Thank you for the link. There are a lot of experiments these days similar to the one presented in this video that illustrate the principle of "Small World" http://en.wikipedia.org/wiki/Watts_and_Strogatz_model networks used to create many known types of behavior. Spontaneous sync and synchronized chaos are the two main models that I used for my algos. The whole conversation in this thread revolves around the simple concept: Markets are chaotic systems that use Deterministic rules to create random chaotic behavior with a very stable strange attractor http://en.wikipedia.org/wiki/Attractor#Strange_attractor . Because markets are the "Small World" http://en.wikipedia.org/wiki/Small_world_networks type of networks they sometimes produce right conditions to create spontaneous synchronization between their parts and cause "flocking" behavior. At that time by finding the path of the flock one can make extremely reliable predictions with regards to the price movements associated with the flock's movement.
This robot bird flocking is not spontaneous synchronization. It is guided algorithmic synchronization. IMO no relation to market related phenomena at all.
It seems to me that the next step in creating a trading system based on the average market participant's faulty understanding of probabilities would be to find some recurring situations in which market participants are trying to use their faulty perceptions of probability to trade. One possibility that occurs to me is oscillators, where the common perception is that overbought or oversold readings indicate a higher probability of price reversing. If one could find some recurring situations where correct bayesian analysis indicates that an overbought/oversold condition actually results in a higher probability of continuation rather than reversal, then one could perhaps find an edge trading against the oscillator users. What other common situations exist where market participants' flawed perceptions can create an edge? It seems like trendlines and trading ranges might have some possibilities, though its less clear to me where to look for the edge there. The idea of trading on market participants' misunderstanding of probabilities seems like a fertile area for exploration. Thanks for sharing your ideas Maestro.
What counts in the markets is purchasing power not perception. Purchasing power creates direction. If the view of the majority is flawed but they have enough purchasing power it is not flawed posteriori. This is one major flaw of Bayesian analysis.
Your post and GS's post before you, well show, the basis of Behavioral Finance. Any person with any plan and systemmic strategy can improve it immensely once they correct their belief systems and rid them of your stated beliefs. All perception, automatic or not, comes from two ingredients. By not having any perception possible, then there is no way to move forward. It is very important to find out why Bayes and his ideas are not applicable. Then when Bayes is replaced, it is necessary to use the correct replacements.
The brown cow looks just like intradaybill. Integrated that Lagrangian yet?. Low and High Meander calc yet?.