WEATHER DERIVATIVES

http://www.cmegroup.com/trading/weather/

PRICING the WEATHER
http://www.economist.com/node/21546019
The outlook for the business of hedging against the elements / Feb 4th 2012

Insurance companies have long offered cover against flooding, hurricanes and other catastrophes. For less calamitous changes in the weather, derivatives are a better option. This is still a “niche market”, says Tim Andriesen of CME Group, the exchange where most weather contracts are traded. According to the Weather Risk Management Association, an industry body, the value of trades in the year to March 2011 totalled $11.8 billion, nearly 20% up on the previous year, though far below the peak reached before the financial crisis took the steam out of the business. In 2005-06 the value of contracts had hit $45 billion.

Weather derivatives had an inauspicious start: the first trade was done by Enron in 1997. The instruments were initially used by American energy companies to hedge against the effect that unseasonal temperatures could have on gas sales. But abundant shale gas in the United States has rendered hedges against mild weather less important. Energy companies are still the biggest users of these trades and contracts based on temperatures continue to be the most popular form of weather derivative. But Europe is now the largest market, according to Jürg Trüb of Swiss Re, a reinsurer. And demand for sophisticated and flexible over-the-counter products, which involve other variables such as rainfall, snow and sunshine and are tailored to meet customers’ specific needs, are growing far more quickly than standardised, exchange-traded contracts.

The weather-derivatives industry hopes that farmers will pile in to purchase hedges against sun and rain that can affect the size of their harvest. Subsidised government-insurance schemes offer them some reassurance already, but derivatives can fill gaps or boost coverage. Big construction companies, with tight deadlines and costly penalty clauses, are also turning to derivatives. So too are retailers and companies that run big outdoor events beholden to the weather. Online providers such as CelsiusPro and eWeatherRisk offer small businesses simple and relatively cheap weather-risk coverage. But widening the industry’s appeal further may be tricky. In many instances the direct correlation between weather and revenues is not obvious. And collecting current and historical weather data to calculate risks is harder in Africa or India, both regarded as potentially big markets.

As they look to renewables, it may be that energy companies are the best bet for future growth as well as current revenues. There have been some big transactions with companies that generate hydropower, which requires consistent snow and rain. Products based on sunshine for the solar industry are now available. And some firms are offering contracts to limit the exposure of wind farms to either a lack of puff or gusts that are too strong for turbines. This is helping energy firms to raise cash to invest in pricey wind projects by guaranteeing long-term returns from unpredictable blasts of air. If so, an ill wind might now blow some good.

WEATHER SWAPS
http://www.guardian.co.uk/news/2011/aug/14/weatherwatch-weather-derivatives
by Paul Brown /  14 August 2011

Unlike weather insurance that deals in extremes like floods, weather derivatives pay out on departures from average conditions. A simple example is an ice cream manufacturer who pays a premium against a cooler than average summer. Each day the temperature is below an agreed average then the manufacture gets a pay-out, but if it is a hot summer and ice cream sales boom then the premium costs are more than met from profits. There are many versions. The construction industry loses in cold winters because bricks cannot be laid in frosty conditions. Too many cold days and companies could face costly penalties because of failing to meet construction deadlines. Utilities, on the other hand, lose profits in mild winters.

But not all derivatives involve paying premiums. There are swaps on offer, for example a colder than average winter with lots of snow is good for the skiing industry but expensive for the highway authority that has to clear roads. A swap could be arranged with the skiers paying for road clearing in the event of a bad winter and the highway authority subsidizing the ski resort if it does not snow. Many businesses are dependent on “average weather.” Chocolate sales drop and tanning saloons empty in hot weather while gardening, barbeque and cider sales suffer in cooler summers. White water rafters can pay premiums to guard against too high or too low river flows.

HOW to PLAY the WEATHER
http://articles.businessinsider.com/2011-08-29/wall_street/30056722_1_hurricane-irene-exchange-traded-funds

While others were stockpiling water, flashlights, and board games in preparation for Hurricane Irene, the hedge fund Tudor Investment was crunching numbers. Paul Tudor Jones’ investment firm employs a weather derivatives analyst. Weather derivatives are fairly new, the first one traded in 1997 and the CME introduced the first exchange-traded weather futures contracts in 1999. The main buyers aren’t hedge funds, they are insurance companies, farming conglomerates looking to insure against freezes and bad crops, electric companies, etc. But because weather derivatives are non-correlated (the Euro crisis didn’t stop Irene) and provide a considerable amount of yield, investors in the space have grown recently to include direct investments from pension funds and hedge funds. Some hedge funds, like ~$2.5 billion Nephila Capital for example, specialize in reinsurance and weather risk.

