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WEATHER DERIVATIVES AS A RISK MANAGEMENT TOOL
By Robert E Katz, MComm CA (SA)

ABSTRACT

The weather has an enormous impact on business activities of many kinds and varies both geographically and seasonally. Faced with these weather challenges and opportunities, a new financial instrument called the weather derivative has emerged in recent years. Sellers of weather derivatives use the instruments to hedge their own risks and to make trading profits. Just as a firm can manage its currency exposure, so it can hedge its weather exposure.

KEY WORDS

Weather derivatives
Insurance
Risk
Weather Forecasts
Temperature Variability
Pricing Mechanisms
Indices
Liquidity
Management Tool

1. Introduction
n 2002, FedEx reported that it lost revenue and incurred higher costs as a result of recent severe winter storms; Yum Brands, parent of Pizza Hut, Taco Bell and KFC, reported that store sales fell 5% in February, hurt by wintry conditions; and McDonalds reported that United States (hereafter US) February sales were impacted by the sluggish US economy and severe winter weather (Douglas-Jones, 2003:46).

Weather has always been an unpredictable phenomenon whether it is temperature, rainfall, frost or snow. With weather patterns becoming more and more unpredictable and with the abnormal conditions experienced over the last two decades, many industries are affected by weather in a significant way (Geyser & Van der Venter, 2001:2).

In the agricultural industry, for example, businesses have long used futures contracts of agricultural commodities to hedge weather-related risks. However, today there is such a broad array of weather risks that traditional methods cannot cover them all. As a result, a more versatile financial instrument, namely weather derivatives, has emerged in recent years (Geyser, 2002:2).

2. Basic Concepts
A weather derivative is a contract between two parties that stipulates how payment will be exchanged between the parties, depending on certain meteorological conditions during the contract period. Weather derivatives are usually structured as swaps, futures and call or put options based on different underlying weather indices (Alaton, Djehiche & Stillberger, 2002:4).

Weather derivatives have one major difference from traditional derivatives. In contrast to traditional derivatives, there is no underlying traded instrument on which weather derivatives are based. Whereas equity, bonds or foreign exchange derivatives have their counterparts on the spot markets, weather is not traded as an underlying in a spot market. This means that unlike other derivatives, weather derivatives are not used to hedge the price of the underlying, as the weather itself cannot be priced. They are used rather as a proxy to hedge against other risks affected by weather conditions, for example, the risk that heating oil consumption will decrease due to higher than normal temperatures (Geyser & Van der Venter, 2001:2).

A generic weather derivative contract can be formulated by specifying the following seven parameters:

  • Contract type (swap, call or put);
  • Contract period (e.g., from November 1, 1999 to March 31, 2000);
  • An official weather station from which the meteorological record is obtained;
  • Definition of the underlying weather index(W);
  • Strike for put/call or exercise index for swap (both denominated S);
  • Tick (k) for a linear payout scheme or the fixed payment (Po) for a binary payment scheme; and
  • Premium for the put or call (Zeng, 2000:73).

3. Global Size and Demand
According to the US Department of Commerce, in 2001 at least $1 trillion of the US economy was sensitive to the vagaries of the weather, including vast portions of the energy, manufacturing, retailing, tourism and manufacturing industries (Tawney, 2001:58).

A market survey was conducted in 2002 of 70 companies involved in the global weather risk management market by the risk magazine Futures and Options World, in which respondents included energy companies, brokers, investment banks and specialist weather derivative providers from the US , Europe and Japan. The results are shown in figures 1 and 2 below.

It can be seen that the US dominates the market. However, despite their rather small percentages, the markets in Europe, the United Kingdom, Japan and Asia should not be underestimated. According to market participants, growth when it comes, will be significant and will occur at a rapid pace. Responses to the survey also showed that Heating Degree Days (hereafter HDD) contracts are by far the most prevalent at 60% , followed by Cooling Degree Days (hereafter CDD) at 34%, because of their use by energy companies, which are still the biggest participants in the weather derivatives market (Douglas-Jones, 2002a:50/51).

The survey also showed which industry sectors show the biggest demand for weather derivatives products. The findings also illustrate the markets differing characteristics between geographical time zones, as seen in figure 2 (Douglas-Jones, 2002a: 50/51).

4. Weather Derivatives in South Africa
Traders have begun paying close attention to the market in South Africa. Demand for weather hedging products comes predominantly from the agricultural sector as it is not subsidised and because the energy sector currently remains regulated. Gensec’s deal in February 2002 with Aquila, a subsidiary of the listed Kansas City based company UtiliCorp United, was the first weather derivatives deal in the South African market. The deal was structured to provide ZZ2 Ceres, one of South Africa’s largest producers of deciduous fruit and vegetables, protection against early spring frost, and is one example of how weather derivatives can be utilised by the country’s agricultural sector. The transaction saw ZZ2 being paid for days when the temperature was equal to or below 0 degrees Celsius during the crucial budding phase (Douglas-Jones, 2002b:27).

Since the Gensec deal was announced in 2002, there has been a positive response to the products from a number of industries, particularly wheat and maize growers, silo owners, transport companies in the sugar industry, fishing as well as insurance companies (Bolin,2002:37).

There are many sectors that would benefit from participating in weather hedging:

  • Theme Parks and Sporting Events

In South Africa the busiest period for theme parks and sporting events are the summer months, unfortunately the same months that most of the country receives its rain. Attendance figures are closely correlated with weather conditions;

  • Construction

In this industry, heavy financial penalties can be imposed for work that runs past its completion schedule. At the same time, delays can also cause projects to run over budget. Construction sites that are under water are subject to heavy delays, concrete cannot set and the operation of heavy machinery in rainy conditions is very difficult;

  • Clothing

Although fashion determines the clothing line retailers stock in their stores, weather conditions strongly influences what customers buy. If a very mild winter is experienced, jacket and sweater manufacturers’ products will experience slow sales; and

  • Agriculture

Weather is a major risk in agriculture. Whether it be sunshine hours, temperature, rainfall or wind, they can all affect the quality and quantity of a crop (Geyser, 2002:5).

5. Impact on Emerging Markets
The introduction of weather derivatives to the agricultural sector in particular has generated considerable interest among supranational organisations including the World Bank and International Finance Corporation (IFC).Farmers in most under-developed countries, in particular Africa where weather risk can be devastating, are not supported by government sponsored crop insurance programmes and weather derivatives could provide a way to protect them against the risk of a drought or a poor harvest. A large proportion of South America’s economy for example, relates to growing commodities and selling them on the world markets. In Brazil, the coffee harvest could be adversely affected by bad weather conditions and ultimately have a major impact on the economy. Weather derivatives on the appropriate locations could bring added stability to Brazil’s economy and ultimately to the world economy (Cooper, 2001:28).

6. Current markets
In a survey focused on activity in the weather risk industry in 2002,Weather Risk Management Associates found that the number of transactions transacted grew by 43% compared to the last year, with 3,937 weather transactions completed for a total notional value of over $4.3 billion dollars, a dollar increase of 72% (Douglas-Jones, 2002b:24).

The recent departure of many energy firms from the market has been a catalyst in pushing out the weather derivative knowledge and skills base to other sectors. Trading teams have moved from the energy sector to the financial sector as banks realise the importance of a weather risk management capability. In addition, banks such as ABN Amro, Goldman Sachs, Deutshe Bank and insurance and re-insurance firms such as Swiss Re are starting to bring in a new more diversified client base (Douglas-Jones, 2002b:24/25).

An impediment to expansion has been the lack of liquidity in secondary market trading. Most weather structures are specific to the needs and locations of end users, and thereby have narrow appeal to the broader market. Only those assets indexed to weather in big cities are likely to generate frequent secondary trades. Currently, as the market’s notional size increases, the market is still left without the enhanced liquidity it indisputably needs (Dischel, 2002:20).

Because the market is thinly traded, transactions are arranged by a narrow band of market makers and participation involves a limited number of counterparties. It is not uncommon for bid/offer spreads to be in the triple digits. This lack of liquidity, as evidenced by these sizable spreads, can make weather derivatives a costly and sometimes inefficient hedging mechanism (Williams, 1999:5).

7. Weather Derivative Structures
Weather derivatives are usually structured as futures, call/put options and swaps based on different underlying weather indices.

7.1 Weather Futures
The Chicago Mercantile Exchange (hereafter CME) offers trading with futures based on the Degree Day Index, which is the cumulative sum of daily HDDs or CDDs during a calendar month. The HDD/CDD Index futures are agreements to buy or sell the value of the HDD/CDD Index at a future date. The notional value of one contact is $100 times the Degree Day Index. On the CME the options on futures are European style, which means that they can only be exercised at the expiration date (Alaton, et al. 2002:4/5).

7.2 Weather options
For generic weather options, the buyer of a HDD call pays the seller a premium at the beginning of the contract. In return, if the number of HDDs for the contract period is greater then the predetermined strike level, the buyer will receive a payout. The size of the payout is determined by the strike (S) and the tick size (k). The tick size is the amount of money that the holder of the call receives for each degree-day above the strike level for the period. Often the option has a cap on the maximum payout unlike, for example, traditional options on shares (Alaton, et al. 2002:5).

