payoff that depends on some measured aspect of the weather. Since the
future weather can be considered as random, the payoff of a weather derivative
is also random. The economic purpose of weather derivatives is to allow
companies that have profits that are affected by the weather to hedge some
or all of that risk. This can be illustrated by a simple example, adapted from
Jewson and Jones (2005):
A weather derivative example
ABC gas company doesn’t like warm winters because they sell less natural gas to
their domestic customers, who use the gas for heating their homes. ABC can lose
up to £10 million in a warm winter relative to an average year. They decide to use
weather derivatives to help hedge this warm winter risk. They analyse their historical
revenues against historical weather data and conclude that there is a high
correlation between their revenues and the total number of heating degree days
measured in London between November and March (note that heating degree
days, or HDDs, are a measure of the extent to which the temperature falls below
18 degrees Centrigrade, and, in this case, can be taken as a proxy for temperature
on an inverted scale). Because of this high correlation they decide to base
their weather derivative on a London November to March HDD index.
This has the advantage that there is a well-traded market on this index, which makes it
more likely that they will get a good price in the market because of the pricetransparency
brought about by such trading. In the first year of hedging they buy
a put option, which will pay them if the number of HDDs is low (corresponding
to a warm winter). A reasonable estimate of the average number of HDDs
at this location and over this period is 1670 HDDs, with a standard deviation of
120HDDs, and the distribution of possible numbers of HDDs is close to normal.
ABC decide to hedge themselves from 1650 HDDs downwards. They buy a put
option with a strike of 1650HDDs, a tick of £50,000/HDDand a limit of £10,000,000
(this limit corresponds to 200HDDs below the strike, or 1450 HDDs). They compare
quotes from a number of banks, and end up paying a premium of £2,000,000
for this contract. When the actual weather comes in at 1500 HDD they receive a
payout of £7,500,000, and hence make an overall profit on the weather derivative of
£5,500,000. This roughly balances themoneythey lose on their gas supply business.
In the second year they test a different strategy: they sell a swap with a strike of 1670
HDDs, a tick of £50,000/HDD, and limits at both ends of £10,000,000. Again the
weather comes in warmer than normal, this time at 1640 HDDs. Again, they lose
money on their gas business but make money on the weather derivative: this time
£1,500,000.
This example illustrates the following important points. First, weather
derivatives are based on weather measured at a specific location: in this
case, London (in a real example it would probably be London’s Heathrow
Airport, weather station 03772). Second, weather derivatives are based on
a weather index that has a single value per year: in this case, this index is
the total number of HDDs during the winter season for this location. Third,
there is a function that relates the value of the weather index to a payoff.
Puts, calls and swaps are the most common functions used, but any other
function is also possible. Swaps are typically traded without a premium,
while options have a premium. Fourth, weather derivatives may have a
limit on the financial payout. Typically, over the counter (OTC) contracts
have limits while exchange traded contracts do not.
The example given above is very typical of trades in the weather market.
Variations include:
(a) Using different locations: London, NewYork, Chicago andTokyo are the
most commonly traded locations, but many hundreds of other locations
have also been used, and any location with reliable weather measurements
is a potential candidate. For a hedger there may be a trade-off
between using a location at which the weather correlates highly with
their business, and using a commonly traded location for which better
prices would be available.
(b) Using different weather variables: the bulk of the current market is
based on temperature, but precipitation contracts are common, and
wind contracts have also traded.
(c) Using different indices: temperature contracts are usually based on
HDDs, as above, but can also be based on average temperature, the
sum of daily temperatures, the number of days where the temperature
exceeds a certain threshold, and so on.
(d) Using different time periods: monthly and seasonal contracts are the
most common, although there are also contracts traded OTC with time
periods as short as one hour.
(e) Using multiple locations or multiple variables at once in a single
contract.
(f) Combining the definition of the index with financial variables such as
gas price or power price.
The companies that sell weather derivatives to corporate hedgers like
ABC gas company in our example are typically banks, insurance companies
or hedge funds. Such companies endeavour to make a profit by selling
weather derivatives using one or more of a number of possible strategies.
Almost all such strategies involve selling more than one contract, and in
many cases may involve trading many hundreds of contracts. They then
have to consider the total financial risk in their portfolio.
Read More: WHAT ARE WEATHER DERIVATIVES?
