Change Point Detection from Stock Data：n Empirical Study
Date Issued
2008
Date
2008
Author(s)
Pai, Szu-Yu
Abstract
In this paper, we discuss the problems of change point detection. There are some classical methods for change point detection, such as the cumulative sum (CUSUM) procedure. However, when utilizing CUSUM, we must be sure about the model of the data before detecting.e here introduce a new method to detect the change points by using Hilbert-Huang Transformation (HHT) to devise a new algorithm. This new method (called the HHT test in this paper) has the advantage that no model assumptions are required. Moreover, in some cases the HHT test performs better than the CUSUM test, and has better simulation results. In the end, an empirical study of the volatility change based on S&P 500 is also given for illustration.
Subjects
Arbitrage detection
change point detection
Hilbert-Huang transformation
volatility
stock prices
Type
thesis
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