资产价格平均退出时间的标度和数据崩溃
Scaling and data collapse for the mean exit time of asset prices
摘要：
我们研究金融时间序列的平均退出时间的理论和实证方面。理论建模是在连续时间随机游走的框架内进行的。我们的经验验证，平均退出时间遵循二次标度律，它与一个前因子，这是特定的分析股票。我们进行了一系列的统计测试，以确定哪种相关性负责这种特异性。主要贡献与股票收益率的自相关性有关。我们介绍和解决解析两个状态和三状态马尔可夫链模型。用两状态马尔可夫链模型获得的分析结果使我们能够在单个主曲线中获得20个实测MET曲线的数据崩溃。
英文摘要：
We study theoretical and empirical aspects of the mean exit time of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a pre-factor which is specific to the analyzed stock. We perform a series of statistical tests to determine which kind of correlation are responsible for this specificity. The main contribution is associated with the autocorrelation property of stock returns. We introduce and solve analytically both a two-state and a three-state Markov chain models. The analytical results obtained with the two-state Markov chain model allows us to obtain a data collapse of the 20 measured MET profiles in a single master curve.
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