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The nature of volatility in temporal profit with in Ethiopian commodity exchange: The case of washed export coffee modelled using ARFIMA-M-HYGARCH model

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  • Mezgebo, Taddese

Abstract

Using AFIRMA-M-HYGARCH model it is found that the structure of temporal profit was observed to change in three periods. Since the second and third periods are associated with lagged effect of heavy handed state intervention, it was possible to get an idea to the effect of such state policy. It is concluded in this paper that the strategy was more destabilizing and it did harm wholesale traders by reducing their return from volatility, but it also improve their leverage to some extent. More over in what state intervention resulted is in changing the stable high volatility toward more structured and hard to control clustered volatility, than reducing it. For some time, however, the limit of the volatility was reduced while destabilizing the market from day to day. In general the grain market is observed to have high level of volatility in temporal profit.

Suggested Citation

  • Mezgebo, Taddese, 2012. "The nature of volatility in temporal profit with in Ethiopian commodity exchange: The case of washed export coffee modelled using ARFIMA-M-HYGARCH model," MPRA Paper 43345, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:43345
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    References listed on IDEAS

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    1. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    2. 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.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Bollerslev, Tim & Engle, Robert F, 1993. "Common Persistence in Conditional Variances," Econometrica, Econometric Society, vol. 61(1), pages 167-186, January.
    5. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    6. Davidson, James, 2004. "Moment and Memory Properties of Linear Conditional Heteroscedasticity Models, and a New Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22(1), pages 16-29, January.
    7. Mezgebo, Taddese & Dereje, Fikadu, 2010. "Structure, conduct and performance of grain trading in Tigray and its impact on demand for commodity exchange: The case Maychew, Mokone, Alemata, Mekelle and Himora," MPRA Paper 24901, University Library of Munich, Germany.
    8. 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.
    9. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    10. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
    11. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
    12. 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.
    13. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
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    More about this item

    Keywords

    Ethiopian commodity exchange; coffee export; Ethiopia; ECX; FIGARCH; HYGARCH; ARFIMA;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • 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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