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Stochastic Volatility And Garch: Do Squared End-Of-Day Returns Provide Similar Information?, David Edmund Allen
Stochastic Volatility And Garch: Do Squared End-Of-Day Returns Provide Similar Information?, David Edmund Allen
Research outputs 2014 to 2021
The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to twenty plus years of daily data for three indices. As a benchmark, I use the realized volatility (RV) for the S&P 500, DOW JONES and STOXX50 indices, sampled at 5-minute intervals, taken from the Oxford Man Realised Library. Both models demonstrate comparable performance and are correlated to a similar extent with the RV estimates, when measured by OLS. However, a crude variant of Corsi’s (2009) Heterogenous Auto-Regressive (HAR) model, applied to squared demeaned daily returns on the indices, appears to predict the daily RV of …
Do We Need Stochastic Volatility And Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns On Ftse, David E. Allen, Michael Mcaleer
Do We Need Stochastic Volatility And Generalised Autoregressive Conditional Heteroscedasticity? Comparing Squared End-Of-Day Returns On Ftse, David E. Allen, Michael Mcaleer
Research outputs 2014 to 2021
The paper examines the relative performance of Stochastic Volatility (SV) and Generalised Autoregressive Conditional Heteroscedasticity (GARCH) (1,1) models fitted to ten years of daily data for FTSE. As a benchmark, we used the realized volatility (RV) of FTSE sampled at 5 min intervals taken from the Oxford Man Realised Library. Both models demonstrated comparable performance and were correlated to a similar extent with RV estimates when measured by ordinary least squares (OLS). However, a crude variant of Corsi’s (2009) Heterogeneous Autoregressive (HAR) model, applied to squared demeaned daily returns on FTSE, appeared to predict the daily RV of FTSE better …