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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Modeling natural gas market volatility using GARCH with different distributions
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Modeling natural gas market volatility using GARCH with different distributions

机译：使用具有不同分布的GARCH对天然气市场波动进行建模

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摘要

In this paper, we model natural gas market volatility using GARCH-class models with long memory and fat-tail distributions. First, we forecast price volatilities of spot and futures prices. Our evidence shows that none of the models can consistently outperform others across different criteria of loss functions. We can obtain greater forecasting accuracy by taking the stylized fact of fat-tail distributions into account. Second, we forecast volatility of basis defined as the price differential between spot and futures. Our evidence shows that nonlinear GARCH-class models with asymmetric effects have the greatest forecasting accuracy. Finally, we investigate the source of forecasting loss of models. Our findings based on a detrending moving average indicate that GARCH models cannot capture multifractality in natural gas markets. This may be the plausible explanation for the source of model forecasting losses.
机译：在本文中，我们使用具有长记忆和长尾分布的GARCH类模型对天然气市场波动进行建模。首先，我们预测现货和期货价格的价格波动。我们的证据表明，在不同的损失函数标准下，没有一个模型能够始终胜过其他模型。通过考虑胖尾分布的典型事实，我们可以获得更高的预测准确性。其次，我们预测以现货和期货之间的价格差为基础的波动性。我们的证据表明，具有非对称效应的非线性GARCH类模型具有最大的预测精度。最后，我们调查了预测模型损失的来源。我们基于下降趋势移动平均线的发现表明，GARCH模型无法捕获天然气市场中的多重分形。这可能是模型预测损失来源的合理解释。

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