You can go long-only in the weather derivatives space, which some liken to fixed income, or you can go long and short using weather derivatives. The types of weather derivatives you can buy vary from precipitation, rainfall and other “event” derivatives to heating and cooling products, which an electric company might use when measuring volumetric risk around how much product they might sell. Before an event like Irene, a hedge fund like Tudor would build a position based on a prediction, which one of their analysts made about Irene on Friday. Tudor’s weather derivatives analyst sent around a report on Friday afternoon that predicted the chances of a hurricane of disastrous proportions were 35%. Chances that it will be less serious, costing the city a few billion dollars in damage, he said were 75%.

The worst case scenario the analyst predicted, according to a report seen by Business Insider, is a hurricane that costs the area it hits, which includes New York, $40 billion+ in damage. The power could be out for up to a week. He compared it to the devastating hurricane that hit New York in 1821.
On Saturday he updated his prediction to say it looks like slightly less than what we expected. But “stay on guard.” Tudor is currently up around 3% this month. We’ll have to wait to see if they made money on Irene.

RISK MANAGEMENT
http://theconversation.edu.au/why-hedging-a-bet-on-mother-nature-is-a-hot-commodity-5495
http://openmarkets.cmegroup.com/2927/hedging-a-bet-on-mother-nature
by Adam Clements / 12 March 2012

For some industries, the weather plays a significant role in determining revenue. Unexpected weather events can often cause significant financial losses. For instance, a drought can yield a severe impact on an agribusiness’ amount and quality of produce; unseasonably mild winters can similarly diminish the profit margins of utility companies. So, how can companies – particularly those at the mercy of Mother Nature – protect themselves against the elements and limit their exposure to financial risk? Increasingly, companies have been managing weather risk by using derivatives, which provide the means for businesses to protect themselves against adverse financial affects that are due to variations in climate. According to industry body, the Weather Risk Management Association, trading volume of weather derivatives in 2010-2011 increased by 20 percent  on the previous year.

How it Works
Derivative contracts generally represent a contract to trade a specified quantity of an underlying asset, at an agreed price and time. By making a payment to a separate company that will assume the financial weather risk for them, organizations are buying a type of insurance: the company assuming the risk will pay the purchaser a pre-set amount of money that will correspond to the loss or cost increase caused by the disruptive weather. As such, risk exposure can be managed in a wide range of settings. Weather derivatives derive their value from climatic conditions such as temperature, snowfall, hurricanes or rainfall. An important set of contracts traded at CME Group are temperature-based futures contracts. Contracts are offered for trade based on the temperature across a range of U.S., European and Australian cities such as Brisbane, Sydney and Melbourne.

The most common of these contracts come in the form of either Heating Degree Day (HDD) or Cooling Degree Day (CDD) contracts. The payoff of these contracts is based on the cumulated difference in daily temperatures relative to 18⁰C (about 64⁰F) over a fixed period such as a month. The fixed level of 18⁰C is the temperature at which the energy sector believes little heating or cooling occurs in households. The buyer of a HDD or CDD contract benefits from a positive payoff if cumulative temperature is below or above a specified level. While this nomenclature may seem counter-intuitive, heating (or cooling) occurs when temperatures are lower (higher). Major participants in this market include utilities and insurance companies, whose costs and or revenues are dependent upon weather conditions. In an Australian setting, an electricity supplier normally provides its customers with electricity at a fixed price irrespective of the wholesale price in the National Electricity Market. However, the wholesale price of electricity can fluctuate wildly with extreme weather conditions. CDD contracts can provide a hedging tool for such fluctuations in electricity prices in the wholesale market during periods of extremely high temperatures. Similar arguments apply in the northern hemisphere, where utilities face risk from increased demand during periods of low temperatures and hence HDD contracts are a natural hedging tool.

