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Weather Derivatives Weather Derivatives [presentation to [presentation to Australian Barley Board Australian Barley Board , 9 September, 2004] , 9 September, 2004] Dr Harvey Stern Dr Harvey Stern Bureau of Meteorology, Melbourne Bureau of Meteorology, Melbourne

Weather Derivatives [presentation to Australian Barley Board, 9 September, 2004] Dr Harvey Stern Bureau of Meteorology, Melbourne Dr Harvey Stern Bureau

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Weather DerivativesWeather Derivatives

[presentation to [presentation to Australian Barley BoardAustralian Barley Board, 9 September, 2004], 9 September, 2004]

Weather DerivativesWeather Derivatives

[presentation to [presentation to Australian Barley BoardAustralian Barley Board, 9 September, 2004], 9 September, 2004]

Dr Harvey SternDr Harvey Stern

Bureau of Meteorology, MelbourneBureau of Meteorology, Melbourne

Dr Harvey SternDr Harvey Stern

Bureau of Meteorology, MelbourneBureau of Meteorology, Melbourne

Important WEB SitesImportant WEB SitesImportant WEB SitesImportant WEB Sites

• http://www.bom.gov.au

• http://www.artemis.bm/artemis.htm

• http://www.wrma.org

Outline of PresentationOutline of PresentationOutline of PresentationOutline of Presentation

• Recent Weather Risk Management (WRM) news.• WRM products.• Weather Derivatives.• Hedging Applications.• Current state of the global WRM market.

• Recent Weather Risk Management (WRM) news.• WRM products.• Weather Derivatives.• Hedging Applications.• Current state of the global WRM market.

The Noah RuleThe Noah RuleThe Noah RuleThe Noah Rule

“Predicting rain doesn’t count;

Building arks does”.

Warren Buffett,Australian Financial Review,11 March 2002.

“Predicting rain doesn’t count;

Building arks does”.

Warren Buffett,Australian Financial Review,11 March 2002.

Some Recent NewsSome Recent NewsSome Recent NewsSome Recent News

• The next few slides illustrate some recent news.• The next few slides illustrate some recent news.

Foundation of the Weather MarketFoundation of the Weather MarketFoundation of the Weather MarketFoundation of the Weather Market

“The foundation of today’s financial weather contracts is in the US power market …

For the weather-sensitive end-user, not to hedge is to gamble on the weather.”

Robert S. Dischell

“The foundation of today’s financial weather contracts is in the US power market …

For the weather-sensitive end-user, not to hedge is to gamble on the weather.”

Robert S. Dischell

The Asia-Pacific RegionThe Asia-Pacific RegionThe Asia-Pacific RegionThe Asia-Pacific Region

• Interest in weather risk management has grown in the Asia-Pacific Region (covering electricity, gas, & agriculture). Countries involved include:

- Japan;- Korea; and,- Australia/New Zealand.

Source: Weather Risk Management Association.

• Interest in weather risk management has grown in the Asia-Pacific Region (covering electricity, gas, & agriculture). Countries involved include:

- Japan;- Korea; and,- Australia/New Zealand.

Source: Weather Risk Management Association.

Australian Developments Australian Developments 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 four years ago.

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

• Partnerships are emerging between merchant banks and weather forecasting companies.

• 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 four years ago.

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

• Partnerships are emerging between merchant banks and weather forecasting companies.

Weather-linked SecuritiesWeather-linked SecuritiesWeather-linked SecuritiesWeather-linked Securities

• 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.

• 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.

SecuritisationSecuritisationSecuritisationSecuritisation

• The reinsurance industry experienced several catastrophic 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 (including weather-related risks).

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

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

• The reinsurance industry experienced several catastrophic 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 (including weather-related risks).

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

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

Catastrophe BondsCatastrophe BondsCatastrophe BondsCatastrophe Bonds

• A catastrophe (cat) bond is an exchange of principal for periodic coupon payments wherein the payment of the coupon and/or the return of the principal of the bond is linked to the occurrence of a specified catastrophic event.

• The coupon is given to the investor upfront, who posts the notional amount of the bond in an account.

• If there is an event, investors may lose a portion of (or their entire) principal.

• If there is no event, investors preserve their principal and earn the coupon.

Source: Canter & Cole at http://www.cnare.com

• A catastrophe (cat) bond is an exchange of principal for periodic coupon payments wherein the payment of the coupon and/or the return of the principal of the bond is linked to the occurrence of a specified catastrophic event.

