Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets
Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets
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DOI：
10.1002/fut.21759
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发表时间：
2015-08
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影响因子：
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通讯作者：
Marcel Prokopczuk;L. Symeonidis;Chardin Wese Simen
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文献类型：
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作者：
Marcel Prokopczuk;L. Symeonidis;Chardin Wese Simen
本文描述了跳跃的动态特征并分析了它们对于波动率预测的重要性。使用四个主要能源市场的高频数据，我们将实现的方差进行无模型分解为其连续和不连续分量。我们发现了 2007 年至 2012 年间能源市场跳跃的有力证据。然后我们研究了跳跃对于波动性预测的重要性。为此，我们估计并分析了几个明确捕获跳跃动态的异质自回归（HAR）模型的预测能力。通过进行广泛的样本内和样本外分析，我们发现显式建模跳跃并不能显着提高预测准确性。我们的结果在四个能源市场、预测范围和损失函数方面基本一致。 © 2015 Wiley periodicals, Inc. Jrl Fut Mark 36:758–792, 2016
This paper characterizes the dynamics of jumps and analyzes their importance for volatility forecasting. Using high‐frequency data on four prominent energy markets, we perform a model‐free decomposition of realized variance into its continuous and discontinuous components. We find strong evidence of jumps in energy markets between 2007 and 2012. We then investigate the importance of jumps for volatility forecasting. To this end, we estimate and analyze the predictive ability of several Heterogenous Autoregressive (HAR) models that explicitly capture the dynamics of jumps. Conducting extensive in‐sample and out‐of‐sample analyses, we establish that explicitly modeling jumps does not significantly improve forecast accuracy. Our results are broadly consistent across our four energy markets, forecasting horizons, and loss functions. © 2015 Wiley Periodicals, Inc. Jrl Fut Mark 36:758–792, 2016