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>Although M's emphasis is not on predicting the market, he seems to say his
fractal
>generators can help give probabilities of various future moves
Who knows how he does that? It appears that he begins with a 3-piece zig-zag
(Up-Down-Up) which he calls a "fractal" (a 5-piece zig-zag is your standard
Elliott wave fractal) and proceeds to generate a simulated price chart by
replacing each segment of the original fractal with a scaled version of it.
This process is then repeated as long as one wants. It was unclear to me how
one would select the geometric proportions of the multifractals, then throw
the dice to pick which one to use each time he replaces a segment of the
original. Different people doing the simulation will get different price
charts by proceeding this way. I can see how these ideas could lead to
better "stress testing" of a portfolio as one can do this millions of times
picking different fractals, throwing the dice and calculating the
probabilities of the ensemble.
He certainly says nothing about price FORECASTING. The question here is not
how one produces a price chart after selecting a multifractal but how one by
working from a price chart goes backwards to generate the original
multifractal that the chart came from (invariance?). This may have
forecasting implications.
I would be very interested in how M's work with fractals could provide
answers to questions such as: Is the probability that the S&P will trade 100
points higher before it trades 100 points lower better than 66%? Has it
ever been? Or is the probability that the S&P will trade 100 points higher
before it trades 50 points lower better than 50%? Has it ever been? Maybe
his work doesn't address this type of questions. Or maybe he doesn't believe
such questions can be answered to the point where they can give an
exploitable edge to the trader.
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