Finance Research Seminar: “Modelling Volatility Cycles: The (MF)^2 Garch Model’’ by Dr. Christian CONRAD – Heidelberg University
Speaker: Dr. Christian CONRAD
Date and Location – Thursday January 21st 2021 from 12:30 to 14:00 on Zoom
We suggest a multiplicative factor multi frequency ((MF)^2) component GARCH model. The model consists of a short-term and a long-term volatility component. The long-term component is based on a MEM equation for the average standardized forecast errors of the GARCH component and captures the counter-cyclical behaviour of financial volatility. We derive the unconditional variance of the returns in the (MF)^2 GARCH and discuss the news impact function. Since the new model is dynamically complete, it is straightforward to construct multi-step ahead volatility forecasts. We apply the model to the S&P 500, the FTSE 100 and the Hang Seng Index. We show that the long-term component of the S&P 500 behaves counter-cyclical and is driven by news about the macroeconomic outlook, corporate earnings and policy. The (MF)^2 GARCH significantly outperforms the nested one-component (GJR) GARCH as well as several HAR-type models in terms of out-of-sample forecasting.
A joint work with Robert Engle (Nobel Laureate, 2003)