Multiscale interdependence between the major agricultural commoditiesŽivkov D., Njegić J., Pećanac M. (2019): Multiscale interdependence between the major agricultural commodities. Agric. Econ. – Czech, 65: 82-92.
download PDF

This paper investigates multiscale dynamic interconnection between the five agricultural commodities – corn, wheat, soybean, rice and oats, covering more than 18 years period. For research purposes, two complementary methodologies were used – wavelet coherence and phase difference. Low coherence is present at shorter time-horizons, while at longer time-horizons high coherence areas are found, but they are not widespread in all wavelet coherence plots. These results speak in favour of diversification opportunities. Strong coherence in longer time-horizons indicates that common factors are likely to be the main determinants of the agricultural prices in the long-run. On the other hand, rare high coherence areas at lower scales suggest that monetary and financial activities are most likely the causes that have affected the comovements of the grain prices in the short-term horizons. Phase difference discloses a relatively stable pattern between corn-soybean, corn-wheat, rice-oats and oats-soybean in the longer time-horizons. Taking into account investors’ diversification benefits and the leading (lagging) connections in long-run, corn and oats are the most appropriate cereals to be combined in an n-asset portfolio, since these two cereals constantly and very steadily lag soybean, whereas strong coherence between corn and oats does not frequently occur in all wavelet scales.

Adämmer Philipp, Bohl Martin T., von Ledebur Ernst-Oliver (2017): DYNAMICS BETWEEN NORTH AMERICAN AND EUROPEAN AGRICULTURAL FUTURES PRICES DURING TURMOIL AND FINANCIALIZATION. Bulletin of Economic Research, 69, 57-76
Aguiar-Conraria Luı´s, Joana Soares Maria (2011): Business cycle synchronization and the Euro: A wavelet analysis. Journal of Macroeconomics, 33, 477-489
Baldi Lucia, Peri Massimo, Vandone Daniela (2016): Stock markets’ bubbles burst and volatility spillovers in agricultural commodity markets. Research in International Business and Finance, 38, 277-285
Barunik J., Vacha L. (2013): Contagion among Central and Eastern European Stock Markets during the Financial Crisis. Finance a úvěr – Czech Journal of Economics and Finance, 63: 443–453.
Cipra T. (2010): Securitization of longevity and mortality risk. Finance a úvěr – Czech Journal of Economics and Finance, 60: 545–560.
Ceylan O., Gozde U. (2012): Cointegration and extreme value analyses of Bovespa and the Istanbul Stock Exchange. Finance a úvěr – Czech Journal of Economics and Finance, 62: 66–90.
Conlon Thomas, Cotter John (2012): An empirical analysis of dynamic multiscale hedging using wavelet decomposition. Journal of Futures Markets, 32, 272-299
Dajčman S. (2012): The dynamics of return comovement and spillovers between the Czech and European stock markets in the period 1997–2010. Finance a úvěr – Czech Journal of Economics and Finance, 62, 368-390.
Dajčman Silvo (2013): Interdependence Between Some Major European Stock Markets - A Wavelet Lead/Lag Analysis. Prague Economic Papers, 22, 28-49
Datastream (2018): Datastream. European University Institute. Available at
Dewandaru Ginanjar, Rizvi Syed Aun R., Masih Rumi, Masih Mansur, Alhabshi Syed Othman (2014): Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis. Economic Systems, 38, 553-571
Gilbert C.L. (2010a): How to understand high food prices. Journal of Agricultural Economics, 61: 398–425.
Gilbert C.L. (2010b): Speculative Influences on Commodity Futures Prices 2006–2008. United Nations Conference on Trade and Development (UNCTAD). Discussion Papers No. 197.
Grieb Terrance (2015): Mean and volatility transmission for commodity futures. Journal of Economics and Finance, 39, 100-118
Hamadi Hassan, Bassil Charbel, Nehme Tamara (2017): News surprises and volatility spillover among agricultural commodities: The case of corn, wheat, soybean and soybean oil. Research in International Business and Finance, 41, 148-157
Hernandez Manuel A., Ibarra Raul, Trupkin Danilo R. (2014): How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets. European Review of Agricultural Economics, 41, 301-325
Irwin Scott H., Sanders Dwight R. (2012): Financialization and Structural Change in Commodity Futures Markets. Journal of Agricultural and Applied Economics, 44, 371-396
Lahiani Amine, Nguyen Duc Khuong, Vo Thierry (2013): Understanding Return And Volatility Spillovers Among Major Agricultural Commodities. Journal of Applied Business Research (JABR), 29, 1781-
Matošková D. (2011): Volatility of agrarian markets aimed at the price development. Agricultural Economics (Zemědělská ekonomika), 57, 35-40
Musunuru Naveen (2014): Modeling Price Volatility Linkages between Corn and Wheat: A Multivariate GARCH Estimation. International Advances in Economic Research, 20, 269-280
Sanjuán-López Ana I., Dawson Philip J. (2017): Volatility Effects of Index Trading and Spillovers on US Agricultural Futures Markets: A Multivariate GARCH Approach. Journal of Agricultural Economics, 68, 822-838
Trujillo-Barrera A., Mallory M., Garcia P. (2012): Volatility spillovers in U.S. crude oil, ethanol, and corn futures markets. Journal of Agricultural and Resource Economics, 37: 247–262.
Torrence Christopher, Webster Peter J. (1999): Interdecadal Changes in the ENSO–Monsoon System. Journal of Climate, 12, 2679-2690<2679:ICITEM>2.0.CO;2
Vacha Lukas, Barunik Jozef (2012): Co-movement of energy commodities revisited: Evidence from wavelet coherence analysis. Energy Economics, 34, 241-247
Von Braun J., Tadesse G. (2012): Global Food Price Volatility and Spikes: an Overview of Costs, Causes, and Solutions. ZEF-Discussion Papers on Development Policy No. 161.
Živkov D., Balaban S., Đurašković J. (2018): What multiscale approach can tell about the nexus between exchange rate and stocks in the major emerging markets? Finance a úvěr – Czech Journal of Economics and Finance, 68: 491–512.
Živkov Dejan, Đurašković Jasmina, Manić Slavica (2018): How do oil price changes affect inflation in Central and Eastern European countries? A wavelet-based Markov switching approach. Baltic Journal of Economics, 19, 84-104
download PDF

© 2022 Czech Academy of Agricultural Sciences | Prohlášení o přístupnosti