Forecast With Accuracy, Not Like a Professional
Another example of capital markets technology I developed is something I call sentiment-based bell curve forecasting. Like PSRs, I used it for a number of years, but this technology as I first introduced it in the 1990s is today largely priced into the market—in some applications and in some places. But in other applications and places, it still works (we get to that in a bit).
We all now know if everyone agrees some specific market move will occur, it likely won’t. But let’s consider why for another moment to lead us in a circuitous path to some valuable technology. Remember our analogy from the Preface about creating a representative sample of investors for a poll? You know polling technology is sufficient because it can discern within a predictable level of error the outcome of the election of a president, governor or senator just beforehand. This technology is mature. The pollsters start by building a representative sample of the actual voter world. If the sample isn’t built correctly, the polls don’t work; but if the sample is representative, it needn’t be huge. You can forecast a big state election with a sample of just 500 people if they’re picked right.
So we took our imaginary sample of investors and polled them about what they thought the market would do next month, let’s call it March. And they overwhelmingly concluded the market would soar in March. So we knew it couldn’t. Because if they were overwhelming in their view ...