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Thank you for taking the time to read the Medium article and for your interest in the source code.
This repository does not contain an example of applying the module to the SP500, or for that matter the application of the module to any real market. However, this is an astute question and as such, deserves attention. I'll refer you to a block quote from "The (Mis)behavior of Markets" by Benoit Mandelbrot.
How do you use these ideas as a real-world financial tool? First, the equations need to feed into a computer model. The model must work two ways, forward and backward. Forward means that we should be able to construct artificial price charts from the fractal seeds, just as we did with the cartoons. Backward means that we should be able to take raw price data, analyze it on our computers, and estimate the key parameters that the multifractal model requires. Then using those values, we should be able to tell the computer to reconstitute the market—to generate an artificial price series that differs from the real one but follows the same statistical pattern. That is exactly what we have done, repeatedly, using a common computer technique called a Monte Carlo simulation. The result was excellent forgeries of the market—not identical, but statistically similar to the genuine article.
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My understanding is that the "key parameters" here are the coordinates of the first turning point of the generator and the weights of the binomial multiplicative cascade. Once these key parameters are resolved, simulate the target market with Monte Carlo in hopes of gaining a better understanding of whatever part of that market you are interested in.
Perhaps you are familiar with machine learning search algorithms and have an idea as to the best approach for resolving the key parameters.
Hi,
Happy to see there is an excellent example of applying fractal geometry on stock market.
I have read your medium articles and the examples in github.
Marcus from Hong Kong
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