• The coupon is given to the investor upfront, who posts the notional amount of the bond in an account.

• If there is an event, investors may lose a portion of (or their entire) principal.

• If there is no event, investors preserve their principal and earn the coupon.

Source: Canter & Cole at http://www.cnare.com

Catastrophe SwapsCatastrophe SwapsCatastrophe SwapsCatastrophe Swaps

• A catastrophe (cat) swap is an alternative structure, but returns are still linked to the occurrence of an event.

• However, with swaps, there is no exchange of principal.• The coupon is still given to the investor upfront, but the

structure enables investors to invest the notional amount of the bond in a manner of his own choosing.

Source: Canter & Cole at http://www.cnare.com

• A catastrophe (cat) swap is an alternative structure, but returns are still linked to the occurrence of an event.

• However, with swaps, there is no exchange of principal.• The coupon is still given to the investor upfront, but the

structure enables investors to invest the notional amount of the bond in a manner of his own choosing.

Source: Canter & Cole at http://www.cnare.com

Weather DerivativesWeather DerivativesWeather DerivativesWeather Derivatives

• Weather derivatives 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.

• Weather derivatives 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.

Derivative or Insurance?Derivative or Insurance?Derivative or Insurance?Derivative or Insurance?

• 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.

• 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.

A Weather-linked OptionA Weather-linked OptionA Weather-linked OptionA Weather-linked Option

• An example of a weather linked option is the Cooling Degree Day (CDD) Call Option.

• Total CDDs 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”, the seller pays

the buyer a certain amount for each CDD above “the strike”.

• An example of a weather linked option is the Cooling Degree Day (CDD) Call Option.

• Total CDDs 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”, the seller pays

the buyer a certain amount for each CDD above “the strike”.

Specifying the CDD Call OptionSpecifying the CDD Call OptionSpecifying 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.

• 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

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

An Historical Note: An Historical Note: An Early ExampleAn Early Example

An Historical Note: An Historical Note: 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.

• 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.

Carbon Disclosure Project (2003)Carbon Disclosure Project (2003)Carbon Disclosure Project (2003)Carbon Disclosure Project (2003)

• "Investors failing to take account of climate change and carbon finance issues in the asset allocation and equity valuations may be exposed to significant risks which, if left unattended, will have serious investment repercussions over the course of time."

• "Investors failing to take account of climate change and carbon finance issues in the asset allocation and equity valuations may be exposed to significant risks which, if left unattended, will have serious investment repercussions over the course of time."

Cooling Degree Days (1855-2000)Cooling Degree Days (1855-2000)(and climate change)(and climate change)

Cooling Degree Days (1855-2000)Cooling Degree Days (1855-2000)(and climate change)(and climate change)

• Frequency distribution of annual Cooling Degree Days at Melbourne using all data:

• Frequency distribution of annual Cooling Degree Days at Melbourne using all data:

Cooling Degree Days (1971-2000)Cooling Degree Days (1971-2000) (and climate change)(and climate change)

Cooling Degree Days (1971-2000)Cooling Degree Days (1971-2000) (and climate change)(and climate change)

• Frequency distribution of annual Cooling Degree Days at Melbourne using only recent data:

• Frequency distribution of annual Cooling Degree Days at Melbourne using only recent data:

Should Companies Worry? Should Companies Worry? 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.

• 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.

Weather-related Industry RiskWeather-related Industry RiskWeather-related Industry RiskWeather-related Industry Risk

"Shares in Harvey Norman fell almost 4 per cent yesterday as a cool summer and a warm start to winter cut into sales growth at the furniture and electrical retailer's outlets… Investors were expecting better and marked the shares down 3.8 per cent to a low of $3.55…

Sales at Harvey Norman were hit on two fronts. Firstly, air conditioning sales were weak because of the cool summer, and a warmer than usual start to winter had dampened demand for heating appliances”.

Source: The Australian of 18 April, 2002

"Shares in Harvey Norman fell almost 4 per cent yesterday as a cool summer and a warm start to winter cut into sales growth at the furniture and electrical retailer's outlets… Investors were expecting better and marked the shares down 3.8 per cent to a low of $3.55…

Sales at Harvey Norman were hit on two fronts. Firstly, air conditioning sales were weak because of the cool summer, and a warmer than usual start to winter had dampened demand for heating appliances”.

