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


  • Karathanassis, George
  • Sogiakas, Vasilios


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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  • Karathanassis, George & Sogiakas, Vasilios, 2007. "Spill Over Effects of Futures Contracts Initiation on the Cash Market: A Comparative Analysis," MPRA Paper 5958, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:5958

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    References listed on IDEAS

    1. Figlewski, Stephen, 1981. "Futures Trading and Volatility in the GNMA Market," Journal of Finance, American Finance Association, vol. 36(2), pages 445-456, May.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Bessembinder, Hendrik & Seguin, Paul J, 1992. " Futures-Trading Activity and Stock Price Volatility," Journal of Finance, American Finance Association, vol. 47(5), pages 2015-2034, December.
    4. Merton, Robert C., 1995. "Financial innovation and the management and regulation of financial institutions," Journal of Banking & Finance, Elsevier, vol. 19(3-4), pages 461-481, June.
    5. Spyros I. Spyrou, 2005. "Index Futures Trading and Spot Price Volatility," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 4(2), pages 151-167, August.
    6. 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, vol. 55(2), pages 391-407, March.
    7. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    8. 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.
    9. Cox, Charles C, 1976. "Futures Trading and Market Information," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1215-1237, December.
    10. 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, vol. 12(3), pages 183-192.
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    More about this item


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

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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