Commodity Futures Markets: are they an effective price risk management tool for the European wheat supply chain? Cesar Revoredo-Giha SRUC - Food Marketing Research Marco Zuppiroli Università degli Studi di Parma - Dipartimento di Economia 2 nd AIEAA Conference, Parma, June 6-7 th, 2013 Outline of the presentation 1. Motivation 2. Research hypothesis 3. Empirical work a. Data used b. Methods 4. Results 5. Conclusions 2
1.Motivation This paper focuses on the use of European wheat futures contracts for hedging price risk. The relatively recent instability of commodity prices has brought back the interest on futures markets and their use by commodity producer for hedging as a device to reduce vulnerability to price risk. Furthermore, futures and options contracts have been proposed as a way in which importing countries could manage price volatility food security - (Sarris et al., 2011). The research on hedging effectiveness of European wheat futures contracts can potentially yield fairly relevant agricultural policy insights. 3 1. Open Interest EU Wheat Futures (converted in metric tons) 4
1. The price risk of wheat USA (Chicago) SRW UK (East Anglia) Feed wheat 1400 250 1200 200 1000 US cents/bushel 800 600 GBP/Tonne 150 100 400 50 200 0 0 01/01/1988 01/07/1988 01/01/1989 01/07/1989 01/01/1990 01/07/1990 01/01/1991 01/07/1991 01/01/1992 01/07/1992 01/01/1993 01/07/1993 01/01/1994 01/07/1994 01/01/1995 01/07/1995 01/01/1996 01/07/1996 01/01/1997 01/07/1997 01/01/1998 01/07/1998 01/01/1999 01/07/1999 01/01/2000 01/07/2000 01/01/2001 01/07/2001 01/01/2002 01/07/2002 01/01/2003 01/07/2003 01/01/2004 01/07/2004 01/01/2005 01/07/2005 01/01/2006 01/07/2006 01/01/2007 01/07/2007 01/01/2008 01/07/2008 01/01/2009 01/07/2009 01/01/2010 01/07/2010 01/01/2011 01/07/2011 01/01/2012 03/10/1988 03/04/1989 03/10/1989 03/04/1990 03/10/1990 03/04/1991 03/10/1991 03/04/1992 03/10/1992 03/04/1993 03/10/1993 03/04/1994 03/10/1994 03/04/1995 03/10/1995 03/04/1996 03/10/1996 03/04/1997 03/10/1997 03/04/1998 03/10/1998 03/04/1999 03/10/1999 03/04/2000 03/10/2000 03/04/2001 03/10/2001 03/04/2002 03/10/2002 03/04/2003 03/10/2003 03/04/2004 03/10/2004 03/04/2005 03/10/2005 03/04/2006 03/10/2006 03/04/2007 03/10/2007 03/04/2008 03/10/2008 03/04/2009 03/10/2009 03/04/2010 03/10/2010 03/04/2011 03/10/2011 03/04/2012 France (Rouen) Milling wheat Italy (Bologna) Milling wheat #3 350.00 350.00 300.00 300.00 250.00 250.00 Euro/Tonne 200.00 150.00 200.00 150.00 100.00 100.00 50.00 50.00 0.00 0.00 27/03/1998 27/07/1998 27/11/1998 27/03/1999 27/07/1999 27/11/1999 27/03/2000 27/07/2000 27/11/2000 27/03/2001 27/07/2001 27/11/2001 27/03/2002 27/07/2002 27/11/2002 27/03/2003 27/07/2003 27/11/2003 27/03/2004 27/07/2004 27/11/2004 27/03/2005 27/07/2005 27/11/2005 27/03/2006 27/07/2006 27/11/2006 27/03/2007 27/07/2007 27/11/2007 27/03/2008 27/07/2008 27/11/2008 27/03/2009 27/07/2009 27/11/2009 27/03/2010 27/07/2010 27/11/2010 27/03/2011 27/07/2011 27/11/2011 27/03/2012 27/03/1998 27/07/1998 27/11/1998 27/03/1999 27/07/1999 27/11/1999 27/03/2000 27/07/2000 27/11/2000 27/03/2001 27/07/2001 27/11/2001 27/03/2002 27/07/2002 27/11/2002 27/03/2003 27/07/2003 27/11/2003 27/03/2004 27/07/2004 27/11/2004 Euro/Tonne 27/03/2005 27/07/2005 27/11/2005 27/03/2006 27/07/2006 27/11/2006 27/03/2007 27/07/2007 27/11/2007 27/03/2008 27/07/2008 27/11/2008 27/03/2009 27/07/2009 27/11/2009 27/03/2010 27/07/2010 27/11/2010 27/03/2011 27/07/2011 27/11/2011 27/03/2012 France Italy Evolution of spot prices during 1988 2012: all the series show higher dispersion since the end of 2006 5 1. Futures markets: the agents Among the participants to the futures markets we have not only commercial hedgers, who use futures contracts to insure their crops or inventories against the risk of fluctuating prices (e.g. merchants, farmers, processors of agricultural commodities) one can also find non-commercial participants, who do not have involvement in the physical commodity trade - in contrast to commercial participants -. The non-commercial participants include: the speculators, who buy and sell futures contracts in order to gain a premium; the financial hedgers, as swap dealers, who are generally involved as commodity index traders (=CIT). 6
2. Research hypothesis The investors categories are related to the current discussion on whether increasing speculation is the culprit behind the rise in commodity prices and in their apparent volatility. What is important, when hedging, is not the absolute movements of the futures and the cash/spot prices but the relationship between them, i.e., the basis. It is clear that, if futures markets trends follow factors that are not related to fundamentals, one should expect changes in futures prices and spot prices to become divorced or less correlated. 7 2. Research hypothesis The implication of the above disassociation (between futures and the physical market) would necessarily be a reduction in the effectiveness of hedging spot price risk using futures markets. Therefore, after computing the hedging ratio and the hedging effectiveness measures, if one finds that hedging in futures markets is still a useful tool for risk management, then it means that both markets are still related and the financialization of futures markets has not broken that link. 8
3.a Data used in the analysis The analysis was performed using data from the London International Financial Futures and Options Exchange (LIFFE) for feed wheat contracts for the period 1988 until 2012 and spot prices from East Anglia (UK). In addition, we also analysed milling wheat contracts from the Marché à Terme International de France (MATIF) for the period 1998 to 2012 and spot prices for Rouen (France) and Bologna (Italy). For comparison purposes the same analysis is performed using the SRW wheat contract from the Chicago Board of Trade (CBOT) for the period 1988 to 2012. 9 3.b Methods used in the analysis While the economic theory behind hedging is still the minimum variance portfolio approach, the econometrics when estimating hedging ratios has evolved with the progress in time series econometrics: Lien and Tse (2002) provide an overview of relatively recent econometric methods to compute the hedging ratio. Myers and Thompson (1989) found that the model with the prices in levels or their returns provided a poor estimation of the ratio (since the variables are normally non-stationary). On the contrary the estimation of a model in price changes, provided reasonably accurate estimates (Myers and Thompson, p. 859). 10
