All Working Papers

Weather derivatives represent a relatively new form of financial security with payoffs contingent on weather indices based on climatic factors. These contracts provide firms with the ability to manage unforeseen climatic changes that create risk in terms of the variability of earnings and costs. The potential for their use in a wide variety of industries is great as it has been estimated that approximately one-seventh of the industrialized economy is weather sensitive (Hanley, 1999). A recent survey for example, conducted by the U.S. Department of Commerce in 2004 estimates that approximately 30% of the total GDP of the United States is exposed to some type and degree of weather risk (Finnegan, 2005). A brief listing of affected industries includes not only agriculture and utilities but also the entertainment industry, beverage, construction and apparel industries.

Weather derivatives include various instruments such as swaps, options and option collars with payoffs dependent upon a wide variety of underlying weather –related variables such as average temperature, heating and cooling degree days, maximum or minimum temperatures, precipitation, humidity, sunshine and even temperature forecasts. Temperature related contracts are however the most prevalent, accounting for 80% of all transactions (Cao and Wei, 2004) with standardized contracts trading on the Chicago Mercantile Exchange for major U.S. cities.

As a result the interest in and use of weather derivatives is growing at a phenomenal rate from an estimated $500 million in notional value in 1998 (Finnegan 2005) to $45.2 billion in March 2006 based upon a recent survey of the Weather Risk Management Association. Much of this growth has occurred in the last few years and recent statistics indicate that the notional value of trading in standardized contracts on the Chicago Mercantile Exchange rose from 2.2 billion in 2004 to 22 billion in 2005. The recent growth in weather derivative arrangements is also being fueled by hedge funds which are beginning to add weather contracts in order to further diversify their investments. (Ceniceros, 2006)

Although the use of weather derivatives is potentially widespread it would appear that firms in many sectors of the economy have not yet established a hedging policy or even ascertained their full exposure to weather risk. Their potential use in the viticulture industry for example has seen limited applications, mainly involving the mitigation of risk in retail sales, due to climate conditions. The use of these instruments in hedging quality and quantity in grape growing has yet to be seen on a widespread basis. Although the lack of liquidity for specialized weather derivative contracts appears to be the main reason for their lack of use, other issues include uncertainties as to the pricing of these securities. In addition, the availability of useful historical weather data and the definition of an appropriate underlying variable that is the source of uncertainty, also adds to their complexity.

The Niagara region of Ontario, Canada represents the largest producer of icewine in the world with icewine significantly contributing to the revenues of many of the over 85 wineries in the region. Its production however is quite sensitive to the occurrence of relatively low temperatures during the winter months, when the grapes employed for icewine are harvested in a frozen state. Cyr and Kusy (2005) explored the potential use of weather derivatives for hedging the risks inherent in icewine production in the Niagara region of Ontario, Canada due to temperature fluctuations. In particular their study attempted to model a temperature variable based on daily observations and subsequent prices of options that could be employed for hedging icewine production. Data limitations and the development of an optimal forecasting model however, mitigated these efforts. Their findings are not unlike previous studies in the application of weather derivatives where the lack of appropriate weather data specific to a region often limits their use.

Cyr and Kusy (2006) later identified a model for estimating optimal icewine hours based upon daily observed temperature variables with fairly high explanatory power. The use of daily temperature variables that are easily measured and observed by both parties to a weather derivatives contract is a critical element to their successful use and aid in the contract’s liquidity. Their model was based upon a three year period for which hourly temperature data was available at a critical weather station.

In the current study we employ the model identified in Cyr and Kusy (2006) in order to estimate optimal icewine production hours for the period of 1966 through 2006. Given the time series of estimated icewine hours we then explore its behavior in order to identify a stochastic process. Using Monte Carlo simulation we then estimate the price of put options based on cumulative optimal icewine hours under varying assumptions with regards to the stochastic process.

Section II provides a brief overview of the history and use of weather derivatives and their basic structure. Section III describes the process of icewine production in Canada, the risks inherent in the endeavor and the potential use of weather derivatives to mitigate those risks. In section IV we attempt to define and identify a stochastic process for estimated icewine production hours based upon daily observed temperature variables and in section V we estimate put option values based upon varying assumptions for the stochastic process.
Finally section VI summarizes the paper.

Bordeaux is a region of France and red Bordeaux wines have been produced in the same place, and in much the same way, for hundreds of years. Yet, there are differences in quality and price from year to year that can sometimes be quite large. Until very recently, these quality differences have been considered a great mystery. In this paper I show that the factors that affect fluctuations in wine vintage quality can be explained in a simple quantitative way. In short, I show that a simple statistical analysis predicts the quality of a vintage, and hence its price, from the weather during its growing season. Along the way, I show how the aging of wine affects its price, and under what circumstances it pays to buy wines before they are at their best for drinking. Since this procedure for predicting wine quality has now been in use for over a decade, I also provide an appraisal of its successes (and failures), and a discussion of the role this information has played in the evolution of the wine trade. When a red Bordeaux wine is young it is astringent and most people will find it unpleasant to drink. As a wine ages it loses its astringency. Because Bordeaux wines taste better when they are older, there is an obvious incentive to store them until they have come of age. As a result, there is an active market for both younger and older wines. Traditionally, what has not been so obvious is exactly how good a wine will be when it matures. This ambiguity leaves room for speculation, and as a result, the price of the wine when it is first offered in its youth will often not match the price of the wine when it matures. The goal in this paper is to study how the price of mature wines may be predicted from data available when the grapes are picked, and then to explore the effect that this has on the initial and final prices of the wines.

This article analyses the way some 6,000 European wine consumers, both connoisseurs and non-connoisseurs, use a set of available signals (price, umbrella branding, goodwill, past consumption) to assess the quality of Bordeaux wines where price is the main source of information on quality. Connoisseurs use this signal less intensively than nonconnoisseurs. Price represents a substitute for umbrella branding where consumers are not aware of who is beneath this umbrella, and where this signal is thus of no help to them. This could explain why such wines tend nowadays to lose market share in favor of branded wines that are easier to evaluate.

We study whether quality assessments made by wine experts and by consumers (based on prices obtained at auction between 1980 and 1992), can be explained by variables describing endowments (land characteristics, exposures of vineyards) and technologies (from grape varieties and picking, to bottled wines). However, since technological choices are likely to depend on endowments, the effects can only be identified using an instrumental variables approach. We show that technological choices affect quality much more than natural endowments, the effect of which is negligible.

The purpose of this paper is to measure the impact of Robert Parker’s oenological grades on Bordeaux wine prices. We study their impact on the so-called en primeur wine prices, i.e., the prices determined by the chaˆteau owners when the wines are still extremely young. The Parker grades are usually published in the spring of each year, before the wine prices are established. However, the wine grades attributed in 2003 have been published much later, in the autumn, after the determination of the prices. This unusual reversal is exploited to estimate a Parker effect. We find that, on average, the effect is equal to 2.80 euros per bottle of wine. We also estimate grade-specific effects, and use these estimates to predict what the prices would have been had Parker attended the spring tasting in 2003.