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Intraday information transmission between DJIA spot and futures markets

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  • Gokce Soydemir
  • A. George Petrie
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    Abstract

    This study empirically examines the dynamic relationship between Dow Jones Industrial Average (DJIA) spot and futures markets by constructing a vector autoregressive (VAR) model. The volatility series in the VAR model are derived from the GARCH model estimations. The findings show evidence of two-way causality, but the impact of a one time increase in futures returns on the spot return volatility is found to be greater than the impact of a one time increase in spot returns on futures return volatility. Further, the results show that an increase in spot trading activity decreases spot and futures return volatility. However, a similar increase in futures trading activity increases futures return volatility but has no net impact on the spot return volatility. The results are consistent with the view that an investor trading in the futures market needs to consider the return movements in both spot and futures markets and the volume movements only in futures market. On the other hand, an investor trading in the spot market needs to consider only the return movements both in the spot and futures markets.

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    File URL: http://www.tandfonline.com/doi/abs/10.1080/0960310022000025460
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

    Volume (Year): 13 (2003)
    Issue (Month): 11 ()
    Pages: 817-827

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    Handle: RePEc:taf:apfiec:v:13:y:2003:i:11:p:817-827

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    Web page: http://www.tandfonline.com/RAFE20

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    1. David E. Runkle, 1987. "Vector autoregressions and reality," Staff Report 107, Federal Reserve Bank of Minneapolis.
    2. Runkle, David E, 1987. "Vector Autoregressions and Reality: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 454, October.
    3. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
    4. Litterman, Robert B, 1986. "Forecasting with Bayesian Vector Autoregressions-Five Years of Experience," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 25-38, January.
    5. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    6. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    7. Runkle, David E, 1987. "Vector Autoregressions and Reality," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(4), pages 437-42, October.
    8. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
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