Modelling volatilities of financial time series using the GARCH (1, 1) model - Zhou, Ze (2013)
The autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model proposed by Bollseslev (1986) are such models that could model time varying volatility. Literally, ARCH/GARCH model take autocorrelation and heteroscedasticity into account when measuring volatility. The aim in this dissertation is to estimate the volatilities of real financial data using GARCH (1, 1) model.