What exactly is wrong with treating two conceptually similar trading indicators as independent pieces of evidence?

External question — Personal Finance Stack Exchange Author: user10478 Original post: https://money.stackexchange.com/questions/158830 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Suppose you come across a financial trading system which starts by checking a security's 200-Period Moving Average, either by itself or in conjunction with the security's price data, perhaps signaling bullish evidence while price is above the 200 MA and signaling bearish evidence while price is below the 200 MA, or whatever other example interpretation you like. Then the system checks the security's 199 MA for confirming evidence, with respect to the same interpretation as the 200 MA. Then it checks the security's 201 MA for more confirming evidence. Maybe it checks 5 or 7 such clustered MAs before feeling confident if the evidence all points in the same direction. This is obviously an absurd trading system, but I've been mistaken in my understanding of how to quantify its absurdity. I used to call this problem autocorrelation. I believed the term to mean "automatic correlation," describing (at the most extreme end of a continuum) two indicators that automatically produce identical bullish/bearing evidence, buy/sell signals, etc., just by virtue of their construction, regardless of their explanatory power derived from the security, and as a result, the pair of indicators together could be no better than the more predictive of the two. Similarly for trading systems involving more than two indicators. I have since learned what autocorrelation actually means, but now I don't know how to quantify the above problem, in order to identify it in less obvious contexts. For the special case in which a trading system's overall decision rule is a linear combination of the pieces of evidence output by its indicators, would this be an example of the phenomenon known as multicolinearity? What would it be studied as in the more general, not-necessarily-linear case?

External answer — Personal Finance Stack Exchange Author: Pete B. Original post: https://money.stackexchange.com/a/158834 License: CC BY-SA 4.0 — https://creativecommons.org/licenses/by-sa/4.0/ Adaptation: HTML converted to plain text; contact email addresses removed. Imagine you want to take a political poll on how people feel about an issue. Your methodology is that you poll people in the same household, or maybe that live on the same street. Did you get a representative sample of the entire country? Obviously the answer to that is "No". By using 185, 190, and perhaps even the 50 day moving average to confirm conclusions about the 200 day moving average is akin to this. You are essentially using the same data to form a conclusion. Even using something like Bollinger Bands might not be dissimilar enough for confirmation as it uses moving averages in its calculation. IMHO the goal, these days, of technical analysis is to predict which direction the Wall Street bots will predict a stock will move and then take action first. It is essentially an arms race.