Source: The Australian of 18 April, 2002

Weather-related Agricultural RiskWeather-related Agricultural RiskWeather-related Agricultural RiskWeather-related Agricultural Risk

“The Australian sugar industry is facing its fifth difficult year in a row with a drought dashing hopes of an improved crop in Queensland, where 95% of Australia's sugar is grown...

Whilst dry weather during the May-December harvest period is ideal for cane, wet weather during this time causes the mature cane to produce more shoots and leaves, reducing its overall sugar content”.

(Australian Financial Review of 8 May, 2002)

“The Australian sugar industry is facing its fifth difficult year in a row with a drought dashing hopes of an improved crop in Queensland, where 95% of Australia's sugar is grown...

Whilst dry weather during the May-December harvest period is ideal for cane, wet weather during this time causes the mature cane to produce more shoots and leaves, reducing its overall sugar content”.

(Australian Financial Review of 8 May, 2002)

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

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 (i.e. accuracy) 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).

• The era of (mostly) categorical forecasts.

• The rapid increase in the application of probability forecasts.

• The provision of forecast verification (i.e. accuracy) 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).

Pricing Derivatives

There are three approaches that may be applied to the pricing of derivatives.

These are:

•Historical simulation (applying "burn analysis");

•Direct modelling of the underlying variable’s distribution (assuming, for example, that the variable's distribution is normal); and,

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

Returning to the Cane GrowerReturning to the Cane GrowerReturning to the Cane GrowerReturning to the Cane Grower

• Suppose that our cane grower has experienced an extended period of drought.

• Suppose that if rain doesn't fall next month, a substantial financial loss will be suffered.

• How might our cane grower protect against exceptionally dry weather during the coming month?

• Suppose that our cane grower has experienced an extended period of drought.

• Suppose that if rain doesn't fall next month, a substantial financial loss will be suffered.

• How might our cane grower protect against exceptionally dry weather during the coming month?

One ApproachOne ApproachOne ApproachOne Approach

• One approach could be to purchase a Monthly Rainfall Decile 4 Put Option.

• Assume that our cane grower decides only to take this action when there is already a risk of a dry month.

• That is, when the current month's Southern Oscillation Index (SOI) is substantially negative.

• So, the example is applied only to the cases when the current month's Southern Oscillation Index (SOI) is in the lowest 5% of possible values, that is, below -16.4.

• One approach could be to purchase a Monthly Rainfall Decile 4 Put Option.

• Assume that our cane grower decides only to take this action when there is already a risk of a dry month.

• That is, when the current month's Southern Oscillation Index (SOI) is substantially negative.

• So, the example is applied only to the cases when the current month's Southern Oscillation Index (SOI) is in the lowest 5% of possible values, that is, below -16.4.

Specifying the Decile 4 Put OptionSpecifying the Decile 4 Put OptionSpecifying the Decile 4 Put OptionSpecifying the Decile 4 Put Option

• Strike: Decile 4. • Notional: $100 per Decile (< Decile 4).• If, at expiry, the Decile is < Decile 4, the seller of the option

pays the buyer $100 for each Decile < Decile 4.

• Strike: Decile 4. • Notional: $100 per Decile (< Decile 4).• If, at expiry, the Decile is < Decile 4, the seller of the option

pays the buyer $100 for each Decile < Decile 4.

Payoff Chart for Decile 4 Put OptionPayoff Chart for Decile 4 Put OptionPayoff Chart for Decile 4 Put OptionPayoff Chart for Decile 4 Put Option

Outcomes for Decile 4 Put OptionOutcomes for Decile 4 Put OptionOutcomes for Decile 4 Put OptionOutcomes for Decile 4 Put Option

Evaluating the Decile 4 Put OptionEvaluating the Decile 4 Put OptionEvaluating the Decile 4 Put OptionEvaluating the Decile 4 Put Option

• 14.2% cases of Decile 1 yields $(.142)x(4-1)x100=$42.60• 13.2% cases of Decile 2 yields $(.132)x(4-2)x100=$26.40• 8.4% cases of Decile 3 yields $(.084)x(4-3)x100=$8.40• The other 25 cases (Decile 4 or above) yield nothing.

…leading to a total of $77.40, which is the price of our put option.

