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A good news or bad news has greater impact on the Vietnamese stock market?

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  • Nguyen Van, Phuong

Abstract

The arrival of news plays an extremely important role in the stock market because it mainly drives the movement of the stock market. In this paper, therefore, we would like to investigate how the Vietnamese stock market responses to the arrival of news via applying the AR – EGARCH in Mean model. Our research result indicates that the arrival of bad news has a greater impact on the conditional volatility than the arrival of good news does. We also found that there exists a positive tradeoff between the stock market returns and conditional volatility in the Vietnamese stock market.

Suggested Citation

  • Nguyen Van, Phuong, 2015. "A good news or bad news has greater impact on the Vietnamese stock market?," MPRA Paper 61194, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:61194
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    References listed on IDEAS

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    1. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    5. 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.
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    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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