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Activity Number:
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130
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #305685 |
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Title:
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Modeling Uncertainty in Daily Asset Returns Using ARCH/GARCH Models
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Author(s):
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Linda Njoh*+ and Jane L. Harvill
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Companies:
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Baylor University and Baylor University
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Address:
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Department of Statistical Science, Waco, TX, 76706,
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Keywords:
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Volatility ; Stock Return ; ARCH ; APARCH ; GARCH ; ARMA
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Abstract:
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One of the most prominent tools used by financial economists for capturing the volatility of financial markets are the so-called value-at-risk models or more precisely, generalized autoregressive conditional heteroscedasticity (GARCH) models. This study investigates the performance of ARCH/GARCH models in explaining volatility of daily time series of Ford stock returns. We fit four time series models (ARMA, ARCH, APARCH and GARCH) to the returns, and use model selection and volatility prediction schemes to pick the model that produces optimal predictions.
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