C13 - Estimation: GeneralReturn

In this paper we analyse a temporal evolution of the Hurst exponent estimated on hourly returns of intraday electricity prices in the Czech Republic in 2017 and 2018. Firstly we used the log-returns with adjustments due to negative values, and secondly we employed the returns based on the area hyperbolic sine transformation. We implemented a sliding window technique in order to estimate the Hurst exponent using the Detrended Fluctuation Analysis method on subsamples with four distinct window sizes. According to the stylised facts of electricity, the spot prices and their corresponding logarithmic returns should be mean-reverting. Since the Czech intraday electricity market remains mostly unexplored, we examined this phenomenon on the intraday rather than on the spot market. Consequently, our analysis showed that the estimated values of Hurst exponent indicate a mean-reverting process for time scales greater than 24 hours and a weakly mean-reverting process for the shorter time scales. There were a few exceptions, though, since our calculations have revealed the presence of a nearly random or even weakly persistent behaviour on the shorter time scales.

The estimation of multiple structural break models is usually associated with identification of spurious break points, which are identified by universal algorithms. This leads to overvaluation of structural distress in financial markets represented by data series. The paper is focused on an estimation of the new index, which incorporates results of Student, Bartlett, GLR, Mann-Whitney, Mood, Lepage, Kolmogorov-Smirnov and finally Cramer-von-Mises tests statistics together. The new measure is named Structural Distress Index and evaluates a probability of structural break occurrence based on estimations of proposed models. SDI values show that Czech and Polish stock markets went through more instable period in 1990s than at the beginning of the global financial crisis in 2007. SDI measure is straightforward and can be easily explained, the highest values of SDI can identify the most important break points of the research period, which starts in year 1993 and ends in year 2014. Universality of SDI offers its further extension and application to further research of financial markets.