The impact of stationarity assessment on studies of volatility and value-at-risk

Recent research on volatility of asset returns demonstrates that model innovations frequently show unconditional heteroscedasticity. On the other hand, ARMA-GARCH models incorporate the heteroscedasticity only in the conditional distribution of the innovations, assuming the unconditional distributions to be stationary (see, e.g., [1,2]). Given the observed unconditional heteroscedasticity of the return innovations [3], there is a need to overcome this shortcoming of existing models. rpose of this paper is to introduce a test of stationarity of the innovations and show its impact in the analysis of volatility and value at risk. The methodological results are accompanied with examples and simulations.