NCCC-134
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The Value of Public Information in Storable Commodity Markets: Application to the Soybean Market
Christophe Gouel
Year: 2018
 

Abstract

This study provides a framework to estimate the potential effects and benefits of the provision of market information in storable commodity markets. This framework is applied to the case of production forecasts for the soybean market. A rational expectations storage model of the global soybean market accounting for both inter-annual and intra-annual market dynamics is built. Shocks that occur between planting and harvesting affect the size of the potential harvest. Estimates of the size of these shocks are reported publicly, and affect the market equilibrium through adjustments to stock levels. By varying counterfactually the observability of seasonal shocks, we can estimate the efficiency gains related to the availability of advance information. They are equivalent to 2% of storage costs; the reduction of stock levels being the main channel explaining the welfare gains. The presence of advance information has a limited effect on inter-annual price volatility but redistributes price volatility during the season, increasing it just before harvest when almost all news has been received and stocks are tight, and decreasing it after harvest. The effect of news shocks is stronger on higher-order moments of the distribution with a strong decrease in skewness and kurtosis related to the lower frequency of price spikes.

 
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Do Livestock Markets Still Value USDA Information?
Berna Karali, Olga Isengildina-Massa, and Scott H. Irwin
Year: 2018
 

Abstract

The informational value of U.S. Department of Agriculture (USDA) livestock reports for cattle and hogs futures markets is analyzed to determine potential impact of increased market concentration seen in the livestock industry over the last three decades. Both market surprises, the difference between the USDA’s and private analysts’ forecasts, and price reactions to those surprises are analyzed for possible changes over time using sub-period analysis and rolling-window regressions. The results suggest that while the market surprise component of the reports decreased over time for both Cattle on Feed and Hogs and Pigs reports, the price reaction to those surprises increased in the early 2000s, suggesting that USDA reports still provide valuable information to market participants beyond private analysts’ expectations.

 
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Forecasting Crop Prices using Leading Economic Indicators and Bayesian Model Selection
Yu Wang and Jeffrey H. Dorfman
Year: 2018
 

Abstract

Corn, wheat and soybeans are very important to the US agricultural sector as the main sources of many farmers’ income. Thus, forecasting the prices of these three crops is important. When considering model specification of crop price forecasting models, this paper focuses on potential benefits from including leading economic indicators variables, both those clearly related to agriculture such as the crude oil price and interest rate and those not clearly related such as the purchasing managers index or the S&P500 stock price index. To do this, our paper tests whether leading economic indicators can be used to improve the forecasts of corn, wheat, and soybean future prices. We take a Bayesian approach to estimate the probability that a set of leading indicators belong in the forecasting model where specification uncertainty is explicitly modeled by assuming a prior distribution over a very large set of models. Model specifications considered vary by different lag lengths for leading indicators and crop prices as well as which variables are included at all. We apply this method to corn, soybean and wheat monthly spot price data from 1985 to 2016. The results show that several leading economic indicators appear to be useful for forecasting crop prices.

 
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How Well Do Commodity ETFs Track Underlying Assets?
Tyler Neff and Olga Isengildina-Massa
Year: 2018
 

Abstract

Exchange Traded Funds are growing in popularity and volume, however academic literature related to their performance is limited. This study analyzes how well the CORN, WEAT, SOYB, USO, and UGA commodity ETFs track their respective futures assets during the period of January 2012 to October 2017. Results indicate that tracking error is small on average, however CORN shows average excess returns significantly smaller than zero. The CORN, WEAT, USO, and UGA ETFs are found to move less aggressively than the respective asset baskets they track. While errors were small on average, large tracking errors were present across ETFs. The size of errors was affected by large price moves, as well as seasonality on a monthly and yearly level. USDA reports impacted the size of errors for CORN, WEAT and SOYB while EIA reports had no impact on error size. The mispricing analysis concluded that CORN and SOYB trade at a discount to Net Asset Value on average while WEAT trades at a premium.

 
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Wholesale Beef Futures Contract
Robert S. Thompson, Ardian Harri, Joshua G. Maples, and Eunchun Park
Year: 2018
 

Abstract

In this research, we develop methods to derive a price series that is theoretically sound for a hypothetical futures contract. We extend a futures valuation model to provide a valuation for a hypothetical futures contract. One such hypothetical contract that has been suggested as a possible solution to recent problems in live cattle futures is the wholesale beef futures contract. We present two different methods for generating the term structure of the hypothetical futures contract. The results show that both methods perform very well. The methods developed here are tested for validity using futures markets for hogs and cattle and are found similar in accuracy to a futures valuation model for existing futures. We also use the derived price series for the hypothetical wholesale beef futures contract to evaluate and compare its effectiveness as a risk management tool to the existing live cattle futures.

 
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The Value of Public Information: Market Microstructure Noise and Price Volatility Spillovers in Agricultural Commodity Markets
Siyu Bian, Teresa Serra, and Philip Garcia
Year: 2018
 

Abstract

After 2013, major grain-related USDA announcements have been rescheduled to be released at 11:00 am CDT. Such a change granted researchers a great chance to study market volatilities and spillovers react to significant USDA information on real time. Also, with new statistical methods, researchers now can separate efficient volatility from noise volatility. In this paper, we adopt a recently developed method, which is called Markov Chain estimator (MC estimator), to study intraday volatility and volatility spillover between corn and soybean futures during USDA announcement days. Our results suggest that volatilities in both corn and soybean would response to USDA announcements immediately after the news being published. The elevated level of volatilities would not settle down within the first hour after announcements. Also, more persistent spillover occurs at equilibrium level, which is measured by efficient return spillover, than at noise level, which is measured by noise return spillovers.

 
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Organic Wheat Prices and Premium Uncertainty: Can Cross Hedging and Forecasting Play a Role?
Tatiana Drugova, Veronica F. Pozo, Kynda R. Curtis and T. Randall Fortenbery
Year: 2018
 

Abstract

Growers considering organic conversion or maintaining current organic wheat production face uncertainties due to large variations in organic wheat prices over time. In this study, the risk associated with organic premiums is evaluated using 5% VaR, and the probability that the additional costs of producing organic wheat will not be covered is calculated. To reduce the uncertainty associated with organic wheat prices, the possibility of cross hedging using conventional wheat futures is examined, as well as the ability of futures to forecast the organic premium. This is done by estimating an optimal hedge ratio using cointegration that at the same time identifies long-run and short-run price relationships between conventional and organic wheat. The data used are monthly wheat prices from USDA AMS, USDA ERS and the Commodity Research Bureau between January 2008 and July 2017. Since organic prices are not completely observed, three methods are used to impute missing values and add robustness to the analysis. Results provide some evidence that conventional futures can be used to cross hedge organic wheat price risk, but results are dependent on the method used to impute the missing values. Similarly, it is found that there is a long-run equilibrium relationship between organic wheat prices and conventional wheat futures prices. In addition, futures prices contain some information useful in predicting organic prices in the short run.

 
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Dynamic Price Discovery of U.S. Fed Cattle Markets: Identifying Short Run Shock Effects through rolling ECM
Hernan A. Tejeda, Man-Keun Kim and Jeffrey Wright
Year: 2018
 

Abstract

This study re-examines the price discovery process of fed cattle markets by taking into account the dynamic effects from unexpected shocks to fed cattle markets. That is, we investigate whether ensuing shocks to the industry, specifically from BSE outbreaks, resulted in any temporal or permanent changes in the reference market(s) (futures market) obtained from the price discovery process. Using weekly weighted average fed cattle cash prices for Nebraska and weekly average live cattle CME futures prices, from May 2001 to January 2017, we construct forward growing samples. The first sample is from May 2001 until four weeks before the first BSE outbreak, and the second sample onwards sequentially incorporates four more weeks of data until January 2017. We model these samples as rolling bivariate Error Correction Models (ECM) and test whether the futures prices hold as the reference market during the three U.S. BSE outbreaks (December 2003, June 2005, and March 2006). Findings are that during and following the first and second BSE outbreaks, the cash market price became the (new) reference price. During this period, the U.S. experienced a ban of beef exports, in particular to its largest markets Japan and South Korea. The futures market became the reference price (again) only a month before the export ban was partially lifted. In addition, we found no changes to the reference market in the thirdBSE outbreaks; when no export bans occurred. Thus unexpected shocks that produced significant impacts, for example, export bans on the market, were accompanied by a change in reference market.

 
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Cost of Immediacy during Large Price Movements: Evidence from Corn Futures Market
Xinyue He, Teresa Serra and Philip Garcia
Year: 2018
 

Abstract

Recent years have witnessed growing presence of intra-day large price movements in corn futures market. This paper focuses on the behavior of bid-ask spread, a gauge for the cost of immediacy, during various large price movements featuring dramatic price decline/increase in a short time period in corn futures market, from 2014 to 2017. We specify a vector autoregressive model (VAR) to model the dynamics in the top of the book and use impulse response functions (IRFs) to examine the dynamic behavior of the spread. Our results reveal a resilient spread which is expected to narrow substantially within 5 – 20 seconds and completely revert back to normal state within 15 - 40 seconds once being shocked to widen. Along with the small average magnitude of bid-ask spread, our results suggest that corn futures market does not appear to experience significant liquidity deterioration over highly volatile periods, and that traders and hedgers who demand immediate execution can expect to do so at a reasonably and consistently low cost throughout the large price movement horizon.

 
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Quantifying the Announcement Effects in the U.S. Lumber Market
Zarina Ismailova, Shishir Shakya, Xiaoli L. Etienne, and Fabio Mattos
Year: 2018
 

Abstract

The impact of new information from public reports has been widely investigated in many commodity markets, but little attention has been paid to the lumber market. In this paper, we examine the impact of two housing market reports, namely the New Residential Construction (Housing Starts) and the New Residential Sales reports, on the U.S. lumber futures market. Our results suggest that the housing starts report indeed affect lumber market volatility, while the New Residential sales report exerts a minor impact on lumber price volatility. We further find that the effect of the two reports on volatility differs depending on the level of inventory and nature of the news. When the level of inventory is low, larger-than-expected housing starts has the largest effect on lumber volatility. During periods of abundant inventory, lower-than-expected housing starts increases the volatility most. For the new home sales reports, we find that while lower-than-expected sales do not affect the volatility of lumber prices, larger-than-expected sales do increase the volatility.

 
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Are Corn Futures Prices Getting “Jumpy”?
Anabelle Couleau, Teresa Serra, and Philip Garcia
Year: 2018
 

Abstract

Corn futures markets have experienced increased intraday price jumps which have been blamed on public information shocks and the reduced trading latency brought by electronic trading. This paper contributes to shed light on this issue by assessing intraday jumps in the corn futures nearby transaction prices from 2008 to 2015. We use a nonparametric jump test and a variance analysis to estimate jump risk. Our results suggest that the real-time trading of major USDA reports has substantially increased the frequency and the magnitude of jump risk. In contrast, results suggest that the electronic platform along with reduced latency may have increased liquidity and prevented price spikes on non-USDA report days.

 
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Impacts of Railroad Costs on Kansas Wheat Basis
Anton Bekkerman and Mykel Taylor
Year: 2018
 

Abstract

Numerous studies and their results have maintained a general consensus that variation in transportation costs between a central futures market and a local delivery market is a main determinant of basis. However, surprisingly few empirical estimates exist to quantify the relationship between variation in transportation costs and basis. Our work is the first to directly model elevator-level grain pricing behavior (i.e., basis) and the transportation costs that those elevators face. We link elevator-specific basis data with actual rail costs incurred by those elevators, and then add elevator-level characteristics to control for numerous factors that can impact pricing behavior. These data are then use to empirically estimate and quantify the degree to which transportation costs affect elevators' pricing behaviors. We find that, as predicted by theory, increases in elevators' transportation costs results in weakening basis at those elevators, and that this is exacerbated in periods of higher expected rail costs and higher expected rail cost variability. However, our results also indicate that change in transportation costs are far from passed through to producers on a one-to-one basis and that variation in local spot market conditions and futures prices contribute more to elevators' price-setting behaviors than changes in rail costs.

 
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Market Power and Farm-Retail Price Transmission: The Case of U.S. Fluid Milk Markets
Charng-Jiun Yu and Brian W. Gould
Year: 2018
 

Abstract

In this paper we seek to understand the impact of market competitiveness on the degree of asym-metric price transmission and associated welfare implications. We estimate a kinked Almost Ideal Demand System for fluid milk products in 18 U.S. metropolitan areas. By conducting an asymmet-ric price transmission test, we find that cities with less competitive food retailing tend to exhibit asymmetric price transmission. The degree of price asymmetry and associated welfare loss are decreasing in the market competitiveness. Our welfare analysis suggests that the welfare loss due to asymmetric price transmission is large in terms of the percentage of milk expenditures. The potential is for substantially higher future welfare loss given the ongoing consolidation in food retailing industry.

 
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