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Predicting New Energy Prices: Are Technical Indicators and Regime-Switching Models Helpful?
Zhufeng Wang1, Lu Wang1, Zitao Zhang2
1Department of Statistics, School of Mathematics, Southwest Jiao Tong University, Chengdu, China.
Abstract:
This study introduces a novel aligned technical index, derived from multiple technical indicators, that encompasses a broader spectrum of technical measurement strategies than those obtained from previous 3PRF (Three-Pass Regression Filter) research. Our empirical results demonstrate that this index exhibits significant predictive power for new energy price returns in both in-sample and out-of-sample tests. This index is extracted using the 3PRF method and yields significantly better results than those obtained with traditional methods. Considering that the market typically operates in two states, we incorporate a regime-switching model with time-varying transition probabilities into our forecasting framework. The findings indicate that the technical index influences the probability of regime transitions between states and that the inclusion of a regime-switching model further enhances predictive performance. The incorporation of the regime-switching mechanism further improves the predictive performance of the model. Moreover, from an asset allocation perspective, both the technical index and regime-switching models deliver considerable economic value to mean-variance investors.
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