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Multivariate EMD-based Portfolio Value at Risk Estimate for Electricity Markets

机译:电力市场风险评估中基于多元EMD的投资组合价值

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With the electricity market reform in recent years, the electricity price is seeing higher level of volatility and risk. Based on the Multivaraite EMD algorithm, this paper proposes a novel risk measurement approach for studying the risk trends and estimating Value at Risk (VaR) in the electricity market. The Multivariate EMD algorithm is introduced to analyze the multi-scale and the volatility behaviors of the correlation among different electricity markets. The heterogeneous data is decomposed in the proposed Multivariate EMD based VaR estimation algorithm. The decomposed time series will be calculate with the DCC-GARCH model. Empirical studies in the representative Australian electricity markets suggest that the proposed algorithm outperforms the benchmark Exponential Weighted Moving Average (EWMA) and DCC-GARCH model, in terms of conventional performance evaluation criteria for the model reliability.
机译:近年来,随着电力市场的改革,电价的波动性和风险性越来越高。基于Multivaraite EMD算法,本文提出了一种新颖的风险度量方法,用于研究电力市场中的风险趋势和评估风险价值(VaR)。引入多元EMD算法来分析不同电力市场之间相关性的多尺度和波动行为。在提出的基于多元EMD的VaR估计算法中分解了异构数据。分解后的时间序列将使用DCC-GARCH模型进行计算。在澳大利亚代表性电力市场的经验研究表明,就模型可靠性的常规性能评估标准而言,该算法优于基准指数加权移动平均线(EWMA)和DCC-GARCH模型。

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