• 14.2% cases of Decile 1 yields $(.142)x(4-1)x100=$42.60• 13.2% cases of Decile 2 yields $(.132)x(4-2)x100=$26.40• 8.4% cases of Decile 3 yields $(.084)x(4-3)x100=$8.40• The other 25 cases (Decile 4 or above) yield nothing.

…leading to a total of $77.40, which is the price of our put option.

Weather & Climate ForecastsWeather & Climate ForecastsWeather & Climate ForecastsWeather & Climate Forecasts

• Daily weather forecasts may be used to manage short-term risk (e.g. pouring concrete).

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

• Forecasts are based on a combination of solutions to the equations of physics, and some statistical techniques.

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

• Daily weather forecasts may be used to manage short-term risk (e.g. pouring concrete).

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

• Forecasts are based on a combination of solutions to the equations of physics, and some statistical techniques.

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

Finally … Ensemble ForecastingFinally … Ensemble ForecastingFinally … Ensemble ForecastingFinally … Ensemble Forecasting

• Another approach to obtaining a measure of forecast uncertainty, is to use ensemble weather forecasts.

• The past decade has seen the implementation of these operational 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.

• A parallel approach is to “run” different models with the same initial analysis

• Spot the differences on the next slide …

• Another approach to obtaining a measure of forecast uncertainty, is to use ensemble weather forecasts.

• The past decade has seen the implementation of these operational 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.

• A parallel approach is to “run” different models with the same initial analysis

• Spot the differences on the next slide …

Weather Risk Management Association

June 10, 2004

Results of 2004 Pricewaterhouse Coopers

Survey…

Results of 2004 Pricewaterhouse Coopers

Survey…

Weather Events Determining Contingent Payments

Weather Measures Depending Exclusively on Temperature

Heating-degree-days measured in FahrenheitHeating-degree-days measured in CelsiusCooling-degree-days measured in FahrenheitCooling-degree-days measured in CelsiusOther exclusively temperature-based measures

Weather Measures Not Depending Exclusively on Temperature

Any measure based exclusively on rainfallAny measure based exclusively on snowfallAny measure based exclusively on windAny other measure, including combinations of the above

Geographic Regions Where Weather Events are Measured

AsiaAustralian Continent

EuropeNorth America, West

North America, MidwestNorth America, East

North America, SouthOther

Reported values weighted by number of trades reported by respondent.

56%

13%

9% 7%4%

11%

Energy

Agriculture

Retail

Construction

Transportation

Other

Total Notional Value (in millions of U.S. dollars)Total Notional Value (in millions of U.S. dollars)

$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

$5,000

2000/1 2001/2 2002/3 2003/4

CME

Winter

Summer

$2,517

$4,339$4,188

$4,578

Distribution of Number of Contracts by Type(No CME trades)

Distribution of Number of Contracts by Type(No CME trades)

0%

20%

40%

60%

80%

100%

2001/2 2002/3 2003/4

Other

Wind

Snow

Rain

Oth Temp

CDD

HDD

Trades by Type of Contract, 2003-4 SurveyTrades by Type of Contract, 2003-4 Survey

Shares including CME trades: HDD: 56%, CDD: 19%, Other

Temp: 20%, Other: 4%.

Number of Trades (No CME)

49%

18%

17%

16%

HDD CDD Oth Temp Other

Notional Value (No CME)

52%

9%

32%

7%

HDD CDD Oth Temp Other

Distribution of Total Number of Contracts by Region

(No CME Trades)

Distribution of Total Number of Contracts by Region

(No CME Trades)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2000/1 2001/2 2002/3 2003/4

Other

Europe

Asia

NA East

NA Mwest

NA South

NA West

Share of Counter-parties Not Participating in Survey

(As a share of total number of contracts)

Share of Counter-parties Not Participating in Survey

(As a share of total number of contracts)

6074 74

61

0

10

20

30

40

50

60

70

80

2000/1 2001/2 2002/3 2003/4

SummarySummary

• The total value of trades in the 2003/4 survey reached $4.6 billion

• The CME again experienced significant increases in both the number of trades and the value of those trades

• The characteristics of the OTC market based on the 2003/4 Survey are similar to the results from last year in terms of type of contracts and geographic distribution

• The total value of trades in the 2003/4 survey reached $4.6 billion

• The CME again experienced significant increases in both the number of trades and the value of those trades

• The characteristics of the OTC market based on the 2003/4 Survey are similar to the results from last year in terms of type of contracts and geographic distribution