Using constant volume scale for modeling fractal characteristics of financial time series (A.Didenko, M.Dubovkiov, B.Poutko)

We propose to use intrinsic time scale based on volume when measuring fractal dimension of financial time series. (Dubovikov, 2004) introduces a new method of measuring fractal dimension which is superior to other methods, including well-known Hurst index in terms of  speed of asymptotic. As a downside, estimates obtained with new method, are noisy and hard to predict, which in turn complicates its use in practice. We demonstrate that sampling time-series across volume scale, instead traditional physical time scale, could significantly improve predictability of fractal dimension.

(Published in Russian in “Science in Modern Information Society IV” , Fall 2014, ISBN 978-1-50232-179-4)