论文标题
IID时间序列测试
IID Time Series Testing
论文作者
论文摘要
传统的白噪声测试，例如Ljung-box测试，仅研究自相关函数（ACF）。时间序列可以是异种的，因此不是I.I.D。但是仍然是白噪声（即零ACF）。异质性的一个例子是财务时间序列：高方差（金融危机）的时代可以与差异较低（平静时代）交替。在这里，时间序列项的绝对值不是白噪声。我们可以分别测试白噪声的原始值和绝对值，例如使用两者使用ljung-box测试。在本文中，我们创建了一个结合这两个测试的综合测试。此外，我们创建一个一般框架来创建各种I.I.D.测试。我们将测试应用于模拟数据，包括自回旋线性和异方差。
Traditional white noise testing, for example the Ljung-Box test, studies only the autocorrelation function (ACF). Time series can be heteroscedastic and therefore not i.i.d. but still white noise (that is, with zero ACF). An example of heteroscedasticity is financial time series: times of high variance (financial crises) can alternate with times of low variance (calm times). Here, absolute values of time series terms are not white noise. We could test for white noise separately for original and absolute values, for example using Ljung-Box tests for both. In this article, we create an omnibus test which combines these two tests. Moreover, we create a general framework to create various i.i.d. tests. We apply tests to simulated data, both autoregressive linear and heteroscedastic.
