Effectiveness of Commodity Futures in Curbing Spot Volatility

Chepchirchir Rancy^1, and Olukuru John¹

¹School of Finance and Applied Economics, Strathmore University, P.O. Box 59857, Nairobi, Kenya

Cite this paper:
Chepchirchir Rancy and Olukuru John. Effectiveness of Commodity Futures in Curbing Spot Volatility. Journal of Finance and Economics. 2017; 5(3):85-95. doi: 10.12691/jfe-5-3-1

Abstract

This study examines the impact of introduction of futures trading on the spot price volatility in the commodity market. The paper considers the United States of America, South Africa and Ethiopian economies. Three commodities i.e. coffee, maize and wheat from New York Mercantile Exchange, South African Futures Exchange and Ethiopian Commodity Exchange are analyzed. ARCH LM test is used to check for heteroskedasticity and GARCH and EGARCH are used to check for the behavior of volatility for the pre- and post-futures periods. For all the three economies, the results indicate presence of the ARCH effect in the log returns. For conditional and unconditional variances; spot price volatility for coffee has decreased after futures trading across all the economies and the EGARCH has also shown reduction in persistence of volatility in the post-futures period in the three economies; while that of maize has reduced for the Ethiopian economy but increased in both the US and South African economies. For wheat, the conditional variance has been found to rise in the post-futures period in all the three economies. These results imply that more positive feedback from futures trading is bound to be seen for maize in the less developed economies as opposed to the developed economies as opposed to the other products. This paper has focused on the overlooked factor by earlier researchers, i.e. of economic-gap amongst countries, in looking at the impact of the futures trading on the spot price variation.

Keywords:
derivatives futures exchange agricultural commodities spot price volatility

This work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

References:

