Given enough data points, every stock will have a natural drift — the range of price activity which the target security gravitates toward over a period of time. However, trading based on this drift can be a maddening exercise because of the myriad directions the market can take. Further, determining a specific outcome from the aggregate of all pricing behaviors is a fool’s errand.
That’s where the quantitative approach comes to the rescue. Rather than trying to decipher the randomness of share prices, I instead developed a sequencing logic, somewhat similar to Morse code but for Wall Street. Essentially, the idea is to group securities into behavioral states consisting of 10 weeks each. From there, it’s easier to map out a decision-tree logic to determine how a market responds to different behavioral states.
