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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.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 43345.

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Date of creation: 20 Feb 2012
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Handle: RePEc:pra:mprapa:43345

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Keywords: Ethiopian commodity exchange; coffee export; Ethiopia; ECX; FIGARCH; HYGARCH; ARFIMA;

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  1. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, American Finance Association, vol. 48(5), pages 1749-78, December.
  2. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, Elsevier, vol. 16(1), pages 121-130, May.
  3. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, Elsevier, vol. 14(2), pages 227-238, October.
  4. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report, Federal Reserve Bank of Minneapolis 157, Federal Reserve Bank of Minneapolis.
  5. 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.
  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, Econometric Society, vol. 55(2), pages 391-407, March.
  7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 347-70, March.
  8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, Elsevier, vol. 31(3), pages 307-327, April.
  9. Bollerslev, Tim & Engle, Robert F, 1993. "Common Persistence in Conditional Variances," Econometrica, Econometric Society, Econometric Society, vol. 61(1), pages 167-86, January.
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