Modeling the Returns on Nigeria's Agricultural Food Export
Price using GARCH Model

Omeruruike Gideon Wobo; Echendu Nwaigwe

doi:https://doi.org/10.56201/ijebm.v8.no3.2022.pg1.8

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Modeling the Returns on Nigeria's Agricultural Food Export Price using GARCH Model

Omeruruike Gideon Wobo & Echendu Nwaigwe

Abstract

The study investigates GARCH Model in modeling of the returns on Nigeria’s agricultural food export price, specifically to; determine whether Nigeria agricultural export Prices can be fitted to a volatility model, to test the present ARCH effect in the return volatility of Nigeria agricultural export Prices and determine the impact of price volatility in Nigerian Agricultural export markets. Using the cotton price to represents Nigeria agricultural export price, the logarithm returns for various months were computed, descriptive statistics of the logarithm returns was calculated and the volatility of the market was estimated using the standard deviation and the addition of the ARCH and GARCH components of the GARCH model was done to the determine persistence of volatility impact . It was found that the Agricultural export market has volatility of 0.514 with 88.3% persistence of volatility impact between 1992 to 2020. This show that the market is highly volatile within period under investigations than the period preceding it. The recommendation is that the depth of instruments in the Agricultural export market should be varied in terms of fix ed tradable financial instruments used to raise capital in the Agricultural export market than concentrating on the would be returned to the marketer if all of the assets were wind up and all of the marketer’s debts were paid off.

Keywords

ModelingReturnsExportPriceGARCH

References

Abduikareem A. and Abdulhakeem K.A (2016). Analyzing Oil Price – Macroeconomic Volatility in Nigeria. Central Bank of Nigeria Journal of Applied Statistics.1(1) Adamu, A. (2008). The Effects of global financial crisis on Nigerian Economy. International Journal of Investment and Finance 1(1)1-2. Apergis, N & Rezitis, A. (2011)“Food price volatility and macroeconomic factors: Evidence from GARCH and GARCH-X estimates”, Journal of Agricultural and Applied Economics,( 43)1, 95-110, Atoi M. (2014). Testing volatility in Nigeria Stock Marketing using GRACH model. Central Bank of Nigeria Journal of Applied Statistics . 5(2) . 65. central Bank of Nigeria (CBN) Cipriani, M., & Guarino, A. (2008). Herd behavior and contagion in financial markets. The B.E. Journal of Theoretical Economics 8(1) 24, 1-54. Deebom, Z . D& Essi I.D(2017), modeling and estimating volatility of Nigerian crude oil markets using GARCH models:1987-June 2017 Engle, R. F. (1982). Autoregressive conditional heteroscadasticity with estimates of the variance of the U.K. inflation. Econometrica, 50(3):987-1008. Mala, R, & Reddy, M. (2007). Measuring stock market volatility in an emerging economy. International Research Journal of Finance and Economics Issue 8 126-133. Newbery, D. M. ( 1989) “The theory of food price stabilization”, Economic Journal,(99) 1065- 1082, Rashid, S. & Meron, A(2007) “Cereal price instability in Ethiopia: An analysis of sources and policy options”, paper prepared for the Agricultural Economics Association for Africa, Accra Ghana, 84-99 Zheng, H. W. Kinnucan,& Thompson, H. (2008) “News and volatility of food prices”, Applied Economics, 40, 1629-1635.

Modeling the Returns on Nigeria's Agricultural Food Export Price using GARCH Model

Abstract

Keywords

References

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