DAMGARCH extends the VARMA-GARCH model of Ling and McAleer (2003) by introducing multiple thresholds and time-dependent structure in the asymmetry of the conditional variances. DAMGARCH models the shocks affecting the conditional variances on the basis of an underlying multivariate distribution....

In the common nonparametric regression model the problem of testing for a specific parametric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a...

This paper attempts to determine the relationship between conditional stock market volatility and macroeconomic volatility using monthly data for Turkey from 1986 to 2003. The macroeconomic variables used include industrial production, the money supply M1, inflation, an exchange rate variable,...

This paper investigates whether the risk-free rate may explain the movements observed in the conditional second moments of asset returns. Original results are derived, within the C-CAPM framework, that attest the existence of a channel connecting these seemingly unrelated quantities. The...

We conduct an empirical study of risk–return trade-off in fourteen Pacific basin equity markets using several volatility estimators, including five variants of GARCH class, equally weighted rolling window volatility, and mixed data sampling (MIDAS), as well as binormal GARCH (BiN-GARCH) model...