Weather Derivatives

Dr Harvey Stern,Dr Harvey Stern,Victorian Regional OfficeVictorian Regional Office

Weather Services Planning Conference

Friday 19 April 10.15am-10.45am

The Noah RuleThe Noah Rule

“Predicting rain doesn’t count;Building arks does”.

Warren Buffett,Australian Financial Review,11 March 2002.

Outline of PresentationOutline of Presentation

• Some recent developments in weather risk.

• Applications of weather derivatives.

• Utilising forecast accuracy and other databases.

• Role of ensemble weather forecasting.

• Recommendations to enable the BoM to keep abreast of devlopments in this growing sector of weather services.

IntroductionIntroduction

• The meteorological community is becoming increasingly skilled at applying weather-related risk management products.

• Most of these products originate from the financial markets.

• It is the energy sector (in the USA) that has, so far, taken best advantage of the growing weather-risk market.

The words of O. G. SuttonThe words of O. G. Sutton“The analogy between meteorology and astronomy is often made

… There is a closer resemblance, to my mind, between meteorology and economics. Both deals fundamentally with the problem of energy transformations and distribution

- in economics, the transformation of labour into goods and their subsequent exchange and distribution;

- in meteorology, transformation and distribution of the energy received from the sun. Both are subject to extremely capricious external influences.”

(from “Mathematics and the future of meteorology”, Weather, October, 1951)

BackgroundBackground

• The property and casualty reinsurance industry experienced several major events during the late 1980s & early 1990s.

• The ensuing industry restructuring saw the creation of new risk-management tools.

• These tools included securitisation of insurance risks.

• A third party issues these securities.

• The securities provide a return structured in a manner related to the occurrence (or otherwise) of an adverse event.

Weather Risk Weather Risk

• Weather risk is one of the biggest uncertainties facing Australian business.

- We get droughts, floods, fire, and cyclones.

• Economic adversity is not restricted to disaster conditions.

- A mild winter ruins a ski season, dry weather reduces crop yields, & rain shuts-down entertainment & construction.

- Recently, a brewer blamed an earnings decrease on a cool summer.

Securitisation of Weather RiskSecuritisation of Weather Risk

• Weather securitisation may be defined as the conversion of the abstract concept of weather risk into packages of securities.

• These may then be sold as income-yielding structured products.

ForecastsForecasts

• Weather forecasts may be used to manage risk associated with short-term activities (e.g. pouring concrete).

• Climate forecasts may be used to manage risk associated with long-term activities (e.g. sowing crops).

• With the focus upon managing risk, the forecasts are increasingly being couched in probabilistic terms.

The Road toThe Road toWeather Risk Management. Weather Risk Management.

• The era of (mostly) categorical forecasts.

• The rapid increase in the application of probability forecasts.

• The provision of forecast verification data.

• The era of the “guaranteed forecast”, with user communities being compensated for an inaccurate prediction.

• The purchase of “stakes” in the industry (by multi-national companies).

Australian Developments Australian Developments • For many years, the power industry has received detailed

weather forecasts from the Bureau.

• Now, Australia has joined the global trend towards an increased focus on the management of weather-related risk.

• The first instance of an (Australian) weather derivative trade occurred about two years ago.

• A number of businesses have now moved into the trading of weather risk products, almost all “over the counter”.

• Partnerships between merchant banks and weather forecasting companies.

Weather-risk & the Financial MarketsWeather-risk & the Financial Markets

• Weather-linked securities have prices which are linked to the historical weather in a region.

• They provide returns related to weather observed in the region subsequent to their purchase.

• They therefore may be used to help firms hedge against weather related risk.

• They also may be used to help speculators monetise their view of likely weather patterns.

Should Companies Worry? Should Companies Worry?

• In the good years, companies make big profits.

• In the bad years, companies make losses.

- Doesn’t it all balance out?

- No. it doesn’t.

• Companies whose earnings fluctuate wildly receive unsympathetic hearings from banks and potential investors.

What is a What is a DerivativeDerivative??

A Derivative is a financial instrumentwhose value is derived from

the value of some other financial variable.

A Familiar ExampleA Familiar Exampleof a of a DerivativeDerivative..

A familiar example of Derivatives were theTELSTRA Instalment Receipts.