3.b Methods used According to Sanders and Manfredo (2004) minimum variance measures of hedging effectiveness have not changed dramatically since Ederington's (1979) initial use of the correlation coefficient to measure the relationship between changes in cash and futures prices. In fact, they point out that hedging effectiveness is most commonly evaluated through an OLS regression of the change in cash price as a linear function of the change in the futures price (Leuthold, Junkus and Cordier, 1989, p. 92), where the resulting R 2 is the measure of hedging effectiveness (Hull, 2008, p. 85). 11 3.b Methods used We found that the series in levels were non-stationary. Therefore, they were expressed in differences (which were stationary). The traditional model to compute the hedge ratio (Carter, 1984): P = α + β + st P ft t where Pst is the change in the spot price, Pft is the change in the futures price, β is the hedging ratio ( α is the intercept of the regression and ε is the regression error) and the R 2 value gives the proportionate reduction of price risk attainable. Furthermore we also introduced dummy variables for the years 2006 until 2012, to evaluate whether the hedging ratios and their effectiveness had been affected by the described events in futures markets. ε 12
3.c Classes of hedging All the operators working along the wheat supply chain have a potential interest for hedging, but for everyone hedging has its own meaning. We have : The farmer s hedge, which considers only the farming season, i.e. the period in between the planting and the harvesting time (around 10 months intervals). Merchants and processors usually hedge their physical (spot) positions all over the year holding position in the futures market for much less than 10-11 months. The lengths assumed here are 30, 60 and 90 trading days ( shortterm hedge). The length of the hedge suitable for merchants and processors is shorter than for farmers and is not seasonally specified. It follows that the evaluation of the effectiveness for the hedges in question needs a separate computation comparing the dynamics of spot and futures prices for all the 30, 60 and 90 trading-day intervals available. Finally, as comparison with Carter (1984), hedges at very close range (quick hedge) that imply, approximately 7 trading days were also calculated. 13 4. Hedging outcome for farmers Results for the farmers show that when the entire sample is used, the performance of the European Exchanges, in terms of the variance reduction that farmers could have attained through hedging, is better than in the Chicago market. Thus, a US farmer hedging 39% of his wheat using the Chicago wheat futures would have reduced his price risk only by 14%; whilst the reduction using the European Exchanges ranged from 40% (for the case of spot prices from Bologna and the MATIF Futures Markets) to 73% (for the East Anglia spot prices and the LIFFE Futures Markets). 14
4. Hedging outcome for farmers It is important to note that the results using the entire sample mask dramatic changes in the hedging ratios since 2007 for all the cases. It is obvious that, if farmers had computed their hedging ratios based only on historical price information, the errors (and therefore losses from the hedging strategy) would have been significant. 15 4. The outcome for short-term hedges The hedging effectiveness of the short-term hedges are, in general, high and sometimes very high (with more than 75% of price risk reduction in several cases). The short-term hedges improve their performance with the lengthening of the hedge duration. This behaviour is common to all markets. The inclusion of the dummy variables to adjust the ratios (despite the fact that in many cases they are statistically significant) do not improve much the coefficient of determination of the short term hedging regressions, i.e., the changes in the hedging ratios add little to the reduction in the price risk. The value of the ratios obtained would indicate that for shorter periods than those used for the farmers hedging, the futures and the physical markets would be still closely related and therefore useful for hedging price risk. 16
4. The outcome for short-term hedges Note that when the physical market is more distant from the futures centre, as in the Italian case (i.e., spot price in Bologna and MATIF futures price based in France), the hedging effectiveness lowers. Thus, respect to Rouen prices, the basis absolute level between Bologna prices and MATIF prices is much higher due to greater transportation costs. Finally, as regards the 7 days hedges, the studied markets show that CBOT Exchange performs substantially better than the European Exchanges. Probably this is related to an issue of market liquidity. 17 5. Conclusions The results of the hedging effectiveness can provide an assurance (as an implicit test) that the increasing financialization has not made futures markets divorce from the physical markets. It is only for lengthy period hedges (such as farmers hedges) that appear to be some concerns of their effectiveness. The futures markets (the European ones included) are not only still efficient tool in risk management, but may also be a useful tool for food security purposes. The next step suggests to compute hedging ratios incorporating additional relevant information (e.g., supply and demand information). The main extension of the paper would need optimal hedge ratio estimates to change over time. 18
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