why statistics matter
A great movie called Moneyball is really all about baseball, a true story about two guys Bille Bean and Peter Brand, who developed a system for selecting a winning team that cost substantially less than millonaire teams like the New York Yankees would spend.
The thing behind this story was that not only did they understand that some players were undervalued and bought these players, but they had the courage to stick with their system in the face of a string of successive losses, despite the world thinking they were crazy.
It’s much like trading in that sence, as once you have a system that you have devised and backtested, you have to have belief in it and trade it, even when you have those periods of losses.
Armed with the statistical knowledge, the trader might gain additional confidence in his trade idea and might even trade it more aggressively.
Knowing what to expect based on precedent—and then seeing if the market actually follows its historical tendencies—helps prepare the minds of discretionary traders for a variety of market scenarios.
As example, I know from my statistical studies that 70% of the time, the imbalanced markets tend to revert back to their balanced prices, especially under conditions of relatively low momentum.
Another stat shows that if a market opens around previous value area and then remains into value increasing volume, there is an 80% chance that the market will rotate all the way to the other side of value.
These are some statistical E-Mini SP500 numbers, that can provide guidelines for discretionary traders:
-95% of the time, one side of the overnight (ON) range is broken.
-25% of the time, both sides of initial balance (IB) are broken.
-96% of the time, one side of initial balance (IB) is broken.
-66% of the time, the initial balance high (IBH) is broken.
-54% of the RTH days are a Normal Variation Day (IB>5 points)
-25% of the RTH days are a Neutral Day (Both IBs are broken)
-18% of the RTH days are a Trend Day (RTH Range>20 points)