Their value fluctuated in accordance withfluctuations in the value of TELSTRA shares.

What is a What is a Weather DerivativeWeather Derivative??

A Weather Derivative is a financial instrumentwhose value is derived from the

magnitude of some weather variable.

Expanding the DefinitionExpanding the Definition

• Weather derivatives are financial instruments that are utilised to manage weather (& climate) related risk.

• They are similar to conventional financial derivatives.

• The basic difference lies in the underlying variables that determine the pay-offs.

• These underlying variables include temperature, precipitation, wind, and heating (& cooling) degree days.

DerivativeDerivative or or InsuranceInsurance??

A Derivative: -has ongoing economic value, -is treated like any other commodity, -is accounted for daily, & -may therefore affect a company’s credit rating.An Insurance Contract: -is not regarded as having economic value, & -therefore does not affect a company’s credit rating.

Some Important IssuesSome Important Issues

• Quality of weather and climate data.

• Changes in the characteristics of observation sites.

• Security of data collection processes.

• Privatisation of weather forecasting services.

• Value of data.

• Climate change.

An Early ExampleAn Early Example

• In 1992, the present author explored a methodology to assess the risk of climate change.

• Option pricing theory was used to value instruments that might apply to temperature fluctuations and long-term trends.

• The methodology provided a tool to cost the risk faced (both risk on a global scale, and risk on a company specific scale).

• Such securities could be used to help firms hedge against risk related to climate change.

Another ExampleAnother Example

• A common example is the Cooling Degree Day (CDD) Call Option.

• Total CDDs in a season is defined as the accumulated number of degrees the daily mean temperature is above a base figure.

• This is a measure of the requirement for cooling.

• If accumulated CDDs exceed “the strike”, then the seller pays the buyer a certain amount for each CDD above “the strike”.

Specifying the CDD Call OptionSpecifying the CDD Call Option

• Strike: 400 CDDs.

• Notional: $100 per CDD (> 400 CDDs).

• If, at expiry, the accumulated CDDs > 400, the seller of the option pays the buyer $100 for each CDD > 400.

Pay-off Chart for the CDDPay-off Chart for the CDDCall OptionCall Option

Approaches to PricingApproaches to Pricing

• Historical simulation.

• Direct modeling of the underlying variable’s distribution.

• Indirect modeling of the underlying variable’s distribution (via a Monte Carlo technique).

Significant Long-term TrendsSignificant Long-term Trends• Some weather elements have trended significantly.

• Trends need to be considered when valuing weather securities (such as CDD Call Options).

• The trend in the minimum temperature at Melbourne (Australia) is shown here.

Cooling Degree Days (1855-2000) Cooling Degree Days (1855-2000)

• The chart shows frequency distribution of annual accumulated Cooling Degree Days at Melbourne using all data:

Cooling Degree Days (1971-2000) Cooling Degree Days (1971-2000)

• The chart shows frequency distribution of annual accumulated Cooling Degree Days at Melbourne using only recent data:

Pricing the CDD Call OptionPricing the CDD Call Option

• The two CDD frequency distributions are quite different.

• Utilising the different data in valuation results in different prices.

• Utilising 1855-2000 data yields a price thus: $(.051x2500+.045x7500+.008x12500)= $565.00

• Utilising 1971-2000 data yields a price thus: $(.238x2500+.119x7500+.029x12500)= $1850.00

• The more recent frequency distribution should provide a more relevant result.

An Option linked to a Climate IndexAn Option linked to a Climate Index

• Suppose we define a rainfall put option, to apply when the Southern Oscillation Index (SOI) is in the lowest three deciles.

• Location: Echuca.

• Strike: Decile 4.

• Notional: $100 per decile below Decile 4.

- If, at expiry, the rainfall Decile is less than 4, then the seller of the option pays the buyer $100 for each Decile below 4.

Pay-off Chart for Decile 4 Put OptionPay-off Chart for Decile 4 Put Option

Rainfall DistributionRainfall Distribution

• To value the put option one uses data giving actual distribution of rainfall for cases when the SOI is in the lowest 3 deciles.

