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3 Table 1. Coefficient of correlation between the 2 out of 4 livestocks' nearby prices on CME futures markets, of live Cattle, Feeder Cattle, Live Hog, Frozen Pork Bellies from 1984 to 1994 Chicago Mercantile Exchange. 63
4 Table 2. Coefficient of correlation, means, standard deviation, maximum R: Coefficient of correlation between cash prices and Live Cattlle's nearby prices on CME CME: Chicago Standard Deviation Max: Maximim Min: Minimum. 64
5 and minimum based on weekly data since 1984 to 1993
6 Table 3. Coefficient of correlation, means, standard deviation, maximum R: Coefficient of correlation between cash prices and Live Cattle's nearby prices on CME CME: STD: Standard Deviation Max: Maximim Min: Minimum. 66
7 and minimum based on weekly data since 1984 to 1993
8
9 Fig. 1. The relationship between each differences of two Standard Deviations and each coefficients of correlations, which are 27 commodities (Cattle, Carcasses, Trimmings) in the U.S. from 1984 to The differences of two Standard Deviations: Standard Deviation of cash prices minus Standard Deviation based on 27 commodities of Cattle, Carcasses, Trimmings in the U.S. Fig. 2. The relationship between each differences of two Standard Deviations and each coefficients of correlations, of 33 commodities (Beef Primals and Boxed Beef) in the U.S. from 1984 to The differences of two Standard Deviations: Standard Deviation of each prices minus Standard Deviation based on 33 commodities of Beef Primals and Boxed Beef in the U.S.
10 Table 4. Marketing numbers of cattle from feedlots and numbers of cattle slaughtered in the U.S. Unit: 1,000 heads This table is based on data from 13 states. Arizona, California, Colorado, Idaho, Illinois, Iowa, Kansas, Minnesota, Nebraska, Oklahoma, South Dakota, Texas, Washington. Table 5. Market share of big meat packers of fed steers and heifers slaughtered from 1988 to 1994 in the U.S. Unit: 70
11 Table 6. Percent of futures open interest represented by hedgers and speculators on CME Live Cattle market. which are based on monthly data from January 1993 to March 1994_ thereafter weekly data
12 Table 7. Traders' positions in CME Live Cattle as a percentage of total interest and the number of traders holding positions futures and futures-equivalent options from April 5 to July 12 in 1994, which are based on weekly data
13 Table 8. Funds, Packers and Feeders' All-futures-combined positions as a percentage of All-futurescombined open interest in CME Live Cattle Futures and future equivalent options, which are based from March 7 to June 13 in 1995 Table 9. Coefficient of correlation (R) between steers cash price and Live Cattle nearby price on CME futures market in U.S. from 1990 to 1995
14 Table 10. Cash price of Steers, nearby price and distant price of CME Live Cattle and historical volatility based on data from January to October S.D.: Standard Deviation, 20D-HV: historical volatility caluated from 20 day's historical data 74
15 Table 11. The price of nearby two contract month at expiration date on CME's Live Cattle futures markets from 1990 to 1995 CME: Chicago Mercantile Exchange 75
16
17 Table 12. Relation between supply and demand of meat in Japan from 1988 to 1993 (Date in 1993/Date in 1988)
18 Fig. 3. The relationship between (Import volume of beef)/(domestic consumption of beef) and Import volume of beef for each year from 1988 to 1993 in Japan.
