A Comparative GARCH Analysis of Macroeconomic Variables and Returns on modelling the kurtosis of FTSE 100 Implied Volatility Index

Modelling the volatility (or kurtosis) of the implied volatility is an important aspect of financial markets when analysing market consensus and risk strategies. The purpose of this study is to evaluate the ability of symmetric and asymmetric GARCH systems to model the volatility of the FTSE 100 Implied Volatility Index (IV). We use GARCH, EGARCH, GJR-GARCH and GARCH-MIDAS to model variance. We also introduce FTSE 100 returns and several macroeconomic variables (UK industrial production, 3M LIBOR, GBP effective exchange rate and unemployment rate) to investigate whether they explain variance. Our results show that market returns is a major explanatory factor besides macroeconomic variables. Also, GARCH (1,1) outperforms other asymmetric models unless there is exceptionally high volatility such as the crisis of 2008 in which case EGARCH performs better. GJR-GARCH is outperformed by all other models. GARCH-MIDAS shows that both macroeconomic variables and market returns are useful when estimating IV.