DocumentCode :
2669171
Title :
Applications of Ensemble Empirical mode decomposition to stock-futures basis analysis
Author :
Sun, Jingliang ; Sheng, Huanye
Author_Institution :
Dept. of Comput. Sci. & Technol., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2010
fDate :
17-19 Sept. 2010
Firstpage :
396
Lastpage :
399
Abstract :
In rational, efficiently functioning markets, the returns on stock index and stock index futures contracts should be perfectly, contemporaneously correlated. But in the first two month, Chinese stock index futures contracts exhibited persistent departures from fair price, offering potentially profitable arbitrage opportunities. In this paper, we examine the stock-futures basis of CSI 300 recorded every 5 min over the period from April 16, 2010 to June 10, 2010 (1872 total data points). Ensemble Empirical mode decomposition (EEMD) is a time-frequency analysis method which has been developed and widely used for non-stationary and non-linear time series analysis. In the present study, we apply the EEMD to analyze the stock-futures basis series. As a result, we extract a monotonic decreasing trends from the series which implies the market becomes more and more efficient.
Keywords :
stock markets; time series; time-frequency analysis; CSI 300; Chinese stock index futures contracts; ensemble empirical mode decomposition; fair price; monotonic decreasing trend; nonlinear time series analysis; nonstationary time series analysis; potentially profitable arbitrage opportunities; stock-futures basis series; time-frequency analysis method; Band pass filters; Contracts; Indexes; Time frequency analysis; Time series analysis; Transforms; White noise; ensemble empirical mode decomposition; financial time series; non-stationary; stock index futures;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Financial Engineering (ICIFE), 2010 2nd IEEE International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-6927-7
Type :
conf
DOI :
10.1109/ICIFE.2010.5609386
Filename :
5609386
Link To Document :
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