Please use this identifier to cite or link to this item: https://hdl.handle.net/10593/13053
Title: Modeling and Forecasting the Implied Volatility of the WIG20 Index
Authors: Buszkowska-Khemissi, Eliza
Płuciennik, Piotr
Keywords: implied volatility
GARCH
ARFIMA
forecasting
Issue Date: 2007
Publisher: Uniwersytet Łódzki
Citation: Buszkowska, E., Płuciennik, P., Modeling and Forecasting the Implied Volatility of the WIG20 Index. Proceedings of Thirty Third International Conference Macromodels 2006, Łódź 2007.
Abstract: The implied volatility is one of the most important notions in the financial market. It informs about the volatility forecasted by the participans of the market. In this paper we calculate the daily implied volatility from options on the WIG20 index. First we test the long memory property of the time series obtained in such a way, and then we model and forcast it as ARFIMA process
URI: http://hdl.handle.net/10593/13053
ISBN: 978-83-924305-4-4
Appears in Collections:Materiały konferencyjne (WPiA)

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