Weather Derivatives
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Transcript of Weather Derivatives
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.