Curiousity And Causality


"The important thing is not to stop questioning. Curiosity has its own reason for existing. – Albert Einstein

I'd love to have talked to Albert Einstein about stocks. Everything the man said or wrote suggests he constantly sought to understand why A led to B and B led to C. Stock analysis is all about that kind of causality. Of course, such analysis is challenging because causality can be impossible to quantify.

Curiosity about causality got me thinking about why investors put so much value on economic trends. Is a strong labor market good for stocks? How about robust retail sales or demand for new homes? Financial pundits like to tie all three of these trends to the fate of stocks, mostly because the labor, retail, and housing markets all reflect the relative health of consumers and the businesses that sell to them.

It seems reasonable to expect all three trends to show some correlation with stock returns. And there is correlation, though not as much as you might think.

The coefficient of determination estimates the percentage of the index's movement explained by a particular economic trend. Note the use of "explained" rather than "caused," because we can't truly know what causes the market to behave in a certain way. At best we can ascertain whether the movements of one variable are connected to the movements of another.

Let me boil the data down to three key points:

1) Retail sales had the most explanatory power over the last five, 10, and 25 years, though it never accounted for more than one-third of the index's movements. New-home sales had the lowest correlation with stock returns over the last 10 and 25 years.

2) Coefficients of determination were lower during the last 10 years than during shorter or longer periods, particularly for the labor and housing markets. This makes some sense, as the decade includes a period of unusual conditions for both markets, data that predates the last five years and smooths out over the last 25.

3) The labor market has had a positive correlation with market returns (both payrolls and the index tend to rise at the same time) over periods of 25 years or longer, but has been negatively correlated over the last 10 years. During that decade, we saw a period of 18 months (February 2009 through July 2010) when the market rose despite job losses.

This study didn't unearth a new, super-effective way to predict market movements. However, such exercises have value whenever they provide new information. In this case, the correlation numbers corroborated a statement the Forecasts has made before, one worth reiterating today.

Do pay attention to economic data because it provides a snapshot of a slice of the market at a particular time, information always worth knowing. But don't live and die by the data, because even the most predictive economic trends only explain a small portion of the stock market's behavior. Particularly over short periods, those economic trends can point investors in the wrong direction.

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