This is an indicator featured in one of Ernie Chan's mean reversion strategies. The Hurst Exponent will analyze a time series and determine whether it is a geometric Brownian motion, mean reverting or trending. This could be useful as a filter (to avoid whipsaws for example) or for offline analysis (such as data mining mean reversion opportunities).
The Hurst calculation considers a value > 0.9 to be trending, but as this appears to seldom be reached, I have designated it a "StrongTrend", whereas anything that exceeds the limit of geometric Brownian motion is a "Trend".
If there's any enthusiasm towards general utility I will submit a PR with unit tests.
Nate Betz
This is very interesting. Thanks for contributing it!
I'm still playing around with it, to try to get an idea of useful parameters for period and lag. The performance may be a bit of a concern though; it seems computationally very expensive compared to most indicators, but this may correlate with the period used? It looks like it is a performing a new linear regression for the series for each new data point.
James Smith
James Smith
There's at least one prominent proponent for the Hurst Exponent:
http://www.priceactionlab.com/Blog/tag/hurst-exponent/
He has recently published a (paywalled) article with the Hurst exponent being used to analyse SPY for a possible bull market top. I'd say that the large data requirements of the Hurst makes it apprporiate for this kind of long term analysis. It might be worth trying to recreate this...
Petter Hansson
Nice work, better than my own implementation. I would like if this or something similar could be added to Lean's indicator collection.
Alexandre Catarino
Hi guys!
I have opened a GitHub issue for this indicator implementation:
Adds Hurst Exponent Indicator #3924
James Smith
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