Pricing Weather
Futures on traditional assets such as stocks, bonds, agricultural and most energy products are priced under the cost of carry approach. The logic of this approach is that there are two alternatives for obtaining the asset in question at some point in the future. These are either, borrow to purchase it now and store the asset, or agree to purchase the asset at that later date via a futures contract. Under the absence of arbitrage, the cost of both approaches should be equivalent. Hence the current cost of a futures contract is related to the current price of the asset and the cost of borrowing and storing the asset. This arbitrage-free valuation approach is a simple yet common method for pricing many financial securities. Weather derivatives have also gained research attention in academic circles as they represent a unique pricing problem. The cost of carry method is based on the possibility of storing, or holding the underlying asset.  However, in the case of weather contracts such as HDD or CDD, the underlying asset is not storable in any meaningful way.

As such, the cost of carry approach is not relevant and pricing is based on a discounted value of the payoff from the futures contract. A statistical model is required to generate the possible range of outcomes that the underlying weather index may take and subsequent payoffs ensuing from the derivatives contract. The discount rate will be market determined given the prices for contracts that the market will bear. Weather derivatives are of great economic importance in that they allow participants to manage a very specific form of risk. While weather futures contracts currently make up a relatively small proportion of trading in derivatives markets, it is a sector that is experiencing rapid growth – particularly as more companies recognize the correlation between weather and profit.

HEDGING

http://www.investopedia.com/articles/optioninvestor/05/052505.asp

Until recently, there were very few financial tools offering companies’ protection against weather-related risks. However, the inception of the weather derivative - by making weather a tradeable commodity – has changed all this. Here we look at how the weather derivative was created, how it differs from insurance and how it works as afinancial instrument.

Weather: Risky Business
It is estimated that nearly 20% of the U.S. economy is directly affected by the weather, and that the profitability and revenues of virtually every industry – agriculture, energy, entertainment, construction, travel and others – depend to a great extent on the vagaries of temperature. In a 1998 testimony to Congress, former commerce secretary William Daley stated, “Weather is not just an environmental issue; it is a major economic factor. At least $1 trillion of our economy is weather-sensitive.” The risks businesses face due to weather are somewhat unique. Weather conditions tend to affect volume and usage more than they directly affect price. An exceptionally warm winter, for example, can leave utility and energy companies with excess supplies of oil or natural gas (because people need less to heat their homes). Or, an exceptionally cold summer can leave hotel and airline seats empty. Although the prices may change somewhat as a consequence of unusually high or low demand, price adjustments don’t necessarily compensate for lost revenues resulting from unseasonable temperatures. Finally, weather risk is also unique in that it is highly localized, cannot be controlled and despite great advances in meteorological science, still cannot be predicted precisely and consistently.

Temperature as a Commodity
Until recently, insurance has been the main tool used by companies’ for protection against unexpected weather conditions. But insurance provides protection only against catastrophic damage. Insurance does nothing to protect against the reduced demand that businesses experience as a result of weather that is warmer or colder than expected. In the late 1990s, people began to realize that if they quantified and indexed weather in terms of monthly or seasonal average temperatures, and attached a dollar amount to each index value, they could in a sense “package” and trade weather. In fact, this sort of trading would be comparable to trading the varying values of stock indices, currencies, interest rates and agricultural commodities. The concept of weather as a tradeable commodity, therefore, began to take shape. “In contrast to the various outlooks provided by government and independent forecasts, weather derivatives trading gave market participants a quantifiable view of those outlooks,” noted Agbeli Ameko, managing partner of energy and forecasting firm EnerCast. In 1997 the first over-the-counter (OTC) weather derivative trade took place, and the field of weather risk management was born. According to Valerie Cooper, former executive director of the Weather Risk Management Association, an $8 billion weather-derivatives industry developed within a few years of its inception.

In Contrast to Weather Insurance
In general, weather derivatives cover low-risk, high-probability events. Weather insurance, on the other hand, typically covers high-risk, low-probability events, as defined in a highly tailored, or customized, policy. For example, a company might use a weather derivative to hedge against a winter that forecasters think will be 5° F warmer than the historical average (a low-risk, high-probability event). In this case, the company knows its revenues would be affected by that kind of weather. But the same company would most likely purchase an insurance policy for protection against damages caused by a flood or hurricane (high-risk, low-probability events).

