Weather Risk Management

1
Weather Risk Management

• 1999 CAS Annual Meeting

2
What is Weather Risk?

• Uncertainty in earnings or cash flow caused by
  weather volatility.
• It can be the largest source of financial
  uncertainty for many companies - particularly
  energy companies.
• There are no physical markets or underlying
  commodities.
• Cannot be controlled (Mother Nature.)

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Weather Hedge Some Examples

• Utilities and energy companies can protect volume
  related-revenue
• Agricultural companies can protect earnings from
  freeze and drought
• Golf Course Management Companies can protect
  against a heavy rain season
• Sports Drink Manufacturers can protect against
  depressed earnings from a cool summer season
• Municipalities can protect snow removal budgets,
  utility costs, and maintain a more stable revenue
  flow from parks and beaches

4
Weather Risk Management Structures

• Climactic protection can be designed for
• Temperature (HDD/CDD)
• Precipitation or snowfall
• Humidity
• Wind speed

5
Heating and Cooling Degree Days

• Most temperature contracts in current practice
  are based on Heating Degree Days (HDD) for winter
  protection, and Cooling Degree Days (CDD) for
  summer protection.
• HDD Max (0, 65 F - average temperature in a
  day)
• CDD Max (0, average temperature in day - 65 F)

6
How Weather Options Work

• Pay off is based on a measurable index (CDD, HDD,
  etc)
• Pay off is based on how the index performs
  relative to a trigger or strike value - not on
  actual loss
• Coverage usually has a defined maximum limit

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Designing Coverage for the Client

• Identify the weather exposure, and the weather
  statistic associated with that risk.
• Determine the geographic areas where you have
  margins at risk. Identify related weather
  stations.
• Select a strike - normally 1/2 to 1 full standard
  deviation from the mean. Strikes closer to the
  mean are obviously more expensive, and clients
  should try to avoid dollar swapping.

8
Basic Types of Option Contracts

• Put Option - pays off if the index at the end of
  term is below the predetermined strike
• Call Option - pays off if the index at the end of
  term is above the predetermined strike
• Swap - pays off on both sides (above and below) a
  predetermined strike
• Collar, Strangle, Etc.

9
Coverage as Insurance or Derivatives

• Climate coverage can be structured as
• Derivatives - An international swap dealers
  association (ISDA) confirmation is issued to the
  client
• Insurance - an insurance policy is issued, but
  still indemnifies for loss based on a stated
  amount per unit of the index

10
Heating Degree Days - An Example

• Problem A natural gas supplier in the New York
  City area experiences large decreases in revenue
  during mild winters due to low heating demand.
  This significantly impacts earnings per share and
  puts downward pressure on their US stock price.
  Each lost heating degree day during the winter
  (below normal) decreases earnings by 50,000.
• Solution A Heating Degree Day (HDD) put option
  which pays 50,000 per heating degree day below
  the pre-determined strike.

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New York HDD Put Example

• Put Option Features
• Period Nov-Mar
• Strike 4,000
• Floor 3,800
• Tick 50,000
• Limit 10 mil
• Price 2.5 mil

12
Snowfall Cover - An Example

• Problem The municipality of Fort Wayne, IN has
  budgeted 1,000,000 for snow removal for the
  upcoming winter period. The budget allows for the
  removal of 12 inches of snow. The municipality
  estimates that for every 1/2 inch of snow in
  excess of 12, they incur 20,000 in additional
  product and labor costs.
• Solution A Snowfall call option which pays
  20,000 per 1/2 inch of snowfall above the
  pre-determined strike (i.e. 12 inches).

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Pricing of Exposure

• Historical Data
• Data Adjustments
• Stochastic Modeling

14
New York HDD Data

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Weather Data

• Historical data from NCDC
• 50 years or more available for most major cities.

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Data Adjustments

• Station Changes
• Trends
• Global Climate Cycles
• Urban Heat Island Effect
• Population Densities
• ENSO Cycles
• Forecasting

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Stochastic Modeling

• Fit Distribution to Weather Data
• Monte Carlo Simulation

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Issues

• State regulatory and legal issues that may arise
  with a new product
• Aggregate exposure management
• Overcoming an undeveloped and uneducated primary
  market
• Sophisticated market players
• Basis risk associated with selected weather
  station
• Basis risk associated with selected option
  structure

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Insurer/Reinsurer Participation

• Source of Premium/Revenue Growth
• Diversification of Risk Portfolio
• Risk Management Solutions for Clients
• Natural outgrowth - insurers already provide risk
  management solutions for natural events such as
  Hurricanes and Earthquakes.