A Synthesis of Technical Analysis and Fractal Geometry - Evidence from the Dow Jones Industrial Average Components

The profitability of technical analysis has been investigated extensively, with inconsistent results. This paper seeks to develop new insights into the profitability of technical trading rules through a synthesis of fractal geometry and technical analysis. The Hurst exponent (H) emerged from fractal geometry as a means to detect long-term dependencies in a time series; the same dependencies that technical analysis should be able to identify and exploit to earn profits. Two tests of the synthesis are conducted using the thirty Dow Jones Industrial Average components. Firstly, the financial series are classified into three groups based on their H to determine if a higher (lower) H results in higher returns to trending (contrarian) trading rules. Secondly, the relationship between H and profits to technical analysis are estimated through OLS regression. Both tests suggest that the fractal nature of a time series explains a significant portion of the profits generated by technical analysis