Transcription of Introduction to ARCH & GARCH models
{{id}} {{{paragraph}}}
Example: stock market
Introduction to ARCH & GARCH models
University of IllinoisDepartment of EconomicsEcon 472 Fall 2001 Optional TA HandoutTA Roberto PerrelliIntroduction to ARCH & GARCH modelsRecent developments in financial econometrics suggest the use of nonlineartime series structures to model the attitude of investors toward risk and ex-pected return. For example, Bera and Higgins (1993, ) remarked that a major contribution of the ARCH literature is the finding that apparentchanges in the volatility of economic time series may be predictable andresult from a specific type of nonlinear dependence rather than exogenousstructural changes in variables. Campbell, Lo, and MacKinlay (1997, ) argued that it is both logi-cally inconsistent and statistically inefficient to use volatility measures thatare based on the assumption of constant volatility over some period whenthe resulting series moves through time. In the case of financial data, forexample, large and small errors tend to occur in clusters, , large returnsare followed by more large returns, and small returns by more small suggests that returns are serially dealing with nonlinearities, Campbell, Lo, and MacKinlay (1997)make the distinction between: Linear Time Series: shocks are assumed to be uncorrelated but notnecessarily identically independent distributed (iid).
this inappropriate use of a calendar time scale may lead to volatility clustering since relative to the calendar time, the variable may evolve more quickly or slowly” (Bera and Higgins, 1990, p. 329; Diebold, 1986]. Estimating and Testing ARCH Models Johnston and DiNardo (1997) suggest a very simple test for the presence of ARCH problems.
Loading..
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: