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Spill Over Effects of Futures Contracts Initiation on the Cash Market: A Comparative Analysis


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  • Karathanassis, George
  • Sogiakas, Vasilios
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    This paper investigates possible spill over effects on the Spot Market due to the initiation of Futures contracts in three different financial markets. According to many analysts there still exists a puzzle regarding the stabilization or destabilization effects of futures contracts. Although the speculative forces (uninformed investors) tend to destabilize the market, rational hedging strategies and the transition of risk allow for stabilization shift. In order to investigate this issue, many researchers during the last decade, have utilized the GARCH framework enriched to capture many stylized financial features, such as the asymmetric response to news and leptokurtosis. However, in this paper the GARCH framework is extended to allow for skewness in the distribution of returns and to examine the timing of possible structural changes, while the conditional mean of the process is adjusted to account for time-varying risk premia and for the day of the week effects decomposition. Furthermore, the distinguishing feature of this paper is the SWARCH econometric model, which enables a dynamic regime shifting through a Markov Chain transition matrix. According to the empirical findings for the UK, Spanish and Greek Capital markets, there exist a significant stabilization effect either in the long run or in the short run, which is negatively associated with the level of efficiency and completeness of these capital markets.

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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 5958.

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    Date of creation: 26 Nov 2007
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    Handle: RePEc:pra:mprapa:5958

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    Keywords: Index Futures Contracts; AP-GARCH-M; SWARCH-L;

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    1. Pierluigi Bologna & Laura Cavallo, 2002. "Does the introduction of stock index futures effectively reduce stock market volatility? Is the 'futures effect' immediate? Evidence from the Italian stock exchange using GARCH," Applied Financial Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 12(3), pages 183-192.
    2. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 391-407, March.
    3. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    4. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, Elsevier, vol. 64(1-2), pages 307-333.
    5. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(4), pages 493-530.
    6. Robert C. Merton, 1995. "Financial Innovation and the Management and Regulation of Financial Institutions," NBER Working Papers 5096, National Bureau of Economic Research, Inc.
    7. Figlewski, Stephen, 1981. "Futures Trading and Volatility in the GNMA Market," Journal of Finance, American Finance Association, American Finance Association, vol. 36(2), pages 445-56, May.
    8. Bessembinder, Hendrik & Seguin, Paul J, 1992. " Futures-Trading Activity and Stock Price Volatility," Journal of Finance, American Finance Association, American Finance Association, vol. 47(5), pages 2015-34, December.
    9. Cox, Charles C, 1976. "Futures Trading and Market Information," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 84(6), pages 1215-37, December.
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