TITLE:
Intraday Periodicity and Long Memory Volatility in Hong Kong Stock Market
AUTHORS:
Wei Dai, Dejun Xie, Bianxia Sun
KEYWORDS:
Volatility, High Frequency Data, Periodicity, Long Memory
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.3 No.7,
July
14,
2015
ABSTRACT: This paper characterizes the volatility in
Hong Kong Stock Market based on a 2-year sample of 5-min Heng Seng Index. By
using the method of Flexible Fourier Form Filtering, we have successful removed
the periodicity and have built a model of ARMA (1,1)-FIAPARCH (2, 0.300165,1).
Further, the intraday volatility exists with long memory and asymmetry; the
negative shock from the market will give rise to a higher volatility than the
positive ones.