In trading and investing, as well as just about any other pursuit, analyzing how two or more elements react relative to one another can be a very powerful tool for developing an effective strategy.
To give you a great example of this from the world of sports, let’s examine what is know in baseball as a “shift.”
Although it was rarely used on the professional level until about 15 years ago, the first well-known instance of a shift occurred in 1946 when the Cleveland Indians player/manager Lou Boudreau shifted the majority of his players to the right side of the field to defend against Red Sox slugger Ted Williams – a left handed pull hitter (meaning he tended to hit the ball to the right) who achieved an incredible .400+ batting average.
By recognizing what the likely result of Williams’ at-bat would be, Boudreau was able to develop a powerful defense against it.
The shift was so effective – and thus so widely emulated by other teams – against Williams that it is estimated that the it shaved 15 points off of his lifetime batting average.
Despite it’s effectiveness, it wasn’t until the beginning of the 21st century, with the advent of statistical analysis and data-driven solutions like sabermetrics, that the shift really started to catch on.
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While it may have had a slow start, the shift is now used by almost every Major League Baseball team today. In fact, according to MLB.com, more than 17% of all at-bats end up in a shift these days.
And in keeping with the theme of this article, there is a correlation we can draw to our investing strategy that will help defend our portfolio against market downturns…
The Power of Being Able to Measure Correlation
One of the key thoughts that institutional money managers keep in the front of their minds is the diversity of a given portfolio.
We could dig into modern portfolio theory and other academic claptrap here, but let’s cut right to the chase. To most money managers, having a diversified portfolio essentially means that a money manager wants to make sure that all the elements of the portfolio don’t go down at the same time.
So if the stock market has a 15% sell off, a portfolio manager doesn’t want the whole portfolio to drop 15%.
To make this happen, you need to find assets that don’t move in the same way. The mathematical term we use for measuring how similarly different instruments act is correlation.
Two things are correlated if they move in the same direction at the same time. This would be the case almost all the time for the S&P 500 index and the Nasdaq index. They both tend to move up and down at the same time, though one might move more in that direction for any given timeframe. Here’s a chart that is typically used to measure the correlation of two instruments (don’t worry that the chart’s a little busy – there are explanatory notes below):
Notes for Red Circles above:
1 & 2: The dark line is the S&P 500 index, and #2 shows its scale on the right side of the chart
3 & 4: The grey line is the Nasdaq index and the #4 shows that its scale on the left side of the chart
5: This is scale for the correlation coefficient between the S&P 500 and the Nasdaq. The scale runs from the highest level 1.00, which would mean perfect correlation or that the two instruments always move in the same direction. A reading of -1.00 is perfect inverse correlation, meaning that the two instruments always move in the opposite direction of each other. A reading of 0 means non-correlated or that the two have no relationship to each other
6: You can see that the the S&P 500 index and the Nasdaq are highly correlated. This charts shows correlation for the movements of the past 50 trading days (about 2 ½ months). And the correlation between the two is in the high 90s (currently at 0.98).
7: Periods of lower correlation do happen, like in the fall of 2016 when the mega tech stocks like Facebook(FB), Amazon (AMZN), and Alphabet/Google (GOOGL) swooned while the S&P 500 held steady. But you can see that for almost all periods the correlation is very high.
So having both an S&P 500 ETF and a Nasdaq ETF in your portfolio would give very little diversification.
What would give some diversification vs. U.S. stocks? The classic answer is U.S. Treasury bonds. Let’s see how that looks on our chart:
Here we can see that most of the action stays with an inverse or negative correlation (they move in opposite directions) with brief periods of correlated moves. In particular, look at how inversely correlated the two became at during the big drop at the end of last year.
Now that we have a useful tool for measuring how assets move relative to one another, in our next article we’ll look at how cryptocurrencies like Bitcoin move in relation to other assets. Spoiler alert – this mathematical analysis is why I think cryptocurrencies are becoming a whole new asset class.
So stay tuned…
Great trading and God bless you,
D.R. Barton, Jr.