  We empirically analyze the most volatile component of the electricity price
time series from two North-American wholesale electricity markets. We show that
these time series exhibit fluctuations which are not described by a Brownian
Motion, as they show multi-scaling, high Hurst exponents and sharp price
movements. We use the generalized Hurst exponent (GHE, $H(q)$) to show that
although these time-series have strong cyclical components, the fluctuations
exhibit persistent behaviour, i.e., $H(q)>0.5$. We investigate the
effectiveness of the GHE as a predictive tool in a simple linear forecasting
model, and study the forecast error as a function of $H(q)$, with $q=1$ and
$q=2$. Our results suggest that the GHE can be used as prediction tool for
these time series when the Hurst exponent is dynamically evaluated on rolling
time windows of size $\approx 50 - 100$ hours. These results are also compared
to the case in which the cyclical components have been subtracted from the time
series, showing the importance of cyclicality in the prediction power of the
Hurst exponent.
