Modeling the Impact of News on volatility The Case of Iran

Abstract

In this paper various ARCH models and relevant news impact curves including a partially nonparametric (PNP) one are compared and estimated with daily Iran stock return data. Diagnostic tests imply the asymmetry of the volatility response to news. The EGARCH model, which passes all the tests and appears relatively matching with the asymmetry in the data, seems to be the most adequate characterization of the underlying data generating process. The PNP model successfully reveals the shape of the news impact curve and is a useful approach to modeling conditional heteroskedasticity.