Open AccessVolatility Clustering at a Sector Level in the Chinese Equity Market
Author(s) -
Gerardo “Gerry” Alfonso Perez
Publication year - 2018
Publication title -
international journal of financial research
Language(s) - English
Resource type - Journals
eISSN - 1923-4031
pISSN - 1923-4023
DOI - 10.5430/ijfr.v9n3p103
Subject(s) - volatility (finance) , cluster analysis , econometrics , economics , volatility swap , equity (law) , portfolio , volatility clustering , volatility risk premium , financial economics , implied volatility , statistics , autoregressive conditional heteroskedasticity , mathematics , political science , law
The issue of volatility clustering i.e., if periods of high volatility on stocks returns are typically followed by other periods of high volatility and vice versa, is analysed in this article at a sector level for the Chinese stock market. This analysis was performed with daily returns for the period from 2008 to 2017. When the entire dataset is analysed the statistical tests are rather consistent indicating that there is volatility clustering for all the major nine sectors (basic materials, communications, consumer cyclical, consumer non-cyclical, energy financial, industrial, technology and utilities). However, when each year is analysed independently the results are much more mixed with some sectors, such as technology companies, that could a priori look as a prime candidate for volatility clustering having less years with such feature present that other sectors such as for instance basic materials. The issue of volatility clustering at a sector level is of clear interest and can be used as another tool to optimize portfolio allocations. It is interesting to see that volatility clustering seems to be present when the statistical tests are performed over long periods of time but less so when the timeframe is shortened.