Monitoring correlation change in a sequence of random variables

作者：Wied Dominik^*; Galeano Pedro

来源：Journal of Statistical Planning and Inference, 2013, 143(1): 186-196.

DOI：10.1016/j.jspi.2012.06.007

• Correlation changes
• Gaussian process
• Online detection
• Threshold function

We propose a monitoring procedure to test for the constancy of the correlation coefficient of a sequence of random variables. The idea of the method is that a historical sample is available and the goal is to monitor for changes in the correlation as new data become available. We introduce a detector which is based on the first hitting time of a CUSUM-type statistic over a suitably constructed threshold function. We derive the asymptotic distribution of the detector and show that the procedure detects a change with probability approaching unity as the length of the historical period increases. The method is illustrated by Monte Carlo experiments and the analysis of a real application with the log-returns of the Standard %26 Poor%26apos;s 500 (S%26P 500) and IBM stock assets.

• 出版日期2013-1