[1]	Antonio, A. and Holmes, P. (1995). Futures Trading, Information and Spot Price Volatility: Evidence from the FTSE-100 Stock Index Futures Contract Using GARCH. Journal of Banking and Finance 19, 117-129.
[2]	Miller, K. D. (1979). The Relation Between Volatility and Maturity in Futures Contracts.” in Commodity Markets and Futures Prices, Leuthold, R. M. (ed). Chicago Mercantile Exchange, pp. 25-36.
[3]	Chance, D. M., & Brooks, R. (2015). Introduction to derivatives and risk management. Cengage Learning.
[4]	FAO, I., IMF, O., & UNCTAD, W. (2011). The World Bank, the WTO, IFPRI and the UN HLTF (2011). Price Volatility in Food and Agricultural Markets: Policy Responses. Rome, FAO.
[5]	Jacks, D. S., O'Rourke, K. H., & Williamson, J. G. (2011). Commodity price volatility and world market integration since 1700. Review of Economics and Statistics, 93(3), 800-813.
[6]	Newbery, D. M. (1989). The theory of food price stabilisation. The Economic Journal, 99(398), 1065-1082.
[7]	Tadesse, G., & Guttormsen, A. G. (2011). The behavior of commodity prices in Ethiopia. Agricultural Economics, 42(1), 87-97.
[8]	Bessembinder, H., & Seguin, P. J. (1992) Futures-trading activity and stock price volatility. Journal of Finance, 47, 2015-2034.
[9]	Aber, J. W., Li, D., & Can, L. (2009). Price volatility and tracking ability of ETFs. Journal of Asset Management, 10(4), 210-221.
[10]	Carlson, J. B., Craig, B., Higgins, P., & Melick, W. R. (2006). FOMC communications and the predictability of near-term policy decisions. Futures, 8, 10.
[11]	Chen H., Han Q., Li Y. & Wu K. (2012). Does Index Futures Trading reduce Price Volatility in the Chinese Stock market? A Panel data Evaluation Approach Journal of Finance, 33 (12), 1167-1190.
[12]	Cox, C. C. (1976). Futures Trading and Market Information Journal of Political Economy 84(6).
[13]	Brorsen, B. W. and Yang, S. R. (1989). “Generalized Autoregressive Conditional Heteroskedasticity as a Model of the Distribution of Futures Returns.” Applied Commodity Price Analysis, Forecasting, and Market Risk Management. Hayenga, M. (ed.). Ames, IA: Iowa State University.
[14]	Polk, C., Hanson, R., Ledyard, J., & Ishikida, T. (2003). The policy analysis market: an electronic commerce application of a combinatorial information market.
[15]	Spyrou, S. I. (2005). Index Futures Trading and Spot Price Volatility: Journal of Emerging Market Finance 4: 151-167.
[16]	Jacks, D. S. (2007). Populists versus theorists: Futures markets and the volatility of prices. Explorations in Economic History, 44(2), 342-362.
[17]	Tauchen, G. E., & Pitts, M. (1983). The price variability-volume relationship on speculative markets. Econometrica: Journal of the Econometric Society, 485-505.
[18]	Gilbert, C.L. and Morgan, C. W. (2010) Food Price Volatility: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 365, 3023-34.
[19]	Rolfo, J. (1980). Optimal Hedging under Price and Quantity Uncertainty: The case of a Cocoa Producer. JPE. 88(1) 100-116.
[20]	Debasish, S.S. (2009). Effect of futures trading on spot-price volatility: evidence for NSE Nifty using GARCH The Journal of Risk Finance 10(1) 67-77.
[21]	Chen, H., Han, Q., Li, Y., & Wu, K. (2013). Does index futures trading reduce volatility in the Chinese stock market? A panel data evaluation approach Journal of Futures Markets, 33(12), 1167-1190.
[22]	Darrat, A. F., & Rahman, S. (1995). Has futures trading activity caused stock price volatility? Journal of Futures Markets, 15, 537-557.
[23]	Rahman, S. (2001). The introduction of derivatives on the Dow Jones Industrial Average and their impact on the volatility of component stocks Journal of Futures Markets, 21(7), 633-653.
[24]	Mayhew, S. (2000). The Impact of Derivatives on Cash Markets: What Have We Learnt? Working Paper, Department of Banking & Finance, University of Georgia, Athens.
[25]	Galeano, P., & Tsay, R. S. (2010). Shifts in individual parameters of a GARCH model. Journal of Financial Econometrics, 8(1), 122-153.
[26]	Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of econometrics, 31(3), 307-327.
[27]	Marquering, W., & Verbeek, M. (2004). The Economic Value of Predicting Stock Index Returns and Volatility (Digest Summary). Journal of Financial and Quantitative Analysis, 39(2407-429).
[28]	Brooks, C. (2008). Univariatetime series modelling and forecasting. Introductory Econometrics for Finance. 2nd Ed. Cambridge University Press. Cambridge, Massachusetts.
[29]	Engle, R. F., & Bollerslev, T. (1986). Modelling the persistence of conditional variances. Econometric reviews, 5(1), 1-50.
[30]	Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The GARCH of financial markets. Nonlinearities in Financial Data.
[31]	Butterworth, D. (1998) The Impact of Futures Trading on Underlying Stock Index Volatility: The Case of the FTSE Mid 250 Contract‟, Journal of Finance, Department of Economics, University of Durham.
[32]	Antoniou, A., & Holmes, P. (1995). Futures trading, information and spot price volatility: evidence for the FTSE-100 stock index futures contract using GARCH. Journal of Banking & Finance, 19(1), 117-129.
[33]	Nelson, D. B. (1991). Conditional heteroskedasticity in asset returns: A new approach. Econometrica: Journal of the Econometric Society, 347-370.
[34]	Floros, C., & Vougas, D. V. (2006). Index futures trading, information and stock market volatility: The case of Greece. Derivatives Use, Trading & Regulation, 12(1-2), 146-166.
[35]	Unctad, T. (2005). Development Report. United Nations, New York and Geneva.