1,198 research outputs found
Are Corn and Soybean Options Too Expensive?
A growing body of recent evidence suggests that premiums for financial options might be too high. For agricultural options, market participants often make similar claims, however there is very limited scientific literature to prove or disprove such claims. This research investigates the efficiency of corn and soybean options markets by directly computing trading returns. Time effects on market efficiency are also investigated. When the sample period is considered as a whole, risk adjusted returns indicate that no profits can be made by taking either side of the corn or soybean options markets. However, when time effects are analyzed, corn calls appear to have provided excess returns during the 1998--2005 period. This result do not appear to be driven by movements in the underlying futures, since similar differences were not found for corn puts. Based on the evidence presented here, corn puts and soybean options would constitute fairly-well priced insurance tools. Further research should investigate the causes of corn call returns.corn, soybeans, options markets, mispricing, trading returns, market efficiency, Crop Production/Industries, Marketing,
Has the Performance of the Hog Options Market Changed?
The hog option contract has served as a risk management tool for the pork industry for more than 20 years. However, very limited information exists about how this market behaves and how it was affected by the contract redesign of 1996. This paper evaluates the efficiency of hog options markets comparing its pricing function during the live hog contract period to the lean hog contract period. Trading returns are computed and adjusted for risk using the Sharpe ratio and the Capital Asset Pricing Model. When the whole sample period is analyzed, results indicate that no profits can be made by taking either side of the hog options markets. However, analyzing the live and the lean hog contracts separately, some evidence suggest that opportunities for speculative profits existed during the live hog contract period. These conclusions are not driven by the extreme price movements in the futures price occurred during late 1998. Further research should investigate whether general futures price movements are responsible for these large returns.Marketing,
2007 U.S CORN PRODUCTION RISKS: WHAT DOES HISTORY TEACH US?
Financial Economics, Production Economics, Risk and Uncertainty,
Understanding USDA Corn and Soybean Production Forecasts: An Overview of Methods, Performance and Market Impacts
Agricultural Finance,
A Reality Check on Technical Trading Rule Profits in US Futures Markets
This paper investigates the profitability of technical trading rules in US futures markets over the 1985-2004 period. To account for data snooping biases, we evaluate statistical significance of performance across technical trading rules using White's Bootstrap Reality Check test and Hansen's Superior Predictive Ability test. These methods directly quantify the effect of data snooping by testing the performance of the best rule in the context of the full universe of technical trading rules. Results show that the best rules generate statistically significant economic profits only for two of 17 futures contracts traded in the US. This evidence indicates that technical trading rules generally have not been profitable in US futures markets after correcting for data snooping biases.Marketing,
Understanding USDA Corn and Soybean Production Forecasts: Methods, Performance and Market Impacts over 1970 - 2005
The purpose of this report is to improve understanding of USDA crop forecasting methods, performance and market impact. A review of USDA’s forecasting procedures and methodology confirmed the objectivity and consistency of the forecasting process over time. Month-to-month changes in corn and soybean production forecasts from 1970 through 2005 indicated little difference in magnitude and direction of monthly changes over time. USDA production forecast errors were largest in August and smaller in subsequent forecasts. There appeared to be no trend in the size or direction of forecast errors over time. On average, USDA corn production forecasts were more accurate than private market forecasts over 1970-2005, with the exception of August forecasts since the mid-1980s. The forecasting comparisons for soybeans were somewhat sensitive to the measure of forecast accuracy considered. One measure showed that private market forecasts were more accurate than USDA forecasts for August regardless of the time period considered. Another measure showed just the opposite. As the growing season progresses the difference in the results across the two measures of forecast accuracy diminished, with USDA forecast errors in soybeans about equal to or smaller than private market errors. USDA corn production forecasts had the largest impact on corn futures prices in August and recent price reactions have been somewhat larger than historical reactions. Similar to corn, USDA soybean production forecasts had the largest impact on soybean futures prices in August with recent price reactions appearing somewhat larger than in the past. Overall, the analysis suggests that over the long-run the USDA performs reasonably well in generating crop production forecasts for corn and soybeans.Agricultural Finance,
IMPROVING THE RELEVANCE OF RESEARCH ON PRICE FORECASTING AND MARKETING STRATEGIES
Agricultural economists' research on price forecasting and marketing strategies has been used little by those in the real world. We argue that fresh approaches to research are needed. First, we argue that we need to adopt a new theoretical paradigm, noisy rational expectations. This paradigm suggests that gains from using price forecasting models with public data or from using a marketing strategy are not impossible, but any gains are likely to be small. We need to conduct falsification tests; to perform confirmation and replication; to adjust research to reflect structural changes, such as increased contracting; and always to conduct statistical tests. We also provide a modest agenda for changing our research and extension programs.Demand and Price Analysis, Marketing,
THE EFFECTS OF FUTURES TRADING BY LARGE HEDGE FUNDS AND CTAS ON MARKET VOLATILITY
This study uses the newly available data from the CFTC to investigate the market impact of futures trading by large hedge funds and CTAs. Regression results show that there is a positive relationship between the trading volume of large hedge funds and CTAs and market volatility. However, a positive relationship between hedge fund and CTA trading volume and market volatility is consistent with either a private information or noise trader hypothesis. Three additional tests are conducted to distinguish between the private information hypothesis and the noise trader hypothesis. The first test consisted of identifying the noise component exhibited in return variances over different holding periods. The variance ratio tests provide little support for the noise trader hypothesis. The second test examined whether positive feedback trading characterized large hedge fund and CTA trading behavior. These results suggest that trading decisions by large hedge funds and CTAs, although influenced in small part by past price changes, are not driven by past price changes. The third test consists of estimating the profits and losses associated with the open interest positions of large hedge funds and CTAs. This test is based on the argument that speculative trading can only be destabilizing if speculators buy when prices are high and sell when prices are low, which in turn, implies that destabilizing speculators lose money. Across all thirteen markets, the profit for large hedge funds and CTAs is estimated to be just under $400 million. This implies that the trading decisions are likely based on valuable private information. Overall, the evidence presented in this study suggests trading by large hedge funds and CTAs is based on private fundamental information. These findings imply large hedge funds and CTAs benefit market efficiency by bringing valuable, fundamental information to the market through their trading.hedge fund, commodity trading advisor, volatility, market efficiency, futures markets, Marketing,
Market Instability in a New Era of Corn, Soybean, and Wheat Prices
grain, price, increase, trend, Demand and Price Analysis, Marketing, Q11, Q13,
Market Efficiency and Marketing to Enhance Income of Crop Producers
Recent changes in farm policy have renewed interest in using marketing strategies based on futures and options markets to enhance the income of field crop producers. This article reviews the literature surrounding the dominant academic theory of the behavior of futures and options markets, the efficient market hypothesis. The following conclusion is reached: while individuals can beat the market, few can consistently do so. This conclusion is consistent with Grossman and Stiglitz's model of market efficiency in which individuals who consistently earn trading returns have superior access to information or superior analytical ability. One implication is that, with few exceptions, the crop producers who survive will be those with the lowest cost of production since efforts to improve revenue through better marketing will have limited success. There do appear to be some successful marketing strategies. One is to base storage decisions on when a producer harvests the crop relative to the national harvest of the crop. Another is to base storage decisions on whether the current basis exceeds the cost of storage, and then to use hedging to assure an expected positive return.Market Efficiency, marketing strategies, futures, options
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