Stock return volatility and the internet phenomenon
This study examines the question of 'Does the internet phenomenon affect the volatility of stock returns of legacy companies?’1 GARCH models and the Wald test are applied to investigate the persistence of stock return volatility and breaks in the volatility. A special GARCH (1,1) model is also employed with an additional regressor (the market return) to observe the trend of time-varying betas.
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Volume (Year): 2 (2006)
Issue (Month): 2 (March)
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References listed on IDEAS
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- Young-Hye Cho & Robert F. Engle, 1999. "Time-Varying Betas and Asymmetric Effect of News: Empirical Analysis of Blue Chip Stocks," NBER Working Papers 7330, National Bureau of Economic Research, Inc.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
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Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Lumsdaine, Robin L, 1996. "Consistency and Asymptotic Normality of the Quasi-maximum Likelihood Estimator in IGARCH(1,1) and Covariance Stationary GARCH(1,1) Models," Econometrica, Econometric Society, vol. 64(3), pages 575-596, May.
- Dipankor Coondoo & Paramita Mukherjee, 2004. "Components of volatility and their empirical measures: a note," Applied Financial Economics, Taylor & Francis Journals, vol. 14(18), pages 1313-1318.
- Hai-Chin Yu & Ming-Chang Huang, 2004. "Statistical properties of volatility in fractal dimensions and probability distribution among six stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(15), pages 1087-1095.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July. Full references (including those not matched with items on IDEAS)
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