摘要翻译:
从毫秒到数年的波动率、交易量和交易时间的极值时间内的幂律的观察表明,在其他无特征的过程中,如随机游动中,选择有偏的实现统计子集直接导致了幂律的观察。这种偏差源于对价格峰值的选择,这对价格变化和贸易量的统计数据施加了一个条件,使其分布扭曲。在互通有无的时代,极值和幂律是交易数据格式的结果。
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英文标题:
《Spurious trend switching phenomena in financial markets》
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作者:
Vladimir Filimonov, Didier Sornette
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最新提交年份:
2011
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分类信息:
一级分类:Quantitative Finance 数量金融学
二级分类:Statistical Finance 统计金融
分类描述:Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类:Quantitative Finance 数量金融学
二级分类:General Finance 一般财务
分类描述:Development of general quantitative methodologies with applications in finance
通用定量方法的发展及其在金融中的应用
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英文摘要:
The observation of power laws in the time to extrema of volatility, volume and intertrade times, from milliseconds to years, are shown to result straightforwardly from the selection of biased statistical subsets of realizations in otherwise featureless processes such as random walks. The bias stems from the selection of price peaks that imposes a condition on the statistics of price change and of trade volumes that skew their distributions. For the intertrade times, the extrema and power laws results from the format of transaction data.
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PDF链接:
https://arxiv.org/pdf/1112.3868