I’m starting to work on understanding “Scaling in the Norwegian Stock Market” by Skjeltorp Physica A283 (2000) 496-582. This paper applies chaos theory and fractal analysis to a stock market.

Are you familiar with this paper? If so, can you describe how your algorithm might apply in an analysis such as this?

If you are interested in long cycles and crashes, then it is perfectly adequate to use readily available daily data in the same way. In general, the North American markets are the least volatile, followed by European markets, with larger countries being less volatile than smaller countries. Asian markets tend to be the most volatile.

I practiced cardiology for forty years and would expect failure of medical devices to be a memory-less process with numbers of events over fixed intervals to have exponential tails. If you can show that this is not true with a quantile plot of your tail data versus the ExponentialDistribution[1], and if there is a good linear relationship in the quantile plot the Log[tail data] to the ExponentialDistribution[1], that would be evidence for power tail scaling which might indicate a fractal process.

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