does the other also have a large move relative to its historical movement?   

Correlation is somewhat of a tricky topic.   Something may move very little but still be highly correlated to something that drops a lot.   Look at the utility sector (XLU) vs the S&P 500 (SPY).   XLU has a 0.89 correlation to SPY over the past 60 days.   But XLU is slightly positive so far in Q3 while SPY is currently -9.5% QTD.

Let's do a portfolio example just to see how better to think about this.  If I take 85% ultra-short term bonds (t-bills), but blend it with 15% KBE (bank industry etf) and I compare this to 100% bank index, the result is like this:


You can see how the cash has diluted the loss to just -3% this quarter.   (KBE is -21.1% during the same period).   The correlation has been 0.99 - 1.00.   From this standpoint, a correlation of 1.00 has told you nothing about the true risk in this case.   The correlation is so high obviously because the combination of KBE and t-bills moves a lot whenever KBE moves a lot.  It doesn’t move a lot on an absolute basis --- but it does move a lot relative to its historical range of movement.    Easy enough.


So back to using different securities --  utilities high correlation with the S&P 500 hasn't prevented it from going up recently (slightly).   Utilities have gone up despite the correlation between these two rising.  Thus, when portfolio managers are complaining about high correlations – they are just really complaining of the natural result of high volatility.

Earlier this year we created a simple – but what we think is more useful --- application than your standard correlation matrix.   The ‘Down Day Stats’ module measures how much various ETFs move on just the days a benchmark drops more than X%.


Let’s use the industry ETFs (equities only).  We can use SPY to show all down days this year.   You find that defensives like Pharmaceuticals, Food & Beverage and Telecom outperform on down days.   Energy and mining do the worst.


But then flip it around, use the inverse S&P 500 (SH) to show what happens on up days.   Energy and mining are best and defensives are worst.   They are all highly correlated – so you must consider volatility #1 --- and then think about correlation #2.   It would be nice if lots of equity securities were not correlated.  But the fact is they are and it gets worse whenever there is a crisis. If you want a market that is less correlated, then you need to have an extended period without any volatility storms.


Summary:  If the market goes down, volatility will rise and this will push correlations up.  If the market goes up, the reverse will occur.   How many times have we seen this over the past 15 years? Many.


Why would it stop in 2011?

See also 2010 Posts On Correlation



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