CME Weather Futures and Options on Futures
In 1999, the Chicago Mercantile Exchange (CME) took weather derivatives a step further and introduced exchange-traded weather futures and options on futures - the first products of their kind. OTC weather derivatives are privately negotiated, individualized agreements made between two parties. But CME weather futures and options on futures are standardized contracts traded publicly on the open market in an electronic auction-like environment, with continuous negotiation of prices and complete price transparency. Broadly speaking, CME weather futures and options on futures are exchange-traded derivatives that – by means of specific indexes – reflect monthly and seasonal average temperatures of 15 U.S. and five European cities. These derivatives are legally binding agreements made between two parties, and settled in cash. Each contract is based on the final monthly or seasonal index value that is determined by Earth Satellite (EarthSat) Corp, an international firm that specializes in geographic information technologies. Other European weather firms determine values for the European contracts. EarthSat works with temperature data provided by the National Climate Data Center(NCDC), and the data it provides is used widely throughout the over-the-counter weather derivatives industry as well as by CME.

Weather contracts on U.S. cities for the winter months are tied to an index of heating degree day (HDD) values. These values represent temperatures for days on which energy is used for heating. The contracts for U.S. cities in the summer months are geared to an index of cooling degree day (CDD) values, which represent temperatures for days on which energy is used for air conditioning. Both HDD and CDD values are calculated according to how many degrees a day’s average temperature varies from a baseline of 65° Fahrenheit. (The day’s average temperature is based on the maximum and minimum temperature from midnight to midnight.)

Measuring Daily Index Values
An HDD value equals the number of degrees the day’s average temperature is lower than 65° F. For example, a day’s average temperature of 40° F would give you an HDD value of 25 (65 – 40). If the temperature exceeded 65° F, the value of the HDD would be zero. This is because in theory there typically would be no need for heating on a day warmer than 65°.


Daily average temperatures and the corresponding HDD and its impact on the relevant contract

A CDD value equals the number of degrees an average daily temperature exceeds 65° F. For example, a day’s average temperature of 80° F would give you a daily CDD value of 15 (80 – 65). If the temperature were lower than 65° F, the value of the CDD would be zero. Again, remember that in theory there typically would be no need for air conditioning if the temperature were less than 65°F. For European cities, CME’s weather futures for the HDD months are calculated according to how much the day’s average temperature is lower than 18° Celsius. However CME weather futures for the summer months in European cities are based not on the CDD index but on an index of accumulated temperatures, the Cumulative Average Temperature (CAT).

Measuring Monthly Index Values
A monthly HDD or CDD index value is simply the sum of all daily HDD or CDD value recorded that month. And seasonal HDD and CDD values, accordingly, are simply accumulated values for the winter or summer months. For example, if there were 10 HDD daily values recorded in Nov 2004 in Chicago, the Nov 2004 HDD index would be the sum of the 10 daily values. Thus, if the HDD values for the month were 25, 15, 20, 25, 18, 22, 20, 19, 21 and 23 the monthly HDD index value would be 208. The value of a CME weather futures contract is determined by multiplying the monthly HDD or CDD value by $20. In the example above, the CME November weather contract would settle at $4,160 ($20 x 208 = $4,160).

GREAT WEATHER RISK MANAGEMENT TRANSACTIONS in HISTORY
http://www.meteologica.com/meteologica/content/case-studies
http://www.wrma.org/risk_transactions.html

Great Weather Risk Management Transaction No. 1

Managing Human Catastrophe Risk
In a widely publicized transaction the World Food Program purchased a precipitation cover from Axa Re in order to prefund an emergency response in the event the drought affecting Ethiopia continued in 2006.

Summary Technical Details:
Type: Aggregate precipitation cover
Period: Agricultural growing period in Ethiopia, March-October
Form: Derivative – call option
Index: Precipitation as measured at 26 sites throughout the country, converted into crop water-stress indices and combined in a national basket
Trigger: Crop water-stress index above a pre-specified level at the end of the season indicating wide-spread drought and crop failure.
Limit: $7.1 million
Premium: $0.93 million

Rationale:

  • Efficient use of donor funds (i.e. purchased $7 million of financial resource for less than $1 million to be available in the event of continued drought emergency)
  • Rapid response to drought emergency. The instrument pays immediately upon the drought condition – i.e. crop water-stress above the trigger level indicating widespread crop-failure. Normal donor response requires months before funds are available.

