QuantEcon.jl

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While looking at the documentation for this package I was surprised to find that it does not contain any function for Hurst exponent estimation. I feel like it would be a very appropriate addition for this package. Also a general fractal dimension estimation maybe via the common box counting method would be good. What do you think ?

Hi @spirosbax, could you please give some overview of applications that you have in mind?

Well for starters, the Hurst exponent provides information about the memory of a timeseries. It can be seen as describing the ACF by a single number and it is very useful in classifying time series. An H value of 0.5 means that the series is a random walk while a value closer to 1 means that the series follows a trend. For this reason it is used a lot in financial time series as well as in time series analysis in general. The general Fractal Dimension definition is directly related to the Hurst Exponent, in particular D = 2 - H . But the definition is different depending on the application. In finance you can use the box counting method in order to see how the volatility or complexity of a time series changes as you change the length of the measurement window.

Kind Regards, Spiros Baxevanakis On Mar 7, 2020, at 01:59, John Stachurski <[email protected] (mailto:[email protected])> wrote:

Hi @spirosbax (https://github.com/spirosbax), could you please give some overview of applications that you have in mind?

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