因此,传统线性结构模 型(以及时间序列模型)并不能很好地解释金融数据的重要特征, 这包括: 尖峰厚尾(Leptokurtosis):金融资产收益呈现厚尾(fat tails) 和在均值处呈现过度波峰,即出现过度峰度分布的倾向; 波动丛聚性(clustering):金融市场...
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...ering)特征,即方差在一定时段中比较小,而在另一时段中比较大。从取值的分布看表现的则是尖峰厚尾(leptokurtosis and fat-tail)特征,即均值附近与尾区的概率值比正态分布大,而其余区域的概率比正态分布小。
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In the simulation resluts, we analyse the relationship about herd behavior with“leptokurtosis and heavy tails”,“cluster”, the market stability,“leverage effect”, market foam. ,and so on.
对模拟结果分别从羊群行为与“尖峰厚尾”、“丛集性”、市场稳定性、“杠杆效应”和市场泡沫的关系等角度进行了详细的分析。
参考来源 - 投资者羊群行为的微观机理与元胞自动机模拟·2,447,543篇论文数据,部分数据来源于NoteExpress
对期货价格数据进行统计分析,发现期货价格具有“尖峰厚尾”特性。
Secondly, carrying on the statistical analysis to the forward price data, discovered the future price data has the intense ARCH effect.
人民币汇率收益率波动有集群性效应,不符合正态分布,有尖峰厚尾的特点。
The return of RMB exchange rate has a characteristic of fluctuation clustering, does not comply with the normal distribution and has an obvious peak and fat tails.
根据实证检验得出我国股票市场非正态性和尖峰厚尾的特点,选择价差损失值这一度量指标。
According to empirical test, China's stock market shows the characteristics of non-normality and fat tail as well as makes the loss value of the price difference loss as metrics.
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