Rapid availability of funds means that World Food Program can move quickly to provide aid on a timely basis, thereby reducing human misery, limiting population dependence on outside support and ultimately reducing the total cost to the world donor pool of humanitarian assistance for this crisis.

Outcome:
In the rainfall levels in 2006 were above average in Ethiopia and so that no call will be made on the stress index call. World Food Program established a mechanism for accessing global risk markets to supplement traditional donor-based humanitarian relief. Axa Re has demonstrated methods for working effectively with difficult technical and data issues.

NB: This transaction received extensive press coverage, which included publication of financial aspects of the transaction normally not disclosed. Discussion of other transactions may not include such details.

Great Weather Risk Management Transaction No. 2

Managing Costs of Generating Electricity

Hydro generation is among the cheapest sources of electric power. When water is in short supply hydro-electric plants produce less electricity, increasing the cost of production per Kwh. Additionally lost power must be made up from other sources, e.g. from sources for which there is a cost for the underlying energy such as gas-fired generation. The combination of drought and summer heat waves creates scenarios of reduced availability of water and heightened demand. Both factors increase the per Kwh cost of providing electricity to customers.

In 2000 the Sacramento Municipal Utility District (SMUD), a customer owned generator and distributor of electricity, purchased a three year structure to protect it from the volatility of the major components of its cost of generation: water supply and the price of natural gas. The risk takers were two energy trading firms.

Summary Technical Details:

  • Type: Aggregate precipitation cover.
  • Period: October 1, 2000, to September 30, 2003, in three twelve month periods.
  • Form: Derivative – collar
  • Index: Precipitation as measured at Pacific House, California.
  • Trigger: SMUD receives payment when precipitation is less than xx inches (A). SMUD makes payment when precipitation exceeds yy inches (B).
  • Payment: Based on average spring and summer daily price of natural gas at Henry Hub, multiplied by an agreed factor, per inch of precipitation.
  • Maximum Payment SMUD receives payment up to the amount corresponding to qq inches precipitation below trigger A. SMUD pays up to the amount corresponding to rr inches of surplus precipitation greater than trigger B.
  • Premium: $0 (costless collar) plus frictional costs.

Rationale:

  • As a mutual, SMUD sought to minimize costs to its owner-customers. It chose to surrender a portion of its possible excess generation in times of surplus water supply in exchange for protection against possible increases in generation costs due to a shortfall of water and high natural gas prices.

Outcome:

  • Cost of power to SMUD customers remained among the lowest in the State despite turmoil in California electricity market during this period.
  • Successful early example of combining weather risk (which translates into volumetric risk of power supply) and price risk (cost of fuel for alternative, second tier generation) to manage buyer’s own weather risk exposure.

MARKET HISTORY
http://www.wrma.org/risk_history.html
History of the Weather Market

Three transactions in the autumn of 1997 mark the beginning of the current weather risk market. The transactions were between Koch Industries and Enron (2 transactions) and, through the intermediary of Willis, between Koch Industries and PXRe. These transactions marked the culmination of eighteen months’ work by Koch, Willis and Enron aimed at finding a means of transferring the risk of adverse weather. Their work focused on the use of weather data – measurable weather variables such as temperature or precipitation – as the basis for risk indices, which turned out to be the key for making weather risk fungible. Risk was to be expressed and transferred in terms of temperature, precipitation, snowfall, wind or other measurable variables.

The principle is easy to illustrate. In a typical temperature transaction, if weather is too warm – e.g. the average temperature measured over a defined period exceeds a pre-agreed threshold – the buyer is entitled to receive a payment from the seller based on the extent to which the average temperature exceeds the threshold. The amount of payment is determined in advance in accordance with the buyer’s sensitivity to adverse changes in temperature – for example increased costs of air conditioning. In the current weather market, risks can be transferred in this manner in the form of index-based insurances and through derivative transactions built on similar weather indices. Please refer to the “Weather Risk” section of this website for more in depth discussion of weather risk management and the business of weather risk.

In and of itself there was nothing new in the idea of transferring weather risk. Weather had been the subject of insurance for some time – indirectly in the realm of agricultural insurance (e.g. drought insurance, hail) and directly in the realm of contingency insurance, often in conjunction with public events (sporting events, concerts) and sales promotions ($1,000 rebate on your car purchase if it snows on New Year’s Eve). Temperature contingent power supply agreements had existed before the autumn of 1997 as well. More to the point, the concept of systematically managing gas utility temperature risk had been put forth approximately fifteen years before by Roger Wilcox of National Fuel Gas who proposed creating a gas-utility mutual to pool temperature risk expressed in terms of Heating Degree Days.

