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The Price and Trading Volume Dynamics Relationship in the EEX Power Market: A Wavelet Modeling

机译:EEX电力市场中的价格和交易量动力学关系:小波建模

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This paper examines the dynamic relationship between power spot prices and related trading volumes in one of the most emergent energy markets. Traditionally, investigating the bivariate stochastic processes has been dominated by linear econo-metrical methods that proved helpful especially in finance. However, when dealing with intradaily power data, we cannot rely on models developed for financial or other commodity markets. Therefore, wavelet transforms are applied for power markets data to search for and decode nonlinear regularities and hidden patterns existing between the variables. Given its ability to decompose the time series into their time scale components and thus to reveal structure at different time horizons, wavelets are useful in analyzing situations in which the degree of association between processes is likely to change with the time-horizon. Therefore, a wavelet-based cross-analysis is performed between prices and trading volume time series. On the same basis, causality tests and out-of-sample forecasting tasks are carried out to empirically the strong relationship between the two investigated time series.
机译:本文研究了在最新兴的能源市场之一中,电力现货价格与相关交易量之间的动态关系。传统上,调查双变量随机过程的方法主要是线性经济计量方法,事实证明该方法特别有用。但是,在处理日内电力数据时,我们不能依赖为金融或其他商品市场开发的模型。因此,将小波变换应用于电力市场数据,以搜索和解码变量之间存在的非线性规律和隐藏模式。鉴于小波具有将时间序列分解为其时间标度分量并揭示不同时间范围结构的能力,因此小波可用于分析过程之间的关联程度可能随时间水平而变化的情况。因此,在价格和交易量时间序列之间执行基于小波的交叉分析。在相同的基础上,进行因果关系检验和样本外预测任务,以经验为依据研究两个时间序列之间的紧密关系。

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