This isn't so much to generate debates or flames, but for those whom kindly PM'd me in the past asking for the 75% rule in simple terms, I did a small writeup and shared some R code. Hopefully, it changes the way you see random walks a bit. One of many insights I've had (in this case public, but often overlooked) on the issue of gaussian based random time series. Please PM me with any egregious errors, but proofs of the basic concept are contained in the book I mentioned on the writeup. Cue... yeah, but markets aren't gaussian... 10...9...8... http://intelligenttradingtech.blogspot.com/2011/03/can-one-beat-random-walk-impossible-you.html
Interesting. Thanks for posting. I had no idea that was your blog. I check it weekly, but its been a while since you've put anything up on it.
Increments of Uncorrelated Time Series Can Be Predicted With a Universal 75% Probability of Success, D. Sornette: http://arxiv.org/abs/cond-mat/0001324
Basic assumptions, yes, but much harder to do in reality on multiple instruments. Uncorrelated doesn't mean anything either. Uniformly, all are correlated.
I think the point here is that the signals are self fulfilled... If large number of persons/systems rely on the same support level to start a trade at the same time (with the Spontaneous Synchronization rule), then that support level works. The same for EMA crosses, if lots of persons rely on the same EMA periods, then maybe the system will work. So, the idea is to re-evaluate continuously the parameters of the EMAs to match the current value of most of the traders. That way a system can be "tuned" with the "frequency" of the crow.
Linear regression analysis is like any other type of analysis. The opinions derived from the model are usually more a function of the analyst's interpretation than the quality of the model. One of the daily tests I conduct is whether there is the presence of a unit root or not and there are days when it is present and I discard it and vice versa.
I wonder about the following thought experiment: if you create a price trajectory based on a random walk with parameters of your choice, with suitable memory length (i.e., dependence of current price on N last prices + random factor) then what would happen if you tried to "predict" future prices from your random walk trajectory? Naturally your prediction accuracy would be better and better the more memory your random walk trajectory has. I suppose you could measure the memory length or persistence length based on the autocorrelation function of your price trajectory (even for real price trajectories). Just some thoughts.
============= Well actually any trend line maybe helpful; not to predict the future. Trends are not predictions; nor are trend lines predictions. 200 dma is more useful[again , not as a prediction]; perhaps that is because much more investors, much more traders look there............................................... However you may want to consider what General [Top trader]Haggerty said; many institutions will not admit to using a 200 dma...
Could Maestro's concepts be used in directional trading like FX or stocks prices or they apply to options pricing only?