The Art of Prediction Events

Forget astrology. Forget positive thinking and laws of attraction.

If you want to predict events you have to have the numbers. It’s all about data.

We as humans already do this naturally, subconsciously. Sometimes even without knowing. A bold example is seeing some clouds and smelling subtle ozone changes. Perhaps the relaxing feeling of more negative ions in the air. We know that it is going to rain. Sometimes even without a cloud in the sky …

Why because he had enough data. Catching a baseball is another good example. The moment the ball leaves the thrower’s hand, your body is already moving into position to catch the ball; predicting the flight path and where the ball will be in the future. Again. Data. We see the release point, trajectory, and velocity, and our minds do fast trigonometry and how hand is waiting in the right spot to catch the ball.

Las Vegas and online sports betting sites predict the future all the time. They have huge amounts of historical data and look at everything from the weather, to recent performance, and all manner of situational statistics.

But what about predicting markets? Are there things you can practice, some hard rules you can put into place? According to the Harvard Business Review, yes.

The first thing you need to evaluate the risk by mapping out a cone of uncertainty. I’m not going to go in-depth about how to map out a cone of uncertainty. If you don’t know, it’s not too difficult of a concept. The main thing is to factor in as much as you can to help you with the decision-making process. Are there things you are overlooking? Look at the insanely improbable to the highly-probable and everything between to get your cone’s edge.

After you have this, it’s time to look for the S-curve. It’s not normal for change to happen in a straight line – even though that is how we want to think of it. So, you must identify the curve and find the inflection point (essentially the point where the curve changes) before it happens. Once you identify the curve, you can start looking back in time from there to determine factors that lead to this change and hopefully, forecast the inflection point beforehand.

Once you feel like you have a handle on the emerging curve, really dig into those potential indicators that are on the left side of the S-curve. Gather as much data as you can and be sure to look farther back in time than you are trying to forecast forward. Paul Saffo suggests that you look back twice as far as you are trying to look forward. Think about predicting the outcome of a football game. It’s only one week away, yet they are looking back at months worth of data and perhaps smaller sample sizes of head-to-head data that stretches back for years.

But even when you have all the data, intuition still plays a big role. Ultimately it’s up to you when to make a decision. So, don’t rely solely on models that are given to you. Make your own model using factors that the other may not have considered. Compare, and then trust your instincts.

