Title: Heteroscedasticity in stock market indicator return data: volume versus GARCH effects
Abstract: Abstract This paper tests for the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) effects in stock market indicator returns using the NYSE daily return and volume data for four years. The findings strongly suggest that the market indicator returns are best described by the GARCH model in the absence of volume as a mixing variable. The inclusion of volume as a proxy for information arrival in the conditional variance model helps in explaining the GARCH effects in stock returns, however, the GARCH effects do not completely vanish as a result of this inclusion.
Publication Year: 1996
Publication Date: 1996-08-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 76
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