Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets

Abstract

We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the directions of future price changes. We used 60 market indexes of various countries. We empirically discovered that the relationship between the degree of efficiency (the Hurst exponent) and the predictability (the hit rate) is strongly positive. That is, a market index with a higher Hurst exponent tends to have a higher hit rate. These results suggested that the Hurst exponent is useful for predicting future price changes. Furthermore, we also discovered that the Hurst exponent and the hit rate are useful as standards that can distinguish emerging capital markets from mature capital markets.

11 pages

References in corpus (4)

• Multifractal detrended fluctuation analysis of nonstationary time series
• High-Voltage Terminal Test of Test Stand for 1-MV Electrostatic Accelerator
• Enhancement of Real Time EPICS IOC PV Management for Data Archiving System
• Volatility return intervals analysis of the Japanese market

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