One tool for developing independent inputs for our models is a simple scatter chart. Because we are building a relatively long-term model, we need to normalize our data so that long-term trends in earnings and stock prices do not become an issue. First, we must develop a simple normalized momentum indicator:
Now, let’s compare our data in a scatter chart. (We multiply our momentum by 100 so that the scales are easier to read.) First, we’ll look at both S&P 500 momentum vs. the S&P 500 momentum one week into the future (see “Moved by momentum,” below). We will use 16 weeks as a moving average length for both. There’s a clear linear relationship between the current value of the momentum indicator and the future value of the S&P 500 indicator. It’s not perfect — the data are relatively spread out — but the relationship is there.
“Driven by earnings” (below) shows the S&P 500 weekly momentum and our weekly earnings momentum in a scatter chart. Again, we are showing the relationship between the current value of the indicator and the future value of the S&P 500 momentum gauge. As we would expect, the data spreads and relationships are similar, and both show a linear pattern.