An investigation of higher order moments of empirical financial data and their implications to risk.
An investigation of higher order moments of empirical financial data and their implications to risk.
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DOI：
10.1016/j.heliyon.2022.e08833
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发表时间：
2022-03
期刊：
影响因子：
4
通讯作者：
Savel'ev S
中科院分区：
文献类型：
--
作者：
De Clerk L;Savel'ev S
在这里，我们分析了当我们将一个大型数据集截断为越来越小的子集时，金融时间序列的高阶标准化矩的行为，以下称为时间窗口。我们考察了经济环境对这些时间窗口中高阶矩行为的影响。当数据子集的长度减小时，我们观察到两种不同的高阶矩的标度关系：一种是较长时间窗，另一种是较短时间窗。当时间窗口包含金融危机时，这些比例关系就会发生巨大变化。我们还观察到，与高斯值相比，随着时间窗口的缩小，高阶归一化矩发生了质的变化。此外，我们通过分析稀有事件在高阶矩上的层次来模拟观测到的标度律。我们扩展了对标度关系的分析，以包含这些标度关系对风险的影响。我们对这些时间窗口内的收益序列进行分解，并进行风险价值计算。在此过程中，我们通过风险价值水平的变化来观察标度关系的表现。经验数据；标度关系；高阶归一化矩；风险值；高斯混合
Here, we analyse the behaviour of the higher order standardised moments of financial time series when we truncate a large data set into smaller and smaller subsets, referred to below as time windows. We look at the effect of the economic environment on the behaviour of higher order moments in these time windows. We observe two different scaling relations of higher order moments when the data sub sets' length decreases; one for longer time windows and another for the shorter time windows. These scaling relations drastically change when the time window encompasses a financial crisis. We also observe a qualitative change of higher order standardised moments compared to the gaussian values in response to a shrinking time window. Moreover, we model the observed scaling laws by analysing the hierarchy of rare events on higher order moments. We extend the analysis of the scaling relations to incorporate the effects these scaling relations have upon risk. We decompose the return series within these time windows and carry out a Value-at-Risk calculation. In doing so, we observe the manifestation of the scaling relations through the change in the Value-at-Risk level. Empirical data; Scaling relations; Higher order standardised moments; Value-at-risk; Gaussian mixtures
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影响因子：
4.8
作者：
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通讯作者：
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