Fourier transform based investment styles on the Johannesburg Stock Exchange

Abstract

Share price periodicity and calendar effects have been well documented for stock exchanges. If these market anomalies are persistent and of sufficiently high amplitudes, the use of frequency analysis will allow investors to earn abnormal returns. This research study examined the use of the discrete Fourier transform combined with prior exponential growth and momentum periodicity as an investment style. A graphical time series approach was used to evaluate performance of the examined styles. The time series consisted of the JSE top 160 shares from December 1985 to October 2013. A momentum-Fourier transform investment style is identified that outperforms most if not all documented univariate ranked investment styles on the JSE for the analysed timeframe. Returns of 27.6% per annum are achieved. It is found that both examined momentum styles are enhanced by using the Fourier transform as a noise filter. Combining prior exponential growth rate and the Fourier transform failed to produce favourable results.