Non-stationary GARCH modelling for fitting higher order moments of financial series within moving time windows
移动时间窗口内拟合金融序列高阶矩的非平稳 GARCH 模型
Here, we have analysed a GARCH(1,1) model with the aim to fit higher order moments for different companies' stock prices. When we assume a gaussian conditional distribution, we fail to capture any empirical data when fitting the first three even moments of financial time series. We show instead that a double gaussian conditional probability distribution better captures the higher order moments of the data. To demonstrate this point, we construct regions (phase diagrams), in…