This paper presents a general method for pricing weather derivatives. Specification tests find that a temperature series for Fresno, California follows a mean-reverting Brownian motion process with discrete jumps and ARCH errors. Based on this process, we define an equilibrium pricing model for cooling degree day weather options. Comparing option prices estimated with three methods: a traditional burn-rate approach, a Black-ScholesMerton approximation, and an equilibrium Monte Carlo simulation reveals significant differences. Equilibrium prices are preferred on theoretical grounds, so are used to demonstrate the usefulness of weather derivatives as risk management tools for California specialty crop growers. -1- Pricing Weather DerivativesWeather derivatives are contingent securities that promise payment to the holder based on the difference between an underlying weather index -accumulated snowfall, rainfall, or "degree days" over a specified period -and an agreed strike value. Because weather 1 represents a common source of volume risk for agribusinesses of all types, weather derivatives are a potentially valuable tool for risk management. Compared to insurance contracts, there are many benefits to using weather derivatives to manage risk. First, in order to claim a loss under an insurance contract, a grower must prove that a loss occurred on his or her own farm, or county in the case of area-based insurance products.Adjusting crop losses is expensive to administer and contains an element of subjectivity that growers seldom appreciate. Second, insurance in general is intended to cover the damage caused by infrequent, high-loss events rather than relatively high-probability, limited-loss events. Third, crop insurance products that are based on individual-firm losses are subject to moral hazard problems, so an alternative tool that pays out based on some objective measure of the weather itself may be a preferable alternative (Yoo; Turvey; Cao and Wei). In spite of these advantages, and the increasing interest in weather risk management more generally (Weather Risk Management Association), the volume of trade in weather derivatives has been growing relatively slowly (Dischel). Several factors contribute to this lack of liquidity, including (1) the absence of a forward market in a relevant weather index, (2) potential basis risk, (3) problems defining meaningful weather data, and (4) the lack of agreement over a common pricing model (Dischel; Nelken; -2-Turvey). Although the Chicago Mercantile Exchange (CME) began trading degree-day futures and options for a number of major U.S. cities in the fall of 1999, the fact that weather is a local phenomenon and micro-climates often differ radically within small geographic areas means that the CME products are of little use to most agricultural producers, or of limited use to many. Second, basis risk is likely to be a significant problem for firms that wish to hedge using derivatives based on weather indices. Basis risk, in this case, refers to the difference between a weat...
The COVID‐19 pandemic exposed critical weaknesses in the US food supply chain. Faced with the near‐complete loss of the food service distribution channel, stories of wasted food, failing suppliers, and food shortages were common. We argue that the pandemic revealed a fundamental lack of resilience in the food supply chain that, while causing short‐term welfare losses, need not have happened, and resulted from a failure of vision rather than a market failure in the traditional sense. We present a model of supply chain flexibility, grounded in real options theory, that demonstrates how firms can increase shareholder value by maintaining flexibility across supply chains. We present an example from the US fresh produce industry (onions) to demonstrate our hypothesis.
Value‐at‐risk (VaR) determines the probability of a portfolio of assets losing a certain amount in a given period at a particular level of confidence. Value‐at‐risk is receiving considerable attention in the finance literature for its use in reporting the risks of derivatives. This article provides a state‐of‐the‐art review of VaR estimation techniques and empirical findings. The ability of VaR estimates to represent large losses varies among procedure, confidence levels, and data used. To date no consensus exists regarding the most appropriate estimation technique. Potential applications of VaR are suggested in the context of agricultural risk management.
Weather derivatives represent an important financial innovation for risk management. As with the use of any derivatives contract, the behaviour of the basis ultimately determines the net-hedged outcome. However, when using weather derivatives to hedge volumetric risks, risk managers often face unique basis risks arising from both the choice of weather station where a derivatives contract is written, as well as the relationship between the hedged volume and the underlying weather index. Using the encompassing principle, this research shows that the nonlinear relationship often found between crop yields and weather creates a specific hedging role for options. The results suggest that weather derivative instruments with nonlinear pay-offs, such as options, be used solely or in combination with linear payoff instruments, such as swaps or futures, to minimize basis risk associated with the nonlinear relationship between yields and weather. This research also suggests that the choice of weather station may be less critical in managing basis risk than properly accounting for the relationship between yields and weather.
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