19 7) Donald GC, Paul HH. Commodity marketingfrom a producer's perspective Interstate Publishers, Inc. Danville ) James FGJr., James MS. Options, futures and business risk. Journal of Futures Markets, 2: ) John H. Introduction to futures and options 13) John WH. A report on the systematic down ward bias in live cattle futures prices. The Journal of Futures Markets, 1: ) Joseph BD. How CFTC's regulatory work benefits the cattle industry Commodity Futures Trading Commision. Washington ) Kevin LK, Marvin LH. Cash settlement as an alternative settlement mechanism for the live hog futures contract. The Journal of Futures Markets, 14: ) Lennart APJr., James G. The systematic downward bias in live cattle futures: an evaluation. 1) Brian BW, Robert WK. Analysis of spreads in The Journal of Futures Markets, 1: agricultural futures. The Journal of Futures Markets, 15: ) Marvin LH, Dennis DD. Hedging wholesale 2) Charles MO, Paul LF. Futures or cash: which meat prices: analysis of basis risk. The Journal of Futures Markets, 2: market leads live beef cattle prices?. The Journal of Futures Markets, 5: ) Chicago Mercantile Exchange. Managing purchase prices Chicago Mercantile Ex- change. Chicago ) Chicago Mercantile Exchange. Ten strategies Chicago Mercantile Exchange. Chicago ) Chicago Mercantile Exchange. CME agricultural spread charts Chicago Mer- cattle/feeder cattle report Moore Re- 21) Moore Research Center, Inc. Historical live cantile Exchange. Chicago search Center Inc. Oregon ) Commodity Futures Trading Commission.The live cattle futures market, April to June 1994: review of market fundamentals and analysis of large trader positions and actibity Commodity Futures Trading Commision. Washington
20 24) Price Analysis System. Meat price relationships-a guide to etstimating seasonal price moves in livestock, meat and poultry prices Price Analysis Systems. Memphis Forecasting the nearby basis of live cattle. The Journal of Futures Markets, 14: ) Sparks Companies, Inc. Beef futures-new tools for the Japanese beef industry ) Robert WK, Gerald DG. The performance of Sparks Companies, Inc. Memphis live cattle futures as predictions of subsequent 33) Stephen EM, Dawson BL. Alternative techniques for cross-hedging wholesale beef spot prices. The Journal of Futures Markets, 3: prices. The Journal of Futures Markets, 2: 27) Robert DW, Aniruddha B. Cash price variation in the live beef cattle market: the casual role of futures trade, The Journal of Futures Markets, 2: ) Shi-miin L, Wade BB, Charles MO, Paul LF.
21 A Study on the Use of Futures Markets to Manage Price Risk of Cattle and Beef Industry in the U.S. and Japan Kouichi KAKU National Institute of Animal Industry, Tsukuba Norin Kenkyu Danchi, Ibaraki-ken 305 I investigated how the CME (Chicako Mercantile Exchange) Live Cattle Futures have affected cattle and beef producers in the U.S. and how Japan beef futures contracts would function in the future. (1) The date for 4 livestock commodity futures on the CME, which are live cattle, feeder cattle, live hog and frozen pork bellies from 1984 to 1994 were esed. Coefficients of correlation for each year betweem the two out of the two out of the four livestock fututes commodities were varied. Therefore, inter-commodity spreads could be a risky technique. (2) The data from 1984 to 1993 on 60 types of commodities like cattle and beef were used to calulate the basis between steer cash prices and CME live cattle nearby prices. The high coefficients of correlation between cash prices and nearby prices were larger than those of the basis standard deviations of cash prices. Therefore, when you shift cash price risk to the basis price risk, the risk would be smaller. (3) On CME Live Cattle Futures market from January 1993 to June 1994, the percent of futures open interest represented by hedgers is around 80% and percent by speculators is around 20%. Therefore, the CME Live Cattle Futures market in the U.S. is nowadays not as much a speculative market as a hedging market, where big meat pachers and feeders participate in to manage price risk. (4) Coefficients of correlation between steer cash prices and live cattle nearby prices on the CME futures markets in the U.S. from 1990 to 1995 was 0.94 for 1,450 examined days. Coefficients of variation during this period were 7.39% for cash prices, 6.75% for nearby prices, and 5.41% for distant futures prices. Therefore, cash prices varied the greatest. From January 1990 to October 1995, I suggest that Live Cattle Futures prices have a price smoothing function to steer cash prices. (5) In Japan, The Tokyo Grain Exchange is considering futures contracts based on the Australian grass-fed chilled, full-set as hedging tools. If these is a beef futures market in Japan, many different domestic segments, i.e., beef producers, importers, restaurants, meat packers, could lock in their selling prices. Consumers could enjoy stable beef prices using a price smoothing function of the beef futures market. Anim. Sci. Technol. (Jpn.) 68 (1): 61-81, 1997 Key words: Basis, Cattle and beef, CME Live Cattle Futures, Hedging tools, Price risk Anim. Sci. Technol. (Jpn.) 68 (1):
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