Modelling the Assymetry of Stock Market Volatility
Recent studies suggest that a negative shock to stock prices will generate more volatility than a positive shock of equal magnitude. This paper uses daily data from the Hong Kong Stock Exchange to illustrate the nature of stock market volatility. Regression-based tests for integration in variance are applied, providing contrasting results to the usual test based on the Wald statistic. A partially non-parametric model of the relationship between news and volatility is estimated and used in conjunction with tests for the sensitivity to both the size and sign of a shock as a metric to judge various candidate characterizations of the underlying data generating process.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
|Date of creation:||1995|
|Contact details of provider:|| Postal: Department of Economics, The University of Melbourne, 4th Floor, FBE Building, Level 4, 111 Barry Street. Victoria, 3010, Australia|
Phone: +61 3 8344 5355
Fax: +61 3 8344 6899
Web page: http://fbe.unimelb.edu.au/economics
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:mlb:wpaper:487. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Katherine Perez)
If references are entirely missing, you can add them using this form.