Is Hurst Exponent Value Useful in Forecasting Financial Time Series?

Is Hurst Exponent Value Useful in Forecasting Financial Time Series?

We estimated Hurst exponent of twelve stock index series from across the glove using daily values of for past ten years and found that the Hurst exponent value of the full series is around 0.50 confirming market efficiency. But the Hurst exponent value is found to vary widely when the full series is split into smaller series of 60 trading days. Later, we tried to find relationship between Hurst...

Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series

We investigate the use of the Hurst exponent, dynamically computed over a weighted moving time-window, to evaluate the level of stability/instability of financial firms. Financial firms bailed-out as a consequence of the 2007–2008 credit crisis show a neat increasewith time of the generalized Hurst exponent in the period preceding the unfolding of the crisis. Conversely, firms belonging to othe...

Hurst Exponent and Financial Market Predictability

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 ...

Evaluation of Hurst exponent for precipitation time series

A major issue in time series analysis and particularly in the study of meteorological time series behaviour is the long range dependence (LRD). Various estimators of LRD have been proposed. Their accuracy have been generally tested by using simulated time series since sometimes only their asymptotic property are known, or worse, no asymptotic property have been proved. It is well – known that t...

Nonlinear Time Series in Financial Forecasting