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Volatility Modelling In Crude Oil and Natural Gas Prices

机译:原油和天然气价格的波动型建模

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This study analysis the return volatility of spot market prices of crude oil (WTI) and natural gas (Henry Hub) for two different terms which cover 02.01.2009-28.04.2014 and 04.01.2010-28.04.2014 with different version of the GARCH class models such as GARCH, IGARCH, GJRGARCH, EGARCH, FIGARCH, FIAPARCH. In particular, the main idea of employing various GARCH models is to determine which one of these linear and nonlinear asymmetric models perform more accurate in terms of ingroups and intergroups activities. Therefore, the main purpose of the paper is to determine a model which ensures to get a maximum return with response to the minimum loss for returns of the investments held by individual investors and fund managers, private sector budget planning decision makers, and state agencies forecasting about macroeconomic indicators. To do this, the ten-days out-of-sample volatility forecasts of Loss Functions to capture the forecasting performance of GARCH class models and to prevent forecasting errors with efficiency hedge ratio in energy market are being considered. For two periods, asymmetric and integrated GARCH models give relatively more accurate performance than other available models. Respectively, for the first period, minimum loss model is FIGARCH-BBM (SST) and for the second period, is EGARCH(GED) for WTI crude oil series in consideration of MSE and MAE criterion. Similarly, for the first period minimum loss model is FIGARCH-BBM (SST) and for the second period, is EGARCH(GED) for Henry Hub natural gas series in consideration of MSE and MAE criterion. This study has potential recommendations for investors from developed and developing countries, which differs it from the current studies.
机译:这项研究分析的原油(WTI)和天然气(亨利集线器)的现货市场价格覆盖02.01.2009-28.04.2014和04.01.2010-28.04.2014与不同版本的GARCH的两个不同方面的收益波动类模型,如GARCH,IGARCH,GJRGARCH,EGARCH,FIGARCH,FIAPARCH。特别是,采用各种GARCH模型的主要思想是,以确定这些线性和非线性非对称模型之一中内群体和intergroups活动方面执行更准确的。因此,本文的主要目的是确定保证得到与对由个人投资者和基金经理,私营部门预算规划决策者和国家机构的预测持有的投资的回报率最小损失最大的回报模型关于宏观经济指标。要做到这一点,损失函数的十几天出的样本外预测的波动捕捉GARCH类模型的预测效果,并防止在能源市场的效率套期保值比率的预测错误,正在考虑。对于两个时段,非对称和集成的GARCH模型给出比其他可用的模型相对更准确的性能。分别为第一周期,最小损耗模型是FIGARCH-BBM(SST)和在第二周期,是EGARCH(GED),用于WTI原油系列考虑MSE和MAE准则。类似地,对于第一时间段最小损耗模型是FIGARCH-BBM(SST)和在第二周期,是EGARCH(GED),用于在考虑MSE和MAE准则的亨利集线器天然气系列。这项研究有来自发达国家和发展中国家,它不同于从目前的研究对投资者的可能建议。

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