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Time-Varying Betas and Asymmetric Effect of News: Empirical Analysis of Blue Chip Stocks

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Young-Hye Cho
Robert F. Engle

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Abstract

We investigate whether or not a beta increases with bad news and decreases with good news, just as does volatility. Using daily returns for nine stocks in a double beta model with EGARCH specifications, we show that news asymmetrically affects the betas of individual stocks. We find that betas depend on two source of news: market shocks and idiosyncratic shocks. Some stock betas depend on both while others depend on one. We categorize each stock return as belonging to one of three beta process models, a joint, an idiosyncratic, and a market model based on the role of market shocks and idiosyncratic shocks. Our conclusions differ from those of Brown, Nelson, and Sunnier (1995) who worked with monthly aggregated data in a bivariate EGARCH model. We believe that stock price aggregation in this previous research resulted in a loss of cross sectional variation and consequently lead to weak results. If the asymmetric effect is more readily apparent in daily data, then this may again explain previous researchers' inability to detect asymmetric effects. Our findings shed light on the controversy as to whether abnormalities in stock returns result from overreaction to information or from changes in expected returns in an efficient market. Finding an asymmetric effect in betas leads us to conclude that abnormalities can, at least partially, be explained by changes in expected returns through a change in beta.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 7330.

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Date of creation: Sep 1999
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Handle: RePEc:nbr:nberwo:7330

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G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Heiko Ebens, 2000. "The Distribution of Stock Return Volatility," NBER Working Papers 7933, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  2. Virginia Liu & Francis Tapon & Yiguo Sun, 2006. "Stock return volatility and the internet phenomenon," Applied Financial Economics Letters, Taylor and Francis Journals, vol. 2(2), pages 105-109, March. [Downloadable!] (restricted)
  3. Nilsson, Birger, 2002. "International Asset Pricing and the Benefits from World Market Diversification," Working Papers 2002:1, Lund University, Department of Economics. [Downloadable!]
  4. Attiya Y. Javid & Eatzaz Ahmad, 2008. "The Conditional Capital Asset Pricing Model: Evidence from Karachi Stock Exchange," PIDE-Working Papers 2008:48, Pakistan Institute of Development Economics. [Downloadable!]
  5. José L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Working Papers Series 126, Central Bank of Brazil, Research Department. [Downloadable!]
  6. Charles S. Bos & Phillip Gould, 2007. "Dynamic Correlations and Optimal Hedge Ratios," Tinbergen Institute Discussion Papers 07-025/4, Tinbergen Institute. [Downloadable!]
  7. Jose L. B. Fernandes & Augusto Hasman & Juan Ignacio Peña, 2006. "Risk Premium: Insights Over The Threshold," Business Economics Working Papers wb062808, Universidad Carlos III, Departamento de Economía de la Empresa. [Downloadable!]
  8. John M. Maheu & Thomas H. McCurdy, 2003. "News Arrival, Jump Dynamics and Volatility Components for Individual Stock Returns," CIRANO Working Papers 2003s-38, CIRANO. [Downloadable!]
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