News or Noise? Signal Extraction Can Generate Volatility Clusters From IID Shocks

Prasad V. Bidarkota () and J. Huston McCulloch
Additional contact information
J. Huston McCulloch: Department of Economics, Ohio State University

No 304, Working Papers from Florida International University, Department of Economics

Abstract: We develop a framework in which information about firm value is noisily observed. Investors are then faced with a signal extraction problem. Solving this would enable them to probabilistically infer the fundamental value of the firm and, hence, price its stocks. If the innovations driving the fundamental value of the firm and the noise that obscures this fundamental value in observed data come from non-Gaussian thick-tailed probability distributions, then the implied stock returns could exhibit volatility clustering. We demonstrate the validity of this effect with a simulation study.

Keywords: stock returns; volatility clusters; GARCH processes; signal extraction; thick-tailed distributions; simulations (search for similar items in EconPapers)
JEL-codes: C22 E31 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cfn, nep-ets, nep-fmk, nep-mac and nep-rmg
Date: 2003-11
View list of references

Downloads: (external link)
http://www.fiu.edu/orgs/economics/wp2003/03-04.pdf First version, 2003 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:fiu:wpaper:0304

Access Statistics for this paper

More papers in Working Papers from Florida International University, Department of Economics
Contact information at EDIRC.
Series data maintained by Peter Thompson ().