DERIVATIVES AS A RISK MANAGEMENT TOOL
By Robert E Katz, MComm CA (SA)
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.
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,
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,
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,
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
- 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
- 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
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
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
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;
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;
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
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
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:
- 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
- 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,
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,
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
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
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
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
“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
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).
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,
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