If you’re looking for the indicator with the highest correlation to the S&P 500, it’s not GDP growth or even earnings growth.
Some would say: No, it’s butter production in Bangladesh.
In a paper published two decades ago, mathematician David Leinweber and portfolio manager Dave Krider claimed to have found that butter production in Bangladesh had the tightest correlation to the S&P 500 of any data series they could find.
In their view, collectively with American cheese production and the Bangladeshi sheep population, this three-variable model “explained” 99% of the S&P 500’s movements.
Now, before you roll your eyes, Leinweber and Krider published the study in jest. These are geeky quants enjoying geeky quant humor.
The problem is that a lot of traders aren’t smart enough to know it’s a joke.
In an article he wrote for Forbes a few years ago, Leinweber commented that 20 years later he still gets calls to his office asking for the latest Bangladeshi butter production figures.
In my opinion, there is absolutely no plausible reason why Bangladeshi butter production would predict S&P 500 returns.
So, when looking at any model, I think you should always ask yourself: Does it intuitively make sense?
As an example, I spent most of last year backtesting a stock trading model that combined several value investing metrics with momentum metrics.
The result was a portfolio strategy that delivered 43% backtested annual returns from 1999 to the present, utterly crushing the S&P 500.
Now, could this be an example of overfitting the data?
Maybe. But I don’t think so because the approach intuitively makes sense.
Countless studies (most famously Fama and French’s 1993 study; click here to download it) have shown that value investing outperforms over time, and most of the famous investors throughout history, such as Warren Buffett and Benjamin Graham, were value investors.
Value investing works, in my opinion.
Meanwhile, various momentum and trend-following strategies have also been proven to outperform over time.
So, it stands to reason that combining value and momentum would lead to solid results.
I can’t guarantee that the future live results will live up to the backtest. You know the drill: Past performance is no guarantee of future results.
But I’m betting it generates better returns than a Bangladeshi-butter-based market timing model.