英文标题：
《The limits of statistical significance of Hawkes processes fitted to
  financial data》
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作者：
Mehdi Lallouache, Damien Challet
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最新提交年份：
2015
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英文摘要：
  Many fits of Hawkes processes to financial data look rather good but most of them are not statistically significant. This raises the question of what part of market dynamics this model is able to account for exactly. We document the accuracy of such processes as one varies the time interval of calibration and compare the performance of various types of kernels made up of sums of exponentials. Because of their around-the-clock opening times, FX markets are ideally suited to our aim as they allow us to avoid the complications of the long daily overnight closures of equity markets. One can achieve statistical significance according to three simultaneous tests provided that one uses kernels with two exponentials for fitting an hour at a time, and two or three exponentials for full days, while longer periods could not be fitted within statistical satisfaction because of the non-stationarity of the endogenous process. Fitted timescales are relatively short and endogeneity factor is high but sub-critical at about 0.8.
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中文摘要：
许多霍克斯过程对金融数据的拟合看起来相当不错，但大多数都没有统计学意义。这就提出了一个问题，即这个模型能够准确解释市场动态的哪一部分。我们记录了这类过程的准确性，比如改变校准的时间间隔，并比较由指数和组成的各种类型的核的性能。由于外汇市场的开放时间是24小时不间断的，因此外汇市场非常适合我们的目标，因为外汇市场允许我们避免股票市场每天隔夜长时间关闭带来的复杂性。根据三个同时进行的测试，可以获得统计显著性，前提是一次使用两个指数的核拟合一个小时，使用两个或三个指数拟合一整天，而由于内生过程的非平稳性，较长的周期无法在统计满意度范围内拟合。拟合的时间尺度相对较短，内生性系数较高，但在0.8左右为次临界值。
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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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