5 Tips to make better predictions.
By: Timo Kerremans
Tags: Self-awareness, Self Improvement, Predictions, Thoughts

1. Prediction range and certainty

No prediction has any value if it lacks an indication of its certainty. This is too often overlooked because in most cases the degree of certainty is implicitly assumed in the prediction itself, or at least approximately so. For instance, If I told you I am able to predict the card randomly drawn from a deck, you will most likely be impressed. My prediction is of course notable because I only have a chance of roughly 2% to be right. The less likely a predicted event is, the more impressed we are when it actually occurs. We all have an intuitive feeling of how these probabilities work. What is often forgotten, however, is that the degree of certainty is equally important. In the example above, I failed to give you the degree of certainty with which I made the prediction. The reason you did not protest to this, or even noticed it, is because you assumed that I was 100% certain of my prediction. Let me show this basic idea by explicitly stating the certainty in the previous example. Compare the following two predictions. If I say “The ace of diamonds will be drawn, I am 100% certain of it!”, then it gets interesting when the card actually shows up. However, if instead I exclaimed “The ace of diamonds will be drawn, I am 2% certain of it!”, I would rapidly lose your attention because I would be stating the obvious. Even in the case the card did show up, it would be discarded as mere luck. Providing the measure of certainty seems very artificial in this example, because the second prediction never occurs. However, providing your prediction with an indication of certainty not only makes it more meaningful, it also allows for better comparison. In the example above, the first prediction clearly has more value to it than the latter one.

The general tendency to omit any expression of certainty becomes more problematic when the predictions concern vastly more complex situations. For example where the exact odds of each outcome are unknown. Moreover, in these real life situations, we are often confronted with possible outcomes that are continuous or ordered on a scale (as opposed to cards in a deck). For example, predicting a number of book sales, the price of a particular stock, or the number of days within which a particular event will occur. In addition to providing a certainty with our prediction, we have to make predictions in terms of ranges. Let’s see how this is done, starting with an example.

In the stock market it makes no sense to predict what the exact price of a particular stock will be within any time frame. Stock prices take on (near) continuous values. Say a particular stock is worth $100 today, and you try to predict its price a year from now. Whatever number you predict, it will be extremely unlikely that it will actually be priced at exactly that amount. This is because there are so many possibilities. If you predict the price to be $140, then why not $140.01, or $139.43? You notice that the certainty of your prediction will become tiny, making it quite a silly and useless prediction: “I predict the stock will be priced at $140, I am 0.03% certain of it.”. Of course we all intuitively handle this problem by allowing for some margin of error, saying that it will be priced around $140 in our example. However this can become quite fuzzy for edge cases: does $130 still fall within the prediction? We can make these intuitions more precise by working with a predictive range. This term is self explanatory: instead of predicting an exact number, we predict a range in which the outcome will likely fall. How likely? Well, that’s where we address the certainty of our prediction. We simply express the certainty we have that the eventual outcome will fall within a specific range. In our stock example such a prediction would look like “I predict the price to be between $130 and $145, I am 90% certain of it.” Instead of focusing on what the eventual price will be, it states that you would be extremely surprised if it ended up being outside this range; either below $130 or above $145.

In this form, predictions can be compared with each other in a very precise way. Both the range and the certainty we provide tell us something about how convinced we are of our prediction. These can in principle be used to compare to other predictions. However, in the case where we use ranges, the certainty is often fixed at 80% or 90%, and we are left with adjusting only the range. In those scenarios we formulate the prediction as the range in which we think the outcome will fall with 80–90% certainty. As a example to see how such a comparison works, let’s consider elections between two candidates and compare the following three predictions:

I am 90% certain that candidate A will win with 50%-100% of the votes. I am 90% certain that candidate A will win with 51%-53% of the votes. I am 90% certain that candidate A will win with 49%-55% of the votes.

Of these three predictions, both 1 and 2 are really convinced that candidate A will win. There is, however, a notable difference. Prediction 1 is completely uncertain by how many percentage points the victory will be, whereas prediction 2 expresses the fact that elections are always a pretty close call. In terms of ranges, 1 has a much larger range than does 2. Prediction 3 in the list might at first seem odd because it looks like it implies that candidate A can win with 49% of the vote. However, this merely expresses the fact there is a chance for candidate B to win. Similar to prediction 2, it expresses the fact that the election will be a close call. Of these three predictions, 2 is the most valuable since its range is the smallest one, while the certainties are all equal. To conclude this example, note how all of these predictions are significantly more useful than the often used “I think candidate A will win.”

On a day to day basis, the exact numbers don’t really matter so much. As long as you try to formulate your predictions in terms of ranges and provide them with an indication of certainty, you will start to make more valuable predictions. Additionally, this way of predicting allows you to evaluate them over time and thus become incrementally better at them.