The Hurst Exponent and DFA results provide insights into long-range dependency within time series data. A deviation from 0.5 in these metrics indicates persistence or anti-persistence in temporal patterns beyond short-term fluctuations. In this study's context of electricity price forecasting and ACE prediction for market operations, a slight deviation from 0.5 suggests minimal long-term effects or trends in real-time market signals.
For forecasting strategies, understanding these metrics can help determine whether historical patterns will persist or revert over time intervals relevant to decision-making processes. In scenarios where there is low long-range dependency (Hurst exponent close to 0.5), simpler forecasting models may suffice due to limited predictability beyond short-term fluctuations.