These predecessor transactions and initiatives each had their limitations and none developed into a market. The weather risk market established nearly ten years ago distinguishes itself by combining several features:

  • Provides index based risk transfer per measurable weather variables.
  • Handles temperature, precipitation, snowfall, stream flow, wind speed, daylight hours, humidity and other weather variables.
  • Transfers risk on the basis of aggregate measures (e.g. total precipitation in a period, total degree days in a period), frequency of incidence (e.g. days with maximum temperature less than 32ºF in a period) or adverse event (e.g. rainfall greater than 0.50 cm on the day of finals at Wimbledon) per closely related methodologies which integrate the market.
  • Manages risk in ways compatible with both financial and insurance markets.
  • Comprises a primary and secondary market in weather risk.

The weather market has experienced rapid evolution in its short history. Significant ENSO events hallmarked its first two winters, during which the young market was dominated by warm side winter risk, particularly gas utilities seeking protection from the consequences to their revenues of warm winters on volumes of gas purchased by consumers. The risk was held by risk takers (predominantly insurance companies) who, in the main, managed their risk geographically under a buy and hold regime. Particularly the first winter season’s El Niño event not only pushed temperatures against those holding risk in the market, it also made the weather pronouncedly directional across the U. S., destroying the fundamental assumptions of the market’s geographical risk management practices. The surviving risk takers changed their approach, choosing to manage risk dynamically according to disciplines adapted from commodity and financial trading. Energy and utility corporations’ trading operations became increasingly active in the market until the crisis in the energy sector in 2001-2002. The place of the energy traders has been taken by insurers, banks and hedge funds and by trading on exchanges, preeminently on the Chicago Mercantile Exchange. This constellation of market makers and market participants today (2006) offers the weather market greater depth, breadth and financial security than ever. Its numbers include several of the strongest financial institutions on the globe.

Over this period the market also has expanded geographically, with weather business being transacted on risks from all inhabited continents, most particularly North America, Japan and Europe. Emerging from a period in which the market was dominated by energy business, the market is spreading to encompass a variety of sectors, including agriculture, construction, transportation and entertainment. In the last three years the exchange trading of weather risk, often in conjunction with commodity and energy risk, has mushroomed and has attained a level of critical mass on the CME. The weather market has emerged as an important contributor to the management of risk in a wide variety of businesses and areas of government responsibility.

We expect the weather market to continue to develop, broadening its scope in terms of geography, client base and inter-relationship with other financial and insurance markets. Although the weather risk market has made a very good start as it enters its tenth year, there remains plenty of space in which it can grow even further and contribute to the management of a complex of risk which affects a third or more of the world’s GDP.

INTRODUCTION to WEATHER DERIVATIVES
 http://www.globexnymex.com/trading/weather/files/WEA_intro_to_weather_der.pdf
by Geoffrey Considine, Ph.D., Weather Derivatives Group, Aquila Energy

Introduction
The first transaction in the weather derivatives market took place in 1971. Since that time, the market has expanded rapidly into a flourishing over the counter (OTC) market. Further growth in the end-user sector is somewhat limited by the credit issues associated with an OTC market (i.e., satisfying the International Securities and Derivatives Association Master Swap Agreement). To increase the size of the market and to remove credit risk from the trading of weather contracts, the Chicago Mercantile Exchange (CME) is introducing weather derivatives to be traded electronically on the CME’s GLOBEX®2 system. The individual contracts are calendar-month futures (swap) contracts on heating degree days (HDD) and cooling degree days (CDD) as well as options on futures2. This document discusses some of the fundamentals of pricing and analyzing weather contracts.