Evaluating the Decile 4 Put OptionEvaluating the Decile 4 Put Option

• 9 cases of Decile 1 yields $(4-1)x9x100=$2700

• 6 cases of Decile 2 yields $(4-2)x6x100=$1200

• 4 cases of Decile 3 yields $(4-3)x4x100=$400

• The other 25 cases (Decile 4 or above) yield nothing.

…leading to a total of $4300, and an average contribution of $98, which is the price of our put option.

• Later, a catastrophe bond, which may be issued to provide protection in the case of drought, will be described.

Impact of Forecasts Impact of Forecasts

• When very high temperatures are forecast, there may be a rise in electricity prices.

• The electricity retailer then needs to purchase electricity (albeit at a high price).

• This is because, if the forecast proves to be correct, prices may “spike” to extremely high (almost unaffordable) levels.

Impact of Forecast Accuracy Impact of Forecast Accuracy

• If the forecast proves to be an “over-estimate”, however, prices will fall back.

• For this reason, it is important to take into account forecast verification data in determining the risk.

Using Forecast Verification DataUsing Forecast Verification Data

• Suppose we define a 38 deg C call option (assuming a temperature of at least 38 deg C has been forecast).

• Location: Melbourne.

• Strike: 38 deg C.

• Notional: $100 per deg C (above 38 deg C).

• If, at expiry (tomorrow), the maximum temperature is greater than 38 deg C, the seller of the option pays the buyer $100 for each 1 deg C above 38 deg C.

Pay-off Chart: 38 deg C Call OptionPay-off Chart: 38 deg C Call Option

Determining the Price of theDetermining the Price of the38 deg C Call Option38 deg C Call Option

• Between 1960 and 2000, there were 114 forecasts of at least 38 deg C.

• The historical distribution of the outcomes are examined.

Historical Distribution of OutcomesHistorical Distribution of Outcomes

Evaluating the 38 deg C Evaluating the 38 deg C Call Option (Part 1)Call Option (Part 1)

• 1 case of 44 deg C yields $(44-38)x1x100=$600

• 2 cases of 43 deg C yields $(43-38)x2x100=$1000

• 6 cases of 42 deg C yields $(42-38)x6x100=$2400

• 13 cases of 41 deg C yields $(41-38)x13x100=$3900

• 15 cases of 40 deg C yields $(40-38)x15x100=$3000

• 16 cases of 39 deg C yields $(39-38)x16x100=$1600

cont….

Evaluating the 38 deg C Evaluating the 38 deg C Call Option (Part 2)Call Option (Part 2)

• The other 61 cases, associated with a temperature of 38 deg C or below, yield nothing.

• So, the total is $12500.

• This represents an average contribution of $110 per case, which is the price of our option.

A Forecast Error Put OptionA Forecast Error Put Option (defining error as predicted minus observed)(defining error as predicted minus observed)

• Strike: 0 deg C.• Notional: $100 per degree of forecast error below 0 deg C• If the forecast underestimates the actual temperature, then the

seller of the option pays the buyer $100 for each 1 deg C of underestimation.

- Historical simulation yields a suggested price of $67 for our put option.

Particularly Australian ApplicationsParticularly Australian Applications

• Purchase of put contracts to protect against reduced rainfall, by a generator of hydroelectricity.

• Purchase of call contracts to protect against a sequence of very hot days.

• Purchase of variable degree day contracts to protect against very high temperatures.

• Purchase of guaranteed yield contracts (based on relationships between wheat yield & rainfall and temperature).

Ensemble ForecastingEnsemble Forecasting

• In order to obtain a measure of forecast uncertainty, there is an alternative to using historical forecast verification data.

• This is to use ensemble weather forecasts

• Ensemble weather forecasts are derived by imposing a range of perturbations on the initial analysis.

• Uncertainty associated with the forecasts may be derived by analysing the probability distributions of the outcomes.

Concluding RemarksConcluding Remarks

• The sophistication of weather-related risk management products is growing.

• Australia has joined this new market.

• In evaluating weather securities, one may use a variety of data types, and take into account climate trends.

• Ensemble forecasting is an alternative approach to determining forecast uncertainty.

RecommendationsRecommendations

• In order to keep abreast of developments in this growing sector of weather services…

- That the BoM join the Weather Risk Management Association.

- That the BoM be represented at risk management conferences.

- That the BoM develop a program of research into weather risk management.

- That the BoM subscribe to a variety of risk management journals.