Latest Developments in Latest Developments in Weather Risk Management Weather Risk Management presentation to presentation to “Risk Finance” “Risk Finance” , 22-24 March, 2004 , 22-24 March, 2004 The Finance and Treasury Association The Finance and Treasury Association Dr Harvey Stern, Dr Harvey Stern, Shoni Dawkins & Robin Hicks Shoni Dawkins & Robin Hicks Bureau of Meteorology, Melbourne Bureau of Meteorology, Melbourne
91
Embed
Dr Harvey Stern, Shoni Dawkins & Robin Hicks Bureau of Meteorology, Melbourne
Latest Developments in Weather Risk Management presentation to “Risk Finance” , 22-24 March, 2004 The Finance and Treasury Association. Dr Harvey Stern, Shoni Dawkins & Robin Hicks Bureau of Meteorology, Melbourne. Important WEB Sites. http://www.bom.gov.au - PowerPoint PPT Presentation
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
• Another significant development is the diversification of the types of contracts that were transacted.
• Temperature-related protection (for heat and cold) continues to be the most prevalent, making up over 82 percent of all contracts (92% last year)
• Rain-related contracts account for 6.9% (1.6% last year), snow for 2.2% (0.6% last year) and wind for 0.4% (0.3% last year).
Source: Weather Risk Management Association Annual Survey (2002)
• Another significant development is the diversification of the types of contracts that were transacted.
• Temperature-related protection (for heat and cold) continues to be the most prevalent, making up over 82 percent of all contracts (92% last year)
• Rain-related contracts account for 6.9% (1.6% last year), snow for 2.2% (0.6% last year) and wind for 0.4% (0.3% last year).
Source: Weather Risk Management Association Annual Survey (2002)
Views prior to the release of the Views prior to the release of the WRMA 2003 Survey ResultsWRMA 2003 Survey Results
Views prior to the release of the Views prior to the release of the WRMA 2003 Survey ResultsWRMA 2003 Survey Results
“Most market participants … are predicting an increase in total notional volumes”
“The general malaise that has clouded the weather risk market in the past year may be on the wane”
“…we will see a sizeable decrease in volumes … as Enron, Aquila … have left the market”
“The effect of market departures was clearly felt …[but]… big players more than compensated for the loss, providing liquidity and execution of service”
“…weather forecasting improvements could pose a threat to market development”
Energy Power Risk ManagementMay2003
“Most market participants … are predicting an increase in total notional volumes”
“The general malaise that has clouded the weather risk market in the past year may be on the wane”
“…we will see a sizeable decrease in volumes … as Enron, Aquila … have left the market”
“The effect of market departures was clearly felt …[but]… big players more than compensated for the loss, providing liquidity and execution of service”
“…weather forecasting improvements could pose a threat to market development”
Temperature related contracts 85% compared with 90% previously
Rain related contracts 8.6% compared with 6.9% previously
Wind-related contracts 1.6% compared with 0.3% previously
Snow related contracts 2.1% compared with 2.2% previously
Diversification Increasing:
Temperature related contracts 85% compared with 90% previously
Rain related contracts 8.6% compared with 6.9% previously
Wind-related contracts 1.6% compared with 0.3% previously
Snow related contracts 2.1% compared with 2.2% previously
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 three 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 three 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.
• 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.
• "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:
Outline of PresentationOutline of PresentationOutline of PresentationOutline of Presentation
• Sources of meteorological data, their quality control and application…
• Sources of meteorological data, their quality control and application…
Types of Data AvailableTypes of Data AvailableTypes of Data AvailableTypes of Data Available
• Rainfall – daily, monthly, seasonal, analyses,
• Temperature – hourly, maximum and minimum, dew point, monthly averages and extremes
• Wind speed, hourly , maximum wind gust, wind run
• Rainfall – daily, monthly, seasonal, analyses,
• Temperature – hourly, maximum and minimum, dew point, monthly averages and extremes
• Wind speed, hourly , maximum wind gust, wind run
Sources of ObservationsSources of ObservationsSources of ObservationsSources of Observations
• Bureau Staffed Sites– Fully trained
observers– Equipment
maintenance
• Bureau Staffed Sites– Fully trained
observers– Equipment
maintenance
Bureau StationsBureau StationsBureau StationsBureau Stations
• More automated observation sites• Automated data quality control
procedures to enable more checks to be performed
• More data and at higher frequencies
• Increased use of remotely sensed data for estimations in data sparse regions
• More automated observation sites• Automated data quality control
procedures to enable more checks to be performed
• More data and at higher frequencies
• Increased use of remotely sensed data for estimations in data sparse regions
Future trends in dataFuture trends in dataFuture trends in dataFuture trends in data
Solar radiation data – traditional network versus satellite derived estimates
Outline of PresentationOutline of PresentationOutline of PresentationOutline of Presentation
• Managing weather risk using daily weather forecasts and seasonal outlooks…
• Managing weather risk using daily weather forecasts and seasonal outlooks…
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”.
“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.
•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.
• 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.
An Illustration of theAn Illustration of theImpact of Forecasts Impact of Forecasts An Illustration of theAn Illustration of theImpact 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.
• 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 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 accuracy data in determining the risk.
• 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 accuracy data in determining the risk.
Forecast Accuracy Data
The Australian Bureau of Meteorology's Melbourne office possesses data about the accuracy of its temperature forecasts stretching back over 40 years.
Customers receiving weather forecasts have, recently, become increasingly interested in the quality of the service provided.
This reflects an overall trend in business towards implementing risk management strategies. These strategies include managing weather related risk.
Indeed, the US Company Aquila developed a web site that presents several illustrations of the concept:
Using Forecast Accuracy DataUsing Forecast Accuracy DataUsing Forecast Accuracy DataUsing Forecast Accuracy 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.
• 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 OptionPay-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
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.
• 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 OutcomesHistorical Distribution of OutcomesHistorical Distribution of Outcomes
Evaluating the 38 deg C Evaluating the 38 deg C Call Option (Part 1)Call Option (Part 1)
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….
• 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)
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.
• 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,