Birth Of A New Market
There are a number of drivers behind the growth of the weather derivative market. Primary among these is the convergence of capital markets with insurance markets. This process is evidenced by the growth in the number of catastrophe bonds issued in recent years as well as the introduction of the catastrophe options that are traded on the Chicago Board of Trade (CBOT). Weather derivatives are the logical extension of this convergence. The overall growth in the ‘securitization’ of risk in the weather and catastrophe markets shows no signs of slowing. The weather derivative market was jump started during the El Niño winter of 1997-98, one of the strongest such events on record. This event was unique in terms of the publicity that it received in the American press. Many companies, faced with the possibility of significant earnings declines because of an unusually mild winter, decided to hedge their seasonal weather risk. Weather derivative contracts are particularly attractive to businesses that have experience with financial options and futures. The insurance industry was facing a cyclical period of low premiums in traditional underwriting businesses in this same period and was in a position to make available sufficient amounts of risk capital to hedge weather risk. The large base of written options from insurance companies provided the liquidity for the development of a monthly and seasonal swap market in weather.

Hedging Weather Risk
A company has a number of alternatives in structuring a weather deal. The first
alternative is most similar to an insurance product — to buy a cooling degree
day option (CDD) in the case of summer, or a heating degree day option
(HDD) for winter. The number of cooling degree days on a single day is the dif-
ference of the daily average temperature from 65 degrees Fahrenheit. Cooling
degree days and heating degree days are never negative. If the daily average
temperature is less than 65 F, then the difference of the daily average tempera-
ture and 65 F is the number of HDDs. Over the course of a month, one might
accumulate both CDDs and HDDs. Weather options are written on the cumula-
tive HDDs or CDDs over a specified period. The CME contracts therefore are
based on the total number of HDDs or CDDs in the month.

Beyond the insurance-like purchase of a call or put option, a business with
weather exposure may choose to buy or sell a futures contract, which is equiva-
lent to a swap such that one counter party gets paid if the degree days over a
specified period are greater than the strike level, and the other party gets paid if the degree days over that period are less than the strike. A business may also
choose to write an option. A heating oil retailer may feel that if the winter is
very cold they will have high revenues — so they might sell an HDD call. If
the winter is not particularly cold, the heating oil retailer keeps the premium on the call. If the winter is very cold, the retailer can afford to finance the option pay out with higher-than-normal revenues.

A customer may wish to buy a strip of CDD or HDD contracts spanning the
entire cooling season of April through October. Each contract has a specified
strike for each month. Each option is listed with a price for each range of
strikes. In the OTC market, it is common for options to be written on a multi-
month period with a single strike over the entire period. The benefit of buying a
strip of monthly contracts is that the strip can be broken apart more readily than a single, longer-term contract. The simplest approach is to purchase a strip of call or put options over the range of months that are of interest to the user. As one intuitively expects, the further out of the money (i.e., away from normal
conditions) the strike is set, the lower the price of the option (the premium).
The strike is set relative to the normal climatological values. The normal value
is a matter of debate. The market currently seems to be converging on the aver-
age over the past 10-15 years. Clearly there are many cases in which the 15-
year average may not be ideal. Miami, for example, has shown a substantial
warming trend over the past 30 years, such that 15-year average CDDs in sum-
mer are less than one may expect. Of course, the market will have factored the
trend into the pricing of the option. A CDD call option will thus appear quite
expensive if the option is simply priced at the 15-year average. Conversely, a
CDD put option will appear to be inexpensive in this scenario. To date, utilities have been the largest end-users of weather derivatives. However, there are many other businesses in which weather has a major impact on revenues. It is anticipated, for example, that positions in agricultural commodities will be hedged with weather contracts more extensively than power and gas positions because of the long series of historical data available in the agricultural markets. Because growing degree days and cooling degree days are very similar, standard weather contracts could be used to hedge commodity price risk. One of the CME-listed cities is Des Moines, and we present some calculations that demonstrate how a considerable fraction of the volatility of corn prices in Iowa could be hedged using weather options. The challenge in such cross-commodity hedges is the development of appropriate weather pricing models.

Obtaining The Inputs To The Pricing Model
Defining an appropriate mean and standard deviation is the key challenge in
simple-option pricing. Do we use the last 10 years? The last 20 years? How
about 50 years? The problem is that climate is non-stationary, which is to say
that the relevant mean and standard deviation evolve with time. This problem is
well known among climate researchers who have struggled to determine the
Optimal Climate Normal (OCN), or the optimal average time scale of previous
years for determining the expected value for this year. The National Center for
Environmental Prediction (NCEP) runs an operational tool that is a simplified
OCN calculation. This product examines whether the previous 10 years are a
better climate predictor than the defined “climate normal period” of 1961-1990.
Where the historical data indicates that the previous 10 years provides an
improved estimate, this 10-year average is used. One of the primary drivers that
makes the previous 10 years a better predictor than the period from 1961-1990
is large trends in urbanization. Any city that has a strong warming trend will be
better approximated using the most recent 10 years than using NCEP’s 30-year
normal. An interesting issue is that the concept of OCN has not been defined
for determining the standard deviation of the degree days in different regions.

