A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns. / Alsheikhmubarak, Abdulilah; Giouvris, Evangelos.

43rd International Business Research Conference, Proceedings of : 13 - 15 July 2017, Ryerson University, Toronto, Canada. 2017.

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A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns. / Alsheikhmubarak, Abdulilah; Giouvris, Evangelos.

43rd International Business Research Conference, Proceedings of : 13 - 15 July 2017, Ryerson University, Toronto, Canada. 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Alsheikhmubarak A, Giouvris E. A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns. In 43rd International Business Research Conference, Proceedings of : 13 - 15 July 2017, Ryerson University, Toronto, Canada. 2017

Author

Alsheikhmubarak, Abdulilah ; Giouvris, Evangelos. / A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns. 43rd International Business Research Conference, Proceedings of : 13 - 15 July 2017, Ryerson University, Toronto, Canada. 2017.

BibTeX

@inproceedings{cd425b72a7cb4f87b69ee4251dd88ea6,
title = "A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns",
abstract = "Volatility estimation is an important aspect when analysing market movements. The purpose of this paper is to study the ability of symmetric and asymmetric GARCH models to investigate the volatility of the FTSE 100 Implied Volatility Index (IVI). We use several alternative models including GARCH, EGARCH, GJR-GARCH, and the mixed data sampling approach, GARCH-MIDAS to model the conditional variance. We also introduce FTSE 100 index returns and several macroeconomic variables into the analysis to investigate whether they have an explanatory role in defining the conditional variance. The macroeconomic variables are the UK industrial production, 3 months LIBOR, GBP effective exchange rate, and unemployment rate. The results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. Our results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. The GARCH-MIDAS approach also presented evidences of the effect of these explanatory factors on estimating IVI. ",
author = "Abdulilah Alsheikhmubarak and Evangelos Giouvris",
year = "2017",
month = jul,
day = "13",
language = "English",
booktitle = "43rd International Business Research Conference, Proceedings of",

}

RIS

TY - GEN

T1 - A Comparative GARCH Analysis of Macroeconomic Variables and Returns on FTSE 100 Implied Volatility Index Returns

AU - Alsheikhmubarak, Abdulilah

AU - Giouvris, Evangelos

PY - 2017/7/13

Y1 - 2017/7/13

N2 - Volatility estimation is an important aspect when analysing market movements. The purpose of this paper is to study the ability of symmetric and asymmetric GARCH models to investigate the volatility of the FTSE 100 Implied Volatility Index (IVI). We use several alternative models including GARCH, EGARCH, GJR-GARCH, and the mixed data sampling approach, GARCH-MIDAS to model the conditional variance. We also introduce FTSE 100 index returns and several macroeconomic variables into the analysis to investigate whether they have an explanatory role in defining the conditional variance. The macroeconomic variables are the UK industrial production, 3 months LIBOR, GBP effective exchange rate, and unemployment rate. The results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. Our results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. The GARCH-MIDAS approach also presented evidences of the effect of these explanatory factors on estimating IVI.

AB - Volatility estimation is an important aspect when analysing market movements. The purpose of this paper is to study the ability of symmetric and asymmetric GARCH models to investigate the volatility of the FTSE 100 Implied Volatility Index (IVI). We use several alternative models including GARCH, EGARCH, GJR-GARCH, and the mixed data sampling approach, GARCH-MIDAS to model the conditional variance. We also introduce FTSE 100 index returns and several macroeconomic variables into the analysis to investigate whether they have an explanatory role in defining the conditional variance. The macroeconomic variables are the UK industrial production, 3 months LIBOR, GBP effective exchange rate, and unemployment rate. The results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. Our results show that market returns and macroeconomic factors exhibit an important role in modelling the volatility for IVI indices, especially when using GARCH (1,1), which outperformed other models. The GARCH-MIDAS approach also presented evidences of the effect of these explanatory factors on estimating IVI.

M3 - Conference contribution

BT - 43rd International Business Research Conference, Proceedings of

ER -