A major issue in statistical physics literature is the study of the long range dependence phenomenon usually presented in natural, social and financial processes. In particular, a big part of this literature relies on the determination of a parameter known as the Hurst exponent. Although many methods have been proposed to deal with this task, none of them are suitable for any time series and so...

The Hurst exponent (H) is a statistical measure used to classify time series. H=0.5 indicates a random series while H>0.5 indicates a trend reinforcing series. The larger the H value is, the stronger trend. In this paper we investigate the use of the Hurst exponent to classify series of financial data representing different periods of time. Experiments with backpropagation Neural Networks show ...

Estimation of the Hurst parameter provides information about the memory range or correlations (long vs. short) of processes (time-series). A new application for the Hurst parameter, real-time event detection, is identified. Hurst estimates using rescaled range, dispersional and bridgedetrended scaled windowed variance analyses of seizure time-series recorded from human subjects reliably detect ...

In this paper, we show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range analysis (R/S), multifractal detrended fluctuation analysis (MF − DFA), detrending moving average (DMA) and generalized Hurst exponent approach (GHE) estimate Hurst exponent on independent seri...

The Hurst Exponent is a dimensionless estimator for the self-similarity of a time series. Initially defined by Harold Edwin Hurst to develop a law for regularities of the Nile water level, it now has applications in medicine and finance. Meaningful values are in the range [0, 1]. Different methods for estimating the Hurst Exponent have been evaluated: The classical “Rescaled Range” method devel...

Hurst’s seminal characterisation of long-term persistence (LTP) in geophysical records more than seven decades ago continues to inspire investigations into the Hurst phenomenon, not just hydrology and climatology, but many other scientific fields. Here, we present a new theoretical development based on stochastic Hurst–Kolmogorov (HK) dynamics that explains recent finding coefficient increases ...

a r t i c l e i n f o JEL classification: F30 G14 G15 Keywords: Hurst exponent Financial crisis Financial contagion Efficiency Stock markets MFDMA algorithm Copula models This study analyzes how the 2008 and 2010 financial crises, which began in the US and Greece respectively, affected the Hurst exponents of index returns of the stock markets of Belgium, France, Greece, Japan, the Netherlands, ...

The geometric Brownian motion (GBM) model is a mathematical that has been used to asset price paths. By incorporating Hurst parameter GBM characterize long-memory phenomenon, the fractional (GFBM) was introduced, which allows its disjoint increments be correlated. This paper investigates accuracy of and GFBM in modelling Malaysia’s crude palm oil simulation, see display persistent or anti-persi...