The simplest source for tackling the problem of “normal” climate conditions is
the National Climate Data Center (NCDC). The Midwest Climate Center
(MCC) has an online service where one may download daily average tempera-
tures for specific stations, as well as a range of other climate data, using the
NWS standard for degree days. With regard to this issue, the traded contracts
are referenced to a specific measurement station of the National Weather
Service. Each station has a unique NCDC number used to identify it in data-
bases such as MCC. NCDC also publishes archives of historical temperature
and precipitation data at US stations on CD ROM.

OCNs are not necessarily ideal in determining expected values in pricing
options. There are many ways to correct for non-stationary climate data. The
first step is to correct for trends, but the climate record contains variability on many time scales: from a few years to decades and longer. During an El Niño
year, for example, it would be very important to understand how El Niño skews
the climate statistics in the region of interest. For many seasonal contracts, the Gaussian model will be sufficient if one can obtain a good estimate of the mean and standard deviation of degree days.

The current long-range forecasts have quite limited accuracy. NCEP provides
seasonal forecasts using a range of tools. The market makers in the weather
market have proprietary long-range forecasts of varying levels of sophistication.
Further, many commercial forecast services produce long-range forecasts. It is
important to note that many long-range forecast products are of dubious quality.
In general, we have found that most commercial forecast providers cannot
quantify whether they have any forecast skill at all.

Hedging With Weather Options And Swaps
The great appeal of weather derivatives is that they can be used to hedge risks
in other components of an investment portfolio. Many businesses are exposed
to weather risk of some kind. The challenge in hedging is to cover these risks in
an effective manner. There is a great deal of discussion about using weather
options to hedge weather risk in energy markets, for example. Some care is nec-
essary in building a net position containing a physical commodity, such as gas
or power, along with weather options. In this case, weather options are a hedge
on volume, not on price.

While there is obviously a relationship between consumption volume and price,
the relationship is not one-to-one. The capacity to store natural gas is such that high demand may or may not lead to an increase in price in the near term. If
there is a large amount of gas in storage and the weather in winter turns cold, an end user might draw from storage if the price of gas on the spot market is high. In the electrical power market, there is no storage and price is much more sensitive to forecasts of unusually warm or cool weather. Still, the connection
between price and volume consumed involves some uncertainty, with production capacity being a key. If a nuclear reactor in a region is off line and
extremely warm weather appears in summer, the price of electricity in that
region may jump sharply. The ability to change net production is a key consideration that complicates the relationship between electricity price and weather.

The challenge in using weather options as a cross-commodity hedge is in deciding the model risk inherent in determining the fraction of risk that can be effectively hedged using a weather contract. This problem is not limited to power
and gas. In agricultural markets, common wisdom suggests that weather derivatives could be used to hedge yield, but not price. Statistical models can be
developed to couple weather risk to agricultural price risk. Great care must be
taken to determine the effectiveness and quality of the coupling model. As an
example of a possible hedge associated with corn price, we present an analysis
of the change in corn price from March to November in Iowa. Using multiple
linear regression, we have found that a large fraction of the variability in the
change in corn prices from March to November can be explained by cooling
degree days in Des Moines for two months.

The figure below shows the change in the price of Iowa corn from April to
December (black line) from 1958-1997. The grey line shows a model fitted to these price changes in terms of four variables: a trend in time, April price, July
CDDs in Des Moines and August CDDs in Des Moines. All four of these variables are statistically significant in explaining the variability in corn price.
August is more significant as a predictor than July. From these results, it is
clearly possible to hedge changes in corn price using Des Moines CDD monthly contracts. This model is highly statistically robust. We note that there is also a strong mean-reverting behavior in this model such that the correlation
between the Dec. – April price change is negatively correlated with April price.
If one were seeking to hedge against volatility in corn prices, weather derivatives may be an attractive avenue, depending upon the relative pricing of corn futures and options, and weather swaps and options.

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