7.3 Weather Swaps
Swaps are contracts in which two parties exchange risks during a predetermined period of time. In most swaps, payments are made between the two parties, with one side paying a fixed price and the other side paying a variable price. In most types of weather swaps, there is only one date when the cash flows are “swapped”, as opposed to interest rate swaps, which usually have several swap dates. The swaps with only one period can therefore be thought of as forward contracts. Often the contract periods are single calendar months or a period such as January-March (Alaton, et al.2002:6).

8. Weather Measures
As the weather market has been born out of demand for risk management products from the power industry, the most common and liquid products are designed to fit its requirements. However, the market has started to actively trade a growing number of indices tailored to the demands of all participants (Spillet, 2001:34).

Some of the more common indices are:

8.1 Heating Degree Days (HDD)
This index is designed to measure how cold a period is compared to a standard temperature (18oC in Europe and 65oF in the US).This index is favoured by the power industry to hedge against a warm winter in which less power needs to be generated as compared to expectations (Douglas-Jones, 2002a:51).

8.2 Cooling Degree Days (CDD)
Likewise the CDD index is used to measure how warm a period is compared to the standard temperature. This index is favoured by the power industry to hedge against a cool summer in which less power needs to be generated compared to their expectations. This is a common contract in the US where power is required for air conditioning units and not so common in Europe where air conditioning in homes is less common (Douglas-Jones, 2002a:51).

8.3 Other indices
Statistics for deviations from a given value, averages and quantity are available for:

  • Precipitation;
  • Rainfall;
  • Snowfall;
  • Wind speed and direction;
  • Max or min daily temperature;
  • Sunshine; and
  • Humidity (Spillett, 2001: 35).

9. The Distinction between Weather Insurance and Weather Derivatives
For insurance and reinsurance companies, weather risk is often a natural fit with a firms’ core business. They can underwrite weather risk in the same way as they have for years with catastrophe risk. Several re-insurance companies have entered the weather risk market. One of these is Swiss Re. By positioning itself in both the insurance and the financial markets, Swiss Re can offer customers weather deals either in derivative form or in insurance form (Cooper, 2001:32).

Weather derivatives will not totally replace insurance contracts since there are a number of significant differences:

  • Weather insurance is taken out to protect firms from low frequency, high impact weather events such as tornadoes, floods and weather related fires. Weather derivatives protect firms from higher frequency, lower impact events, for example, a temperature drop/increase by a few degrees, a higher/lower amount of snow or rainfall or a higher/lower wind speed (Douglas-Jones, 2003:45);
  • With weather derivatives, the payout is designed to be in proportion to the magnitude of the phenomena. Weather insurance pays a once-off lump sum that may or may not be proportional and as such lacks flexibility;
  • Insurance normally pays out if there has been proof of damage or loss. Weather derivatives require only that a predetermined index value has been passed; and
  • Traditional weather insurance can be expensive and requires a demonstration of loss. Weather derivatives are economical in comparison to insurance, require no demonstration of loss and provide protection from the uncertainty in normal weather (Geyser & Van der Venter, 2001:5).

10. Pricing of Weather Derivatives

10.1 Weather Forecasts
There are different ways to price weather derivatives. Before using any approach, it is important to the gain an intuitive understanding and make sure that the model used is accurately capturing reality. Financial contracts derived from weather-specific measures such as the expected future value of a local temperature, require the ability to predict regional weather conditions, months into the future. Thus, an effective model of the variations of a given weather-specific measure over the course of many months is essential for the accurate pricing of a weather derivative (Garman, Blanco & Erickson, 2000).

Just as financial traders rely on economic forecasts for trading strategy input, weather traders rely on meteorological forecasts for input on expected temperatures. Understanding past weather patterns, including seasonal effects, is an important part of long-range weather forecasting. Weather forecasts are short-term and in the weather derivatives markets should be used in decisions requiring a short-term horizon only. For longer term weather derivatives, seasonal climate forecast are more appropriate (Dutton, 2001:32).

Weather derivatives are classic examples of incomplete markets. The payoffs of these contingent claims are based on weather conditions at a specific site (e.g. Heathrow, London) over a pre-specified period. Clearly, the underlying variable, namely weather, is not a tradable asset as weather in itself does not have a price (Brody, Syroka & Zervos, 2002:189).

10.2 Temperature Variability
Empirical observations show that many weather variables, particularly temperature, exhibit long-range temporal correlations. Long-range dependence, also called “long-memory”, arises from the presence of positive long-range correlations, or persistence, within weather data. If an anomaly of a particular sign exists in the past, it will most likely continue to persist in the future. Hence persistence is the extent to which trends are reinforcing and steadfast and its incorporation into modelling weather dynamics is therefore important in achieving better estimates and bounds for natural weather and climate variability (Brody, et al.2002:190).

The most important decision to be made at the time of analyzing prior data used to price a weather derivative is the choice of the “look back” period. This is the period of time in which to estimate average temperatures and volatilities. Common wisdom holds that 10-20 years of weather data may be required, and that accounting for trends and seasonality’s is essentially de rigor (Garman, et al.2000).

10.3 Weather Derivatives Pricing Approaches
One of the main areas of controversy in the weather derivatives markets is the choice of the pricing methodology to use in order to obtain the “fair” value of the different contracts. Due to the lack of widely accepted weather derivative pricing methodologies, counterparties do not always agree on the right price to trade (Garman, et al.2000).

Below are some of the more popular models currently being used:

10.3.1 Black-Scholes
Fisher Black and Myron Scholes developed a model in 1973 to price put and call options that is still commonly used today. The Black-Scholes model is based on certain assumptions that do not apply realistically to weather derivatives. One of the main assumptions behind the model is that the underlying of the contract (HDD or CDD) follows a random walk without mean reversion. In other words, this model predicts that the variability of temperature increases with time, so temperature could wander off to any level whatsoever (Garman, et al.2000).

The Black-Scholes model is inadequate for weather derivatives for the following reasons:

  • The primary reason not to use a Black-Scholes model to price weather options is that the model is based on an underlying tradable commodity and in weather derivatives there is no underlying commodity. In the natural gas market, for example, the model derives the prices of the gas derivative from the price of physical gas itself. because weather doesn’t have a price, the payoff of a weather option is instead based on a series of weather events, not on the value of the weather; and
  • Black-Scholes requires that it be possible to set up a conceptual portfolio with a position in both the options and the security from which the option value is derived. Without the means to trade weather as a security, we cannot build a riskless portfolio. Weather options are a different kind of derivative than those analysed by Black and Scholes (Dischel, 1998:1).

    10.3.2 Burn Analyses
    This approach is commonly used in the insurance industry and essentially uses a simulation using historical information to estimate uncertain weather related payments. It is easy to implement and understand and in the valuation of complex transactions involving correlated weather indices, the correlation is embedded in the historical data. However, if an extreme event is included in the data, it can distort the results of the analysis as it tends to omit low frequency extreme events (Spillet, 2001:35).

10.3.3 Monte Carlo Based Simulations
“Monte Carlo” is a computer-based method of generating random numbers which can be used to statistically construct weather scenarios. Such Monte Carlo simulations provide a flexible way to price different weather derivative structures. Various types of averaging periods, such as those based on cumulating HDDs or CDDs, can be specified easily. Similarly, and as easily, a contractual cap placed on the price of the derivative can be taken into account (Garman, et al.2000).

10.3.4 Stochastic Process
In this approach a stochastic differential equation is chosen to represent the diffusion of the weather index. The process is calibrated to either historical data sets or market quotes for weather derivatives, should they exist. The equation is then solved using the boundary conditions provided by the payment terms of the derivative transaction. Common features of the processes chosen would be mean reverting or auto-regressive processes. The one main advantage of this method is that the risk statistics are easily expressed. This method is complex to implement, particularly if modelling multiple indices simultaneously (Spillet, 2001:35).

The weather derivatives market needs a standard pricing model so all participants can start communicating in a common language. At the moment, the major weather derivatives market makers have developed “black-box” models that they may not be willing to share with other participants. The large discrepancies between the different models used are preventing the market from developing at an even faster pace. Just as the Black-Scholes model for financial derivatives was one of the main driving factors of the option markets in the 1980s, the weather markets need a common denominator for today’s markets (Garman, et al.2000).

11. Conclusion
The concept behind a weather hedge is simple. It is a way to protect businesses from excessive costs or depressed demand due to unfavourable weather conditions. In this sense weather derivatives are an extension of traditional risk management tools such as options, futures and swaps (Geyser & Van der Venter, 2001:2).

Until the advent of weather derivatives, exposure to the weather had been considered an inherent “business” risk in which only the risk to extreme weather events were hedged through the insurance market (Spillet,2001:34).

As shareholders become increasingly aware of weather derivatives, firms will no longer be able to blame the weather for losses. Just as a firm can manage its currency exposure, so it can hedge its weather exposure. Add to the fact that over 70% of all companies suffer exposure from the weather and you have the beginnings of a major global market (Douglas-Jones, 2002b:27).

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