Enhancing stock volatility prediction with the AO-GARCH-MIDAS model

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Enhancing stock volatility prediction with the AO-GARCH-MIDAS model

Research has substantiated that the presence of outliers in data usually introduces additional errors and biases, which typically leads to a degradation in the precision of volatility forecasts. However, correcting outliers can mitigate these adverse effects. This study corrects the additive outlier...

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Bibliographic Details
Main Authors:	Liu, Ting, Choo, Weichong, Tunde, Matemilola Bolaji, Wan, Cheongkin, Liang, Yifan
Format:	Article
Language:	English
Published:	Public Library of Science 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/113480/ http://psasir.upm.edu.my/id/eprint/113480/1/113480.pdf

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