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The Paris Agreement (PA) opens for parties to use Internationally Transferred Mitigation Outcomes (ITMOs) for implementing their Nationally Determined Contributions (NDCs). This paper analyzes spot, forward and options market trading of ITMOs up to the end of the first PA trading period (2030), given uncertainty about (1) the fulfillment of parties’ NDC targets, and (2) the existence and functioning of the ITMO markets, as ITMO banking beyond 2030 is not allowed. Closed-form solutions are derived for options trading and its welfare impacts given uniform distributions of parties’ uncertainties about fulfilling their individual commitments. Access to call options for late ITMO purchases leads to larger forward ITMO sales or less current mitigation, help parties stay in NDC compliance in 2030, brings early revenue to low-income parties, and is welfare enhancing for all parties. Access to put options for late ITMO sales is less important, and will not be used when put options are not subsidized and parties are risk neutral. The ITMO markets can be enabled by donor-provided climate finance. Effectively functioning ITMO markets can dramatically reduce parties’ costs of achieving their NDCs, and could increase parties’ ambitions, then also reducing global greenhouse gas emissions under the agreement.

We examine the reductions in electricity procurement costs that can be secured when gain-sharing regulation is employed to induce a regulated load serving entity (LSE) to undertake forward contracting despite associated political risk. We identify arguably plausible conditions under which a modest degree of gain sharing can induce an LSE to undertake forward contracting that substantially reduces the LSE’s procurement costs, to the benefit of retail consumers.

The CIF NOLA “river market” represents an important but opaque forward market that serves Gulf exporters and elevators. CIF NOLA bids function similarly to traditional forward contracts; however, like a futures market, firms can offset their forward contractual obligations by offsetting positions in a liquid off-exchange paper market. Analysis shows grain sellers pay a risk premium for fall harvest delivery contracts. However, outside of fall harvest, contract liquidity, coupled with a good institutional balance of long and short market participants, mostly removes the pricing bias commonly found in farmer forward contracting in corn and soybeans.

We develop a theoretical model of optimal hedging that nests expected utility and expected target utility theories. We use this model to characterize optimal hedging with and without reference price dependence. The model’s theoretical predictions are tested with a unique database consisting of every forward contract written with a major grain marketing firm by Iowa corn producers over a fiveyear period. Our results suggest that a current December futures price higher than a reference price triggers hedging activity. A likely candidate for producers’ reference price is a rolling average of the current futures price. We then use trading activity implied by the producers to determine if they benefit from the way they hedge. The evidence is mixed. Finally, we compare the producer forward contract data to the only publicly available data on producer hedging: The Commodity Futures Trading Commission Disaggregated Commitment of Traders Report (DCOT) for Short Hedgers. A hedge ratio constructed from the open interest in new futures contracts of the DCOT report is highly correlated with the producer hedge series in the Iowa data, providing evidence that DCOT data represent farmers’ hedging behavior reasonably well. This work has important implications for future research that uses the DCOT data, and provides new evidence about producers’ hedging behavior that marketing specialists and extension agents can use to enhance their educational efforts related to risk management.

Summary This paper presents a risk‐constrained programming approach to solve a retailer's medium‐term planning problem. A retailer tries to maximize its profit via determining the optimal price offered to the customers as well as optimal strategy of participating in futures and pool markets. The uncertainty of pool prices is modeled by an envelope‐bound information‐gap model. Another source of uncertainty in this problem is the clients' demand, which is considered via a scenario generation method. The proposed method is formulated as a bi‐level stochastic programming problem based on the information‐gap decision theory. The Karush–Kuhn–Tucker optimality conditions are used to convert the bi‐level problem into a single‐level robust optimization problem. The performance of the proposed method is demonstrated using a case study of the New England market, and results are discussed. Copyright © 2015 John Wiley & Sons, Ltd.

Whilst the benefits of forward contracting for goods and services have been extensively researched in terms of mitigating market power effects in spot markets, we analyse how the risk in spot price formation induces a counteracting premium in the contract prices. We consider and test a wide-ranging set of propositions, involving fundamental, behavioural, dynamic, market conduct and shock components, on a long data set from the most liquid of European electricity forward markets, the EEX. We show that part of what is conventionally regarded as the market price of risk in electricity is actually that of its underlying fuel commodity, gas; that market power has a double effect on prices, insofar as it increases spot prices and induces a forward premium; that oil price sentiment spills over and that the premium reacts to scarcity and the higher moments of spot price uncertainty. We observe that considerations of the scale and determinants of the forward premium are at least as important as the market power effects in spot market price formation when evaluating the efficiency of wholesale power trading.

Factors affecting the adoption of crop insurance, forward contracting, and spreading sales are analyzed using multivariate and multinomial probit approaches that account for simultaneous adoption and/or correlation among the three risk management adoption decisions. Our empirical results suggest that the decision to adopt crop insurance, forward contracting, and/or spreading sales are correlated. Richer insights can be drawn from our multivariate and multinomial probit analysis than from separate, single-equation probit estimation that assumes independence of adoption decisions. Some factors significantly affecting the adoption of the risk management tools analyzed are proportion of owned acres, off-farm income, education, age, and level of business risks.

Risk management education has been a focus of U.S. farm policy since 1996. In support of significant ongoing United States Department of Agriculture (USDA) educational efforts, this study examines agricultural producers' educational needs and interests. Data obtained through a survey of crop producers are used in probit models examining interest in additional training in five areas including forward contracting, futures and options, crop yield insurance, crop revenue insurance, and financial management. The study results should be useful in determining appropriate risk management education program content and in identifying and tailoring to specific target audiences.

Two methods were used to estimate the cost of forward contracting hard red winter wheat. One hundred days before delivery, the estimated cost of forward contracting ranged from six cents/bu. to eight cents/bu. Thus, further evidence is provided that the cost of forward contracting grain is not zero.