An Alternative Asymmetric GARCH Model with an Application to Falling and Rising Stock Prices

Ever since the groundbreaking contribution of Engle [1], the ARCH (autoregression-conditional-heteroscedasticity) model has functioned as an essential instrument for assessing a time-based measure of financial risk. Various expansions of this approach have taken place in literature. The current work offers a complementary method for tackling potential asymmetric issues in risk models. Distinct from previous approaches to asymmetry, the current work proposes explicitly separating the negative price shocks from the positive ones when modeling time-dependent risk. A test method is recommended that can be used for testing the null hypothesis of no asymmetry in the risk measure. If the hypothesis of interest is not empirically supported, then the model might be estimated by using the maximum likelihood procedure. The proposed asymmetric risk approach is utilized for modeling the time-dependent risk for rising or falling stock prices in the world marketplace. The results have important implications for both sellers and buyers of stocks in terms of financial risk management.