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The purpose of this paper is to identify the relationships between grain farm and farmer profiles and their respective choices to use forward pricing techniques and revenue protection crop insurance to manage risk.

An e-mail survey of Midwestern grain farmers elicited farmer demographic information, farm profile, risk attitudes and farmer use of forward pricing and revenue protection insurance. Responses regarding use of risk management tools were compiled as choices to use possible bundles of tools to account for simultaneous nature of the decision. Choices to use bundles of tools were used as the independent variable categories in a multinomial logit regression. Regressors were relevant data collected from the survey.

Farm size, using a market advisory service, and being a technology adopter are the most important factors in predicting risk management tool use by grain farmers. Farmers tend to use forward pricing and revenue protection insurance in combination. Large farms are more likely to use forward pricing tools.

Results provide researchers, extension professionals and risk management specialists with a current understanding of how farm and farmer characteristics relate to use of risk management tools. The authors also elaborate on findings to provide guidance for future risk management research.

The survey covered 9 Midwestern states and 648 grain farmers. The survey results update understanding of grain farmers’ risk management practices. The empirical approach treats risk management decisions to use available tools as simultaneous, which recent literature suggests is more appropriate than earlier approaches.

This chapter focuses on the common occurrence of wholesale electricity prices that fall below the cost of production. This “negative pricing” in effect represents payment to high-volume consumers for taking excess power off the grid, thus relieving overload. Occurrences of negative pricing have been observed since the wholesale electricity markets have been operating, and occur during periods of low demand, while generators are being kept in reserve for rapid engagement when demand increases (it is expensive and time-consuming to shut down generators and then restart them, so they are often kept in “spooling mode”). In such situations power production may temporarily exceed demand, potentially overloading the system. When the federal government began subsidizing the construction of wind generation projects, with regulations in place requiring transmission grids to accept all of the electricity produced by the wind generators, negative pricing became more frequent.

Selling goods overseas is more risky than selling goods in the home market.

The purpose of this paper is to analyze price decision-making through a practice-based approach. The paper investigates the micro-level practices used to arrive at sales price decisions.

In this study, a qualitative study approach is used to develop findings abductively. The data are gathered through an in-depth case study at two firms: semi-structured interviews, meeting observations, shadowing and pricing documents.

This paper finds that pricing is a collective decision-making process involving multiple actors across the organization. The case firms work on solving information, coordination and control problems to arrive at sales prices by enacting interlinked practices. Pricing is therefore neither a structure nor a single decision but a process consisting of multiple micro-level practices that enable firms to make pricing decisions.

This paper develops a practice-based approach to pricing that conceptualize the micro-level practices used to to make pricing decisions in the face of information, coordination and control problems. The paper is interdisciplinary and adds to the accounting literature and the market literature, which have tended to study pricing as a decision made by one decision maker, and not as an organizational process where multiple actors share, evaluate, interpret and coordinate information and decisions.

Agricultural markets for commodities have tended to be unstable with high variability in prices received by producers from year‐to‐year. These conditions have always made production planning very risky over time. For this reason and others, since 1933, the federal government has supported commodity prices in one fashion or another at or near break even. Support programs have put pressure on the annual federal deficits and subsequently have added to the national debt. This paper investigates the use of private agricultural options contracts as a price risk management tool. Use of put options was compared for four commodities to the use of forward pricing, the use of cash prices at harvest and the use of futures as commodity pricing strategies. Private put options were found to be a useful alternative to the use of government prices upports in some commodity situations. The paper suggests that the use of option contracts provides additional flexibility in price risk management and in dealing with uncertainty. This knowledge was found to be especially useful in light of current cuts in federal price supports in current federal budgeting activity.

The forward curve dynamics in the Nordic electricity market is examined. Six years of price data on futures and forward contracts traded in the Nordic electricity market are analysed. For the forward price function of electricity, we specify a multi‐factor term structure models in a Heath‐Jarrow‐Morton framework. Principal component analysis is used to reveal the volatility structure in the market. A two‐factor model explains 75 per cent of the price variation in our data, compared to approximately 95 per cent in most other markets. Further investigations show that correlation between short‐ and long‐term forward prices is lower than in other markets. We briefly discuss possible reasons why these special properties occur, and some consequences for hedging exposures in this market.

This paper aims to analyze the statistical characteristics of changes in property forward prices. As highlighted in a survey conducted at the MIT Center for Real Estate in 2006, the relatively weak understanding in their prices is one of the most important barriers in their use. In this context, the analysis of the forward price term structure is essential. Do the short- and long-term forward prices behave similarly? Do property derivatives behave like other derivative assets or other related assets? This study also investigates the lead–lag relationship between spot and forward returns for different maturities.

Using four years and nine months of data on the UK Investment Property Databank (IPD), all property total return swaps are examined. We strip the swaps into their forwards and study their statistical characteristics (the first four moments and their autocorrelation levels). The relationships among the forward contracts, the underlying asset (IPD index and IPD unsmoothed) and other assets (risk-free rate, listed real estate) are explored. Using the Yiu et al. (2005) methodology, the lead–lag relationship between the spot and the forwards is assessed.

The index appears to be significantly less volatile and less efficient, in terms of correlation than its own derivative contracts. Moreover, changes in forward prices are leading indicators of the IPD index. Their risks tend to converge with the implied volatility of the REIT’s operating asset but without being affected by the general stock market risks. Regarding the forward price–discovery function, investors should collect information not only from the spot market but also, maybe primarily, from the derivative market.

In this paper, we use a never-exploited database that is relative to the quotes of the UK IPD swaps. It is the first attempt to analyze the statistical characteristics of their changes. Our results show that these prices are clearly superior to the spot series, in terms of risks but without behaving affected by the tyranny of the past values. These findings may conduct to consider new methods to unsmooth current real estate indices. Characterized by a strong sensitivity to the changes in the information set, property derivative-based indicators should lead to increased efficiency in the spot market.

Midwest Independent Transmission System Operator, Inc. (MISO) is a nonprofit regional transmission organization (RTO) that oversees electricity production and transmission across 13 states and 1 Canadian province. MISO also operates an electronic exchange for buying and selling electricity for each of its five regional hubs.

MISO oversees two types of markets. The forward market, which is referred to as the day-ahead (DA) market, allows market participants to place demand bids and supply offers on electricity to be delivered at a specified hour the following day. The equilibrium price, known as the locational marginal price (LMP), is determined by MISO after receiving sale offers and purchase bids from market participants. MISO also coordinates a spot market, which is known as the real-time (RT) market. Traders in the RT market must submit bids and offers by 30minutes prior to the hour for which the trade will be executed. After receiving purchase and sale offers for a given hour in the RT market, MISO then determines the LMP for that particular hour.

The existence of the DA and RT markets allows producers and retailers to hedge against the large fluctuations that are common in electricity prices. Hedge ratios on the MISO exchange are estimated using various techniques. No hedge ratio technique examined consistently outperforms the unhedged portfolio in terms of variance reduction. Consequently, none of the hedge ratio methods in this study meet the general interpretation of FASB guidelines for a highly effective hedge.