A "HURST COEFFICIENT" ESTIMATION WITH WAVELETS: APPLICATION TO THE ENERGY SECTOR
Keywords:Energy Futures, Hurst exponent, Wavelet models, Efficient market theory.
The energy financial products prices could be affected by herding behavior, speculation and also by supply and demand of the physical assets. This situation is likely to generate economic cycles and a rejection of the efficiency market hypothesis. Then, the aim of this paper is to check the presence of memory in the energy Futures prices. We calculate a useful parameter the "Hurst coefficient", by using a specific tool coming from the signal theory, the wavelet decomposition. Our findings with rolling regressions are that most markets, since the beginning of 90ties, are in a process of maturity and show less and less memory of any type (short or long). Electricity displays long memory, whereas the crude oil markets present some short memory.
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