Welcome to Open Science
Contact Us
Home Books Journals Submission Open Science Join Us News
The Interdependency of Asset pricing on Prices of Its Substitutes: Application to Cocoa, Coffee and Tea
Current Issue
Volume 3, 2015
Issue 5 (October)
Pages: 277-282   |   Vol. 3, No. 5, October 2015   |   Follow on         
Paper in PDF Downloads: 39   Since Sep. 23, 2015 Views: 1764   Since Sep. 23, 2015
Authors
[1]
Kwadwo Agyei Nyantakyi, Ghana Institute of Management and Public Administration (GIMPA), Business School, Accra, Ghana.
Abstract
In this paper we examine the behaviour of the prices, of Cocoa, Coffee and Tea as beverages (substitutes). We also investigate if the pricing of one asset is influenced by the prices of any of the other assets. Using Akaike Information Criterion (AIC), Schwarz Information Criterion (SIC) for selecting the best model out of all the competing models, the best models fitted were, Cocoa prices being ARIMA (0, 1, 2), Coffee prices ARIMA (1, 1, 1) and Tea prices ARIMA (0, 1, 0) respectively. Thus, all the three variables were integrated of order I (1), Using Johansen cointegration test, we observed that there was at most one cointegration equation, among these assets, indicating that there is a long-run equilibrium among the pricing of the prices of Cocoa, Coffee and Tea. Analysis of the Granger causality test shows that there is Granger causality between all the three variables; hence there is a long run association among prices of cocoa, coffee and tea. Also from the cross correlation matrix it was observed that all the three variables were positively correlated with cocoa and coffee having a very high correlation of 0.8. This indicates a probable higher dependency of the pricing of these two assets on the price of the other. Due to the cointegration, Vector Error Correction model (VECM) was used to estimate the equation relating the prices of Cocoa, Coffee and Tea.
Keywords
Cointegration, Long-Run Equilibrium, Correlation Matrix, Normality, VECM
Reference
[1]
Ahn, SK. and G. C. Reinsel (1990) “Estimation for Partially Nonstationary Autoregressive Models”, Journal of the American Statistical Association, 85, 813-823.
[2]
Anderson, T. W. (1984), An Introduction to Multivariate Statistical Analysis, 2nd Edition. Wiley: New York.
[3]
Andrews, D. W. K. and J. C. Moynihan (1990) An Improved Heteroskedastic and Autocorrelation Consistent Covariance Matrix Estimator, Cowles Foundation Discussion Paper No. 942, Yale University.
[4]
Buse, R. C. (1958), “Total Elasticities - A predictive Device”, J. FARM ECONS 40: 881-891.
[5]
Dickey, D. A.; Fuller, W. A. (1979). "Distribution of the Estimators for Autoregressive Time Series with a Unit Root". Journal of the American Statistical Association 74 (366): 427–431.
[6]
Engle, R. F. and Granger, C. W. J. (1987). “Co-integration and error correction representation, estimation and testing”. Econometrica 55: 251-276.
[7]
Gardner, B. L. (1976) “Futures Prices in Supply Analysis”, Am J. AG. Econs.58:81-84.
[8]
Goodwin, N, Nelson, J; Ackerman, F & Weissskopf, T: Microeconomics in Context 2d ed. Sharpe 2009.
[9]
Jarque, Carlos M.; Bera, Anil K. (1980). "Efficient tests for normality, homoscedasticity and serial independence of regression residuals". Economics Letters 6 (3): 255–259.
[10]
Johansen, S. (1988). “Statistical analysis of co-integration vectors”. Journal of Economic Dynamics and Control 12: 231-254.
[11]
Koyck, L. (1954), “Distributed Lags and Investment Analysis”, North-Holland Publishing, Co (1954).
[12]
Mas-Colell, Andreu; Whinston, Green & Michael, Jerry (1995). Microeconomic Theory. Oxford: Oxford University Press.
[13]
Nerlove, M. (1958), The Dynamic of Supply: Estimation of Farmer’s Response to Price, John Hopkins University Press.
[14]
Nicholson, Walter (1978). Microeconomic Theory (Second ed.). Hinsdale: Dryden Press. pp. 90–93.
[15]
Slutsky, E. E. (1915). "Sulla teoria del bilancio del consumatore". Giornale degli Economisti 51 (July): 1–26
[16]
Tomek, W. G. and Robinson K. L., 2003. Agricultural Product Prices, Cornell University Press.
[17]
Vogelvang, E., Smith, H. P., (1997), “Changing Interactions on Markets for Competing Commodities: The Case of Natural and Synthetic Rubber Prices”, Vrije University, Faculty of Economics and Econometrics, De Boelelaan 1105, 1081 HV, Amsterdam, Netherland.
[18]
Wickramasinghe, W. M. Y. A. B., (2013), The Effect of Exogenous Factors on World Natural Rubber Prices. PGIA - University of Peradeniya, Sri Lanka.
[19]
World Bank Pink Sheet Annual Data (1961-2013), [on line]. [Accessed on, 08.08. 2014]. Available at http://econ.worldbank.org.
[20]
Zainalabidin, M, Khin A. A,. and Hameed A. A. A., (2012), “The Impact of the Changes of the World Crude Oil Prices on the Natural Rubber Industry in Malaysia”, World Applied Sciences Journal 20 (5): 730-737, 2012ISSN 1818-4952.
Open Science Scholarly Journals
Open Science is a peer-reviewed platform, the journals of which cover a wide range of academic disciplines and serve the world's research and scholarly communities. Upon acceptance, Open Science Journals will be immediately and permanently free for everyone to read and download.
CONTACT US
Office Address:
228 Park Ave., S#45956, New York, NY 10003
Phone: +(001)(347)535 0661
E-mail:
LET'S GET IN TOUCH
Name
E-mail
Subject
Message
SEND MASSAGE
Copyright © 2013-, Open Science